kircherlab / cadd-scripts Goto Github PK

Hi,

I installed CADD v 1.7 and downloaded the annotations/prescored files separately and put them in the appropriate folders. I then run ./CADD.sh test/input.vcf to test the software, then I get this error

CADD-v1.7 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health at Charité - Univ
ersitätsmedizin Berlin 2013-2023. All rights reserved.
Running snakemake pipeline:
snakemake /tmp/tmp.5xupN9W1bE/input.tsv.gz --use-conda --conda-prefix /RUN/CADD-scripts-1.7/envs/conda --cores 1
--configfile /RUN/CADD-scripts-1.7/config/config_GRCh38_v1.7_noanno.yml --snakefile /RUN/CADD-scripts-1.7/Snakefile -q
Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 1 (use --cores to define parallelism)
Rules claiming more threads will be scaled down.
Job stats:
job         count
--------  -------
join            1
prepare         1
prescore        1
total           3

Select jobs to execute...
Activating conda environment: envs/conda/000a02fda4f9a3dacbe9a7c94df2b69c_
Select jobs to execute...
Activating conda environment: envs/conda/000a02fda4f9a3dacbe9a7c94df2b69c_
Removing temporary output /tmp/tmp.5xupN9W1bE/input.prepared.vcf.
Select jobs to execute...
Activating conda environment: envs/conda/fb032738807041aeaadfd1bd59628e1f_
Smartmatch is experimental at /RUN/CADD-scripts-1.7/envs/conda/fb032738807041aeaadfd1bd59628e1f_/share/ensembl-vep-110.1-0/module
s/Bio/EnsEMBL/VEP/AnnotationSource/File.pm line 472.
Removing temporary output /tmp/tmp.5xupN9W1bE/input.novel.vcf.
Select jobs to execute...
Activating conda environment: envs/conda/57cd93e005aa8f80b32c43193d51c129_
[Tue Apr 23 09:22:54 2024]
Error in rule annotate_esm:
    jobid: 10
    input: /tmp/tmp.5xupN9W1bE/input.vep.vcf.gz, data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_1.pt, data/annotations/GRC
h38_v1.7/esm/esm1v_t33_650M_UR90S_2.pt, data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_3.pt, data/annotations/GRCh38_v1.7/
esm/esm1v_t33_650M_UR90S_4.pt, data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_5.pt, data/annotations/GRCh38_v1.7/esm/pep.1
10.fa
    output: /tmp/tmp.5xupN9W1bE/input.esm_missens.vcf.gz, /tmp/tmp.5xupN9W1bE/input.esm_frameshift.vcf.gz, /tmp/tmp.5xupN9W1bE/in
put.esm.vcf.gz
    log: /tmp/tmp.5xupN9W1bE/input.annotate_esm.log (check log file(s) for error details)
    conda-env: /RUN/CADD-scripts-1.7/envs/conda/57cd93e005aa8f80b32c43193d51c129_
    shell:

        model_directory=`dirname data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_1.pt`;
        model_directory=`dirname $model_directory`;

        python /RUN/CADD-scripts-1.7/src/scripts/lib/tools/esmScore/esmScore_missense_av_fast.py         --input /tmp/tmp.5xupN9W
1bE/input.vep.vcf.gz         --transcripts data/annotations/GRCh38_v1.7/esm/pep.110.fa         --model-directory $model_directory
 --model esm1v_t33_650M_UR90S_1  --model esm1v_t33_650M_UR90S_2  --model esm1v_t33_650M_UR90S_3  --model esm1v_t33_650M_UR90S_4
--model esm1v_t33_650M_UR90S_5          --output /tmp/tmp.5xupN9W1bE/input.esm_missens.vcf.gz --batch-size 1 &> /tmp/tmp.5xupN9W1
bE/input.annotate_esm.log

        python /RUN/CADD-scripts-1.7/src/scripts/lib/tools/esmScore/esmScore_frameshift_av.py         --input /tmp/tmp.5xupN9W1bE
/input.esm_missens.vcf.gz         --transcripts data/annotations/GRCh38_v1.7/esm/pep.110.fa         --model-directory $model_dire
ctory --model esm1v_t33_650M_UR90S_1  --model esm1v_t33_650M_UR90S_2  --model esm1v_t33_650M_UR90S_3  --model esm1v_t33_650M_UR90
S_4  --model esm1v_t33_650M_UR90S_5          --output /tmp/tmp.5xupN9W1bE/input.esm_frameshift.vcf.gz --batch-size 1 &>> /tmp/tmp
.5xupN9W1bE/input.annotate_esm.log

        python /RUN/CADD-scripts-1.7/src/scripts/lib/tools/esmScore/esmScore_inFrame_av.py         --input /tmp/tmp.5xupN9W1bE/in
put.esm_frameshift.vcf.gz         --transcripts data/annotations/GRCh38_v1.7/esm/pep.110.fa         --model-directory $model_dire
ctory --model esm1v_t33_650M_UR90S_1  --model esm1v_t33_650M_UR90S_2  --model esm1v_t33_650M_UR90S_3  --model esm1v_t33_650M_UR90
S_4  --model esm1v_t33_650M_UR90S_5          --output /tmp/tmp.5xupN9W1bE/input.esm.vcf.gz --batch-size 1 &>> /tmp/tmp.5xupN9W1bE
/input.annotate_esm.log

        (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)

Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message
Complete log: .snakemake/log/2024-04-23T092250.542307.snakemake.log

Can you diagnose what's wrong and how to solve this?

Thank you
Yot

I am trying to install the CADD tool v1.6. i downloaded the Zip file from GitHub and installed snakemake, when i runned the install.sh in a new conda environment and am getting some conflict error.
I am attaching the error file here.
v.16_error.txt

I also tried to install version 1.5 and am getting some conflict error and also attaching the error message here.

v1.5_error.txt

I wanted to execute CADD and any help will be appreciable.

Thank you in advance.

The mmsplice environment tries to install python 3.6. Most packages successfully install, but mmsplice relies on a few packages which require setuptools>=61.0.0 which is not available for python 3.6. Any advice on how to get around this issue?

mamba env create -f mmsplice.yml

bioconda/linux-64 Using cache
bioconda/noarch Using cache
conda-forge/linux-64 Using cache
conda-forge/noarch Using cache
pkgs/main/noarch No change
pkgs/r/linux-64 No change
pkgs/r/noarch No change
pkgs/main/linux-64 No change

Transaction

Prefix: /home/david/micromamba/envs/mmsplice

Updating specs:

• python
• cython=0.29.13
• pyranges=0.0.51
• libgcc=7.2.0
• tensorflow
• keras=2.2.4
• numpy=1.16.1
• scikit-learn
• cyvcf2=0.8.4
• pandas[version='<0.25.0']
• pysam
• htslib
• pip

Package Version Build Channel Size
──────────────────────────────────────────────────────────────────────────────────────────────────
Install:
──────────────────────────────────────────────────────────────────────────────────────────────────

• _libgcc_mutex 0.1 conda_forge conda-forge Cached
• libstdcxx-ng 13.2.0 h7e041cc_5 conda-forge Cached
• ld_impl_linux-64 2.40 h41732ed_0 conda-forge Cached
• libgfortran4 7.5.0 h14aa051_20 conda-forge Cached
• ca-certificates 2024.2.2 hbcca054_0 conda-forge Cached
• libgomp 13.2.0 h807b86a_5 conda-forge Cached
• libgfortran-ng 7.5.0 h14aa051_20 conda-forge Cached
• _openmp_mutex 4.5 2_gnu conda-forge Cached
• libgcc-ng 13.2.0 h807b86a_5 conda-forge Cached
• libgpuarray 0.7.6 h7f98852_1003 conda-forge Cached
• libev 4.33 hd590300_2 conda-forge Cached
• libsanitizer 13.2.0 h7e041cc_5 conda-forge Cached
• yaml 0.2.5 h7f98852_2 conda-forge Cached
• libblas 3.9.0 1_h6e990d7_netlib conda-forge Cached
• bzip2 1.0.8 hd590300_5 conda-forge Cached
• openblas 0.3.3 h9ac9557_1001 conda-forge Cached
• xz 5.2.6 h166bdaf_0 conda-forge Cached
• openssl 1.1.1w hd590300_0 conda-forge Cached
• ncurses 6.4 h59595ed_2 conda-forge Cached
• libzlib 1.2.13 hd590300_5 conda-forge Cached
• libnsl 2.0.1 hd590300_0 conda-forge Cached
• libffi 3.4.2 h7f98852_5 conda-forge Cached
• libgcc 7.2.0 h69d50b8_2 conda-forge Cached
• liblapack 3.9.0 3_h893e4fe_netlib conda-forge Cached
• libcblas 3.9.0 3_h893e4fe_netlib conda-forge Cached
• blas 1.1 openblas conda-forge Cached
• libedit 3.1.20191231 he28a2e2_2 conda-forge Cached
• readline 8.2 h8228510_1 conda-forge Cached
• libssh2 1.10.0 haa6b8db_3 conda-forge Cached
• tk 8.6.13 noxft_h4845f30_101 conda-forge Cached
• libsqlite 3.45.1 h2797004_0 conda-forge Cached
• zlib 1.2.13 hd590300_5 conda-forge Cached
• krb5 1.17.2 h926e7f8_0 conda-forge Cached
• sqlite 3.45.1 h2c6b66d_0 conda-forge Cached
• libprotobuf 3.18.0 h780b84a_1 conda-forge Cached
• python 3.6.15 hb7a2778_0_cpython conda-forge Cached
• python_abi 3.6 2_cp36m conda-forge Cached
• setuptools 58.0.4 py36h5fab9bb_2 conda-forge Cached
• libstdcxx-devel_linux-64 13.2.0 ha9c7c90_105 conda-forge Cached
• libgcc-devel_linux-64 13.2.0 ha9c7c90_105 conda-forge Cached
• kernel-headers_linux-64 2.6.32 he073ed8_17 conda-forge Cached
• wheel 0.37.1 pyhd8ed1ab_0 conda-forge Cached
• sysroot_linux-64 2.12 he073ed8_17 conda-forge Cached
• pip 21.3.1 pyhd8ed1ab_0 conda-forge Cached
• zipp 3.6.0 pyhd8ed1ab_0 conda-forge Cached
• typing_extensions 4.1.1 pyha770c72_0 conda-forge Cached
• dataclasses 0.8 pyh787bdff_2 conda-forge Cached
• tabulate 0.8.10 pyhd8ed1ab_0 conda-forge Cached
• natsort 8.2.0 pyhd8ed1ab_0 conda-forge Cached
• pytz 2023.3.post1 pyhd8ed1ab_0 conda-forge Cached
• threadpoolctl 3.1.0 pyh8a188c0_0 conda-forge Cached
• joblib 1.2.0 pyhd8ed1ab_0 conda-forge Cached
• six 1.16.0 pyh6c4a22f_0 conda-forge Cached
• mock 5.1.0 pyhd8ed1ab_0 conda-forge Cached
• werkzeug 2.0.2 pyhd8ed1ab_0 conda-forge Cached
• python-dateutil 2.8.2 pyhd8ed1ab_0 conda-forge Cached
• c-ares 1.11.0 h470a237_1 bioconda Cached
• libdeflate 1.0 h14c3975_1 bioconda Cached
• binutils_impl_linux-64 2.40 hf600244_0 conda-forge Cached
• markupsafe 2.0.1 py36h8f6f2f9_0 conda-forge Cached
• humanfriendly 10.0 py36h5fab9bb_0 conda-forge Cached
• pyyaml 5.4.1 py36h8f6f2f9_1 conda-forge Cached
• cython 0.29.13 py36he1b5a44_0 conda-forge Cached
• numpy 1.16.1 py36_blas_openblash1522bff_0 conda-forge Cached
• importlib-metadata 4.8.1 py36h5fab9bb_0 conda-forge Cached
• protobuf 3.18.0 py36hc4f0c31_0 conda-forge Cached
• libnghttp2 1.41.0 hab1572f_1 conda-forge Cached
• gcc_impl_linux-64 13.2.0 h338b0a0_5 conda-forge Cached
• binutils_linux-64 2.40 hbdbef99_2 conda-forge Cached
• coloredlogs 15.0.1 py36h5fab9bb_1 conda-forge Cached
• scipy 1.5.1 py36h2d22cac_0 conda-forge Cached
• pandas 0.24.2 py36hb3f55d8_1 conda-forge Cached
• click 8.0.1 py36h5fab9bb_0 conda-forge Cached
• tensorflow 1.1.0 py36_0 conda-forge Cached
• libcurl 7.71.1 hcdd3856_8 conda-forge Cached
• gxx_impl_linux-64 13.2.0 h338b0a0_5 conda-forge Cached
• gcc_linux-64 13.2.0 h112eaf3_2 conda-forge Cached
• scikit-learn 0.23.1 py36h0e1014b_0 conda-forge Cached
• curl 7.71.1 he644dc0_8 conda-forge Cached
• hdf5 1.10.6 nompi_h7c3c948_1111 conda-forge Cached
• gxx_linux-64 13.2.0 hc53e3bf_2 conda-forge Cached
• h5py 2.10.0 nompi_py36hecadee3_104 conda-forge Cached
• sorted_nearest 0.0.37 py36h91eb985_1 bioconda Cached
• ncls 0.0.68 py36h91eb985_0 bioconda Cached
• pyrle 0.0.38 py36h91eb985_0 bioconda Cached
• cyvcf2 0.8.4 py36h355e19c_4 bioconda Cached
• htslib 1.9 ha228f0b_7 bioconda Cached
• pysam 0.15.3 py36hda2845c_1 bioconda Cached
• pyranges 0.0.51 py36h516909a_1 bioconda Cached
• mako 1.3.2 pyhd8ed1ab_0 conda-forge Cached
• keras-preprocessing 1.1.2 pyhd8ed1ab_0 conda-forge Cached
• keras-applications 1.0.8 py_1 conda-forge Cached
• pygpu 0.7.6 py36h785e9b2_1001 conda-forge Cached
• theano 1.0.4 py36hf484d3e_1000 conda-forge Cached
• keras 2.2.4 py36_1 conda-forge Cached

Summary:

Install: 95 packages

Total download: 0 B

──────────────────────────────────────────────────────────────────────────────────────────────────

Confirm changes: [Y/n] y

Transaction starting
Linking _libgcc_mutex-0.1-conda_forge
Linking libstdcxx-ng-13.2.0-h7e041cc_5
Linking ld_impl_linux-64-2.40-h41732ed_0
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warning libmamba [openblas-0.3.3-h9ac9557_1001] The following files were already present in the environment:
- lib/libblas.so
- lib/pkgconfig/blas.pc
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- lib/pkgconfig/lapack.pc
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Transaction finished

To activate this environment, use:

micromamba activate mmsplice

Or to execute a single command in this environment, use:

micromamba run -n mmsplice mycommand

Installing pip packages: kipoiseq==0.2.5, git+https://github.com/Aerval/SpliceAI.git, mmsplice==1.0.1
Collecting git+https://github.com/Aerval/SpliceAI.git (from -r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 2))
Cloning https://github.com/Aerval/SpliceAI.git to /tmp/pip-req-build-q8taw397
Running command git clone --filter=blob:none -q https://github.com/Aerval/SpliceAI.git /tmp/pip-req-build-q8taw397
Resolved https://github.com/Aerval/SpliceAI.git to commit 9d4e285f1e42d0730095959039e2fdd8c6b371da
Preparing metadata (setup.py) ... done
Collecting kipoiseq==0.2.5
Using cached kipoiseq-0.2.5-py3-none-any.whl (20 kB)
Collecting mmsplice==1.0.1
Using cached mmsplice-1.0.1-py2.py3-none-any.whl (26.7 MB)
Collecting pyfaidx
Using cached pyfaidx-0.7.1-py3-none-any.whl
Requirement already satisfied: numpy in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from kipoiseq==0.2.5->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 1)) (1.16.1)
Collecting tqdm
Using cached tqdm-4.64.1-py2.py3-none-any.whl (78 kB)
Collecting kipoi>=0.5.5
Using cached kipoi-0.8.6-py3-none-any.whl (102 kB)
Collecting pybedtools
Using cached pybedtools-0.9.1.tar.gz (12.5 MB)
Preparing metadata (setup.py) ... done
Requirement already satisfied: pandas in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from kipoiseq==0.2.5->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 1)) (0.24.2)
Collecting kipoi-conda>=0.1.0
Using cached kipoi_conda-0.3.1-py3-none-any.whl (8.7 kB)
Collecting kipoi-utils>=0.1.1
Using cached kipoi_utils-0.7.7-py3-none-any.whl (30 kB)
Collecting gffutils
Using cached gffutils-0.12-py3-none-any.whl (1.6 MB)
Requirement already satisfied: click in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (8.0.1)
Requirement already satisfied: setuptools in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (58.0.4)
Requirement already satisfied: keras in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (2.2.4)
Collecting scikit-learn==0.19.2
Using cached scikit_learn-0.19.2-cp36-cp36m-manylinux1_x86_64.whl (4.9 MB)
Requirement already satisfied: pyranges in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.0.51)
Collecting concise
Using cached concise-0.6.9-py2.py3-none-any.whl (1.3 MB)
Requirement already satisfied: tensorflow<=1.13.1 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (1.1.0)
Requirement already satisfied: pysam>=0.10.0 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from spliceai==1.3->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 2)) (0.15.3)
Requirement already satisfied: h5py in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (2.10.0)
Requirement already satisfied: keras-preprocessing>=1.0.5 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (1.1.2)
Requirement already satisfied: keras-applications>=1.0.6 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (1.0.8)
Requirement already satisfied: six>=1.9.0 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (1.16.0)
Requirement already satisfied: pyyaml in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (5.4.1)
Requirement already satisfied: scipy>=0.14 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from keras->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (1.5.1)
Collecting urllib3>=1.21.1
Using cached urllib3-1.26.18-py2.py3-none-any.whl (143 kB)
Collecting attrs<=21.4.0
Using cached attrs-21.4.0-py2.py3-none-any.whl (60 kB)
Collecting cookiecutter>=1.6.0
Using cached cookiecutter-1.7.3-py2.py3-none-any.whl (34 kB)
Collecting related>=0.6.0
Using cached related-0.7.3-py2.py3-none-any.whl (16 kB)
Collecting tinydb
Using cached tinydb-4.7.0-py3-none-any.whl (24 kB)
Collecting deprecation>=2.0.6
Using cached deprecation-2.1.0-py2.py3-none-any.whl (11 kB)
Collecting colorlog
Using cached colorlog-6.8.2-py3-none-any.whl (11 kB)
Collecting jinja2
Using cached Jinja2-3.0.3-py3-none-any.whl (133 kB)
Requirement already satisfied: python-dateutil>=2.5.0 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pandas->kipoiseq==0.2.5->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 1)) (2.8.2)
Requirement already satisfied: pytz>=2011k in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pandas->kipoiseq==0.2.5->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 1)) (2023.3.post1)
Requirement already satisfied: werkzeug>=0.11.10 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from tensorflow<=1.13.1->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (2.0.2)
Requirement already satisfied: wheel>=0.26 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from tensorflow<=1.13.1->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.37.1)
Requirement already satisfied: protobuf>=3.2.0 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from tensorflow<=1.13.1->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (3.18.0)
Requirement already satisfied: importlib-metadata in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from click->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (4.8.1)
Collecting descartes
Using cached descartes-1.1.0-py3-none-any.whl (5.8 kB)
Collecting gtfparse>=1.0.7
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Collecting shapely
Using cached Shapely-1.8.5.post1-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.0 MB)
Collecting matplotlib
Using cached matplotlib-3.3.4-cp36-cp36m-manylinux1_x86_64.whl (11.5 MB)
Collecting argcomplete>=1.9.4
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Collecting simplejson
Using cached simplejson-3.19.2-cp36-cp36m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl (125 kB)
Collecting argh>=0.26.2
Using cached argh-0.27.2-py2.py3-none-any.whl (43 kB)
Requirement already satisfied: cython in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pyranges->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.29.13)
Collecting ncls
Using cached ncls-0.0.68.tar.gz (483 kB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-5dx1sagk/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2'
cwd: None
Complete output (2 lines):
ERROR: Could not find a version that satisfies the requirement setuptools>=61.0.0 (from versions: 0.6b1, 0.6b2, 0.6b3, 0.6b4, 0.6rc1, 0.6rc2, 0.6rc3, 0.6rc4, 0.6rc5, 0.6rc6, 0.6rc7, 0.6rc8, 0.6rc9, 0.6rc10, 0.6rc11, 0.7.2, 0.7.3, 0.7.4, 0.7.5, 0.7.6, 0.7.7, 0.7.8, 0.8, 0.9, 0.9.1, 0.9.2, 0.9.3, 0.9.4, 0.9.5, 0.9.6, 0.9.7, 0.9.8, 1.0, 1.1, 1.1.1, 1.1.2, 1.1.3, 1.1.4, 1.1.5, 1.1.6, 1.1.7, 1.2, 1.3, 1.3.1, 1.3.2, 1.4, 1.4.1, 1.4.2, 2.0, 2.0.1, 2.0.2, 2.1, 2.1.1, 2.1.2, 2.2, 3.0, 3.0.1, 3.0.2, 3.1, 3.2, 3.3, 3.4, 3.4.1, 3.4.2, 3.4.3, 3.4.4, 3.5, 3.5.1, 3.5.2, 3.6, 3.7, 3.7.1, 3.8, 3.8.1, 4.0, 4.0.1, 5.0, 5.0.1, 5.0.2, 5.1, 5.2, 5.3, 5.4, 5.4.1, 5.4.2, 5.5, 5.5.1, 5.6, 5.7, 5.8, 6.0.1, 6.0.2, 6.1, 7.0, 8.0, 8.0.1, 8.0.2, 8.0.3, 8.0.4, 8.1, 8.2, 8.2.1, 8.3, 9.0, 9.0.1, 9.1, 10.0, 10.0.1, 10.1, 10.2, 10.2.1, 11.0, 11.1, 11.2, 11.3, 11.3.1, 12.0, 12.0.1, 12.0.2, 12.0.3, 12.0.4, 12.0.5, 12.1, 12.2, 12.3, 12.4, 13.0.1, 13.0.2, 14.0, 14.1, 14.1.1, 14.2, 14.3, 14.3.1, 15.0, 15.1, 15.2, 16.0, 17.0, 17.1, 17.1.1, 18.0, 18.0.1, 18.1, 18.2, 18.3, 18.3.1, 18.3.2, 18.4, 18.5, 18.6, 18.6.1, 18.7, 18.7.1, 18.8, 18.8.1, 19.0, 19.1, 19.1.1, 19.2, 19.3, 19.4, 19.4.1, 19.5, 19.6, 19.6.1, 19.6.2, 19.7, 20.0, 20.1, 20.1.1, 20.2.2, 20.3, 20.3.1, 20.4, 20.6.6, 20.6.7, 20.6.8, 20.7.0, 20.8.0, 20.8.1, 20.9.0, 20.10.1, 21.0.0, 21.1.0, 21.2.0, 21.2.1, 21.2.2, 22.0.0, 22.0.1, 22.0.2, 22.0.4, 22.0.5, 23.0.0, 23.1.0, 23.2.0, 23.2.1, 24.0.0, 24.0.1, 24.0.2, 24.0.3, 24.1.0, 24.1.1, 24.2.0, 24.2.1, 24.3.0, 24.3.1, 25.0.0, 25.0.1, 25.0.2, 25.1.0, 25.1.1, 25.1.2, 25.1.3, 25.1.4, 25.1.5, 25.1.6, 25.2.0, 25.3.0, 25.4.0, 26.0.0, 26.1.0, 26.1.1, 27.0.0, 27.1.0, 27.1.2, 27.2.0, 27.3.0, 27.3.1, 28.0.0, 28.1.0, 28.2.0, 28.3.0, 28.4.0, 28.5.0, 28.6.0, 28.6.1, 28.7.0, 28.7.1, 28.8.0, 28.8.1, 29.0.0, 29.0.1, 30.0.0, 30.1.0, 30.2.0, 30.2.1, 30.3.0, 30.4.0, 31.0.0, 31.0.1, 32.0.0, 32.1.0, 32.1.1, 32.1.2, 32.1.3, 32.2.0, 32.3.0, 32.3.1, 33.1.0, 33.1.1, 34.0.0, 34.0.1, 34.0.2, 34.0.3, 34.1.0, 34.1.1, 34.2.0, 34.3.0, 34.3.1, 34.3.2, 34.3.3, 34.4.0, 34.4.1, 35.0.0, 35.0.1, 35.0.2, 36.0.1, 36.1.0, 36.1.1, 36.2.0, 36.2.1, 36.2.2, 36.2.3, 36.2.4, 36.2.5, 36.2.6, 36.2.7, 36.3.0, 36.4.0, 36.5.0, 36.6.0, 36.6.1, 36.7.0, 36.7.1, 36.7.2, 36.8.0, 37.0.0, 38.0.0, 38.1.0, 38.2.0, 38.2.1, 38.2.3, 38.2.4, 38.2.5, 38.3.0, 38.4.0, 38.4.1, 38.5.0, 38.5.1, 38.5.2, 38.6.0, 38.6.1, 38.7.0, 39.0.0, 39.0.1, 39.1.0, 39.2.0, 40.0.0, 40.1.0, 40.1.1, 40.2.0, 40.3.0, 40.4.0, 40.4.1, 40.4.2, 40.4.3, 40.5.0, 40.6.0, 40.6.1, 40.6.2, 40.6.3, 40.7.0, 40.7.1, 40.7.2, 40.7.3, 40.8.0, 40.9.0, 41.0.0, 41.0.1, 41.1.0, 41.2.0, 41.3.0, 41.4.0, 41.5.0, 41.5.1, 41.6.0, 42.0.0, 42.0.1, 42.0.2, 43.0.0, 44.0.0, 44.1.0, 44.1.1, 45.0.0, 45.1.0, 45.2.0, 45.3.0, 46.0.0, 46.1.0, 46.1.1, 46.1.2, 46.1.3, 46.2.0, 46.3.0, 46.3.1, 46.4.0, 47.0.0, 47.1.0, 47.1.1, 47.2.0, 47.3.0, 47.3.1, 47.3.2, 48.0.0, 49.0.0, 49.0.1, 49.1.0, 49.1.1, 49.1.2, 49.1.3, 49.2.0, 49.2.1, 49.3.0, 49.3.1, 49.3.2, 49.4.0, 49.5.0, 49.6.0, 50.0.0, 50.0.1, 50.0.2, 50.0.3, 50.1.0, 50.2.0, 50.3.0, 50.3.1, 50.3.2, 51.0.0, 51.1.0, 51.1.0.post20201221, 51.1.1, 51.1.2, 51.2.0, 51.3.0, 51.3.1, 51.3.2, 51.3.3, 52.0.0, 53.0.0, 53.1.0, 54.0.0, 54.1.0, 54.1.1, 54.1.2, 54.1.3, 54.2.0, 56.0.0, 56.1.0, 56.2.0, 57.0.0, 57.1.0, 57.2.0, 57.3.0, 57.4.0, 57.5.0, 58.0.0, 58.0.1, 58.0.2, 58.0.3, 58.0.4, 58.1.0, 58.2.0, 58.3.0, 58.4.0, 58.5.0, 58.5.1, 58.5.2, 58.5.3, 59.0.1, 59.1.0, 59.1.1, 59.2.0, 59.3.0, 59.4.0, 59.5.0, 59.6.0)
ERROR: No matching distribution found for setuptools>=61.0.0

WARNING: Discarding https://files.pythonhosted.org/packages/88/b8/210d5cb1fa85c7675323aacbd52af11553dc190aad1c15584699f40797f1/ncls-0.0.68.tar.gz#sha256=81aaa5abb123bb21797ed2f8ef921e20222db14a3ecbc61ccf447532f2b7ba93 (from https://pypi.org/simple/ncls/). Command errored out with exit status 1: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-5dx1sagk/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2' Check the logs for full command output.
Using cached ncls-0.0.67.tar.gz (538 kB)
Preparing metadata (setup.py) ... done
Requirement already satisfied: tabulate in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pyranges->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.8.10)
Requirement already satisfied: sorted_nearest in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pyranges->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.0.37)
Collecting pyrle
Using cached pyrle-0.0.39.tar.gz (461 kB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-a879l2vx/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2'
cwd: None
Complete output (2 lines):
ERROR: Could not find a version that satisfies the requirement setuptools>=61.0.0 (from versions: 0.6b1, 0.6b2, 0.6b3, 0.6b4, 0.6rc1, 0.6rc2, 0.6rc3, 0.6rc4, 0.6rc5, 0.6rc6, 0.6rc7, 0.6rc8, 0.6rc9, 0.6rc10, 0.6rc11, 0.7.2, 0.7.3, 0.7.4, 0.7.5, 0.7.6, 0.7.7, 0.7.8, 0.8, 0.9, 0.9.1, 0.9.2, 0.9.3, 0.9.4, 0.9.5, 0.9.6, 0.9.7, 0.9.8, 1.0, 1.1, 1.1.1, 1.1.2, 1.1.3, 1.1.4, 1.1.5, 1.1.6, 1.1.7, 1.2, 1.3, 1.3.1, 1.3.2, 1.4, 1.4.1, 1.4.2, 2.0, 2.0.1, 2.0.2, 2.1, 2.1.1, 2.1.2, 2.2, 3.0, 3.0.1, 3.0.2, 3.1, 3.2, 3.3, 3.4, 3.4.1, 3.4.2, 3.4.3, 3.4.4, 3.5, 3.5.1, 3.5.2, 3.6, 3.7, 3.7.1, 3.8, 3.8.1, 4.0, 4.0.1, 5.0, 5.0.1, 5.0.2, 5.1, 5.2, 5.3, 5.4, 5.4.1, 5.4.2, 5.5, 5.5.1, 5.6, 5.7, 5.8, 6.0.1, 6.0.2, 6.1, 7.0, 8.0, 8.0.1, 8.0.2, 8.0.3, 8.0.4, 8.1, 8.2, 8.2.1, 8.3, 9.0, 9.0.1, 9.1, 10.0, 10.0.1, 10.1, 10.2, 10.2.1, 11.0, 11.1, 11.2, 11.3, 11.3.1, 12.0, 12.0.1, 12.0.2, 12.0.3, 12.0.4, 12.0.5, 12.1, 12.2, 12.3, 12.4, 13.0.1, 13.0.2, 14.0, 14.1, 14.1.1, 14.2, 14.3, 14.3.1, 15.0, 15.1, 15.2, 16.0, 17.0, 17.1, 17.1.1, 18.0, 18.0.1, 18.1, 18.2, 18.3, 18.3.1, 18.3.2, 18.4, 18.5, 18.6, 18.6.1, 18.7, 18.7.1, 18.8, 18.8.1, 19.0, 19.1, 19.1.1, 19.2, 19.3, 19.4, 19.4.1, 19.5, 19.6, 19.6.1, 19.6.2, 19.7, 20.0, 20.1, 20.1.1, 20.2.2, 20.3, 20.3.1, 20.4, 20.6.6, 20.6.7, 20.6.8, 20.7.0, 20.8.0, 20.8.1, 20.9.0, 20.10.1, 21.0.0, 21.1.0, 21.2.0, 21.2.1, 21.2.2, 22.0.0, 22.0.1, 22.0.2, 22.0.4, 22.0.5, 23.0.0, 23.1.0, 23.2.0, 23.2.1, 24.0.0, 24.0.1, 24.0.2, 24.0.3, 24.1.0, 24.1.1, 24.2.0, 24.2.1, 24.3.0, 24.3.1, 25.0.0, 25.0.1, 25.0.2, 25.1.0, 25.1.1, 25.1.2, 25.1.3, 25.1.4, 25.1.5, 25.1.6, 25.2.0, 25.3.0, 25.4.0, 26.0.0, 26.1.0, 26.1.1, 27.0.0, 27.1.0, 27.1.2, 27.2.0, 27.3.0, 27.3.1, 28.0.0, 28.1.0, 28.2.0, 28.3.0, 28.4.0, 28.5.0, 28.6.0, 28.6.1, 28.7.0, 28.7.1, 28.8.0, 28.8.1, 29.0.0, 29.0.1, 30.0.0, 30.1.0, 30.2.0, 30.2.1, 30.3.0, 30.4.0, 31.0.0, 31.0.1, 32.0.0, 32.1.0, 32.1.1, 32.1.2, 32.1.3, 32.2.0, 32.3.0, 32.3.1, 33.1.0, 33.1.1, 34.0.0, 34.0.1, 34.0.2, 34.0.3, 34.1.0, 34.1.1, 34.2.0, 34.3.0, 34.3.1, 34.3.2, 34.3.3, 34.4.0, 34.4.1, 35.0.0, 35.0.1, 35.0.2, 36.0.1, 36.1.0, 36.1.1, 36.2.0, 36.2.1, 36.2.2, 36.2.3, 36.2.4, 36.2.5, 36.2.6, 36.2.7, 36.3.0, 36.4.0, 36.5.0, 36.6.0, 36.6.1, 36.7.0, 36.7.1, 36.7.2, 36.8.0, 37.0.0, 38.0.0, 38.1.0, 38.2.0, 38.2.1, 38.2.3, 38.2.4, 38.2.5, 38.3.0, 38.4.0, 38.4.1, 38.5.0, 38.5.1, 38.5.2, 38.6.0, 38.6.1, 38.7.0, 39.0.0, 39.0.1, 39.1.0, 39.2.0, 40.0.0, 40.1.0, 40.1.1, 40.2.0, 40.3.0, 40.4.0, 40.4.1, 40.4.2, 40.4.3, 40.5.0, 40.6.0, 40.6.1, 40.6.2, 40.6.3, 40.7.0, 40.7.1, 40.7.2, 40.7.3, 40.8.0, 40.9.0, 41.0.0, 41.0.1, 41.1.0, 41.2.0, 41.3.0, 41.4.0, 41.5.0, 41.5.1, 41.6.0, 42.0.0, 42.0.1, 42.0.2, 43.0.0, 44.0.0, 44.1.0, 44.1.1, 45.0.0, 45.1.0, 45.2.0, 45.3.0, 46.0.0, 46.1.0, 46.1.1, 46.1.2, 46.1.3, 46.2.0, 46.3.0, 46.3.1, 46.4.0, 47.0.0, 47.1.0, 47.1.1, 47.2.0, 47.3.0, 47.3.1, 47.3.2, 48.0.0, 49.0.0, 49.0.1, 49.1.0, 49.1.1, 49.1.2, 49.1.3, 49.2.0, 49.2.1, 49.3.0, 49.3.1, 49.3.2, 49.4.0, 49.5.0, 49.6.0, 50.0.0, 50.0.1, 50.0.2, 50.0.3, 50.1.0, 50.2.0, 50.3.0, 50.3.1, 50.3.2, 51.0.0, 51.1.0, 51.1.0.post20201221, 51.1.1, 51.1.2, 51.2.0, 51.3.0, 51.3.1, 51.3.2, 51.3.3, 52.0.0, 53.0.0, 53.1.0, 54.0.0, 54.1.0, 54.1.1, 54.1.2, 54.1.3, 54.2.0, 56.0.0, 56.1.0, 56.2.0, 57.0.0, 57.1.0, 57.2.0, 57.3.0, 57.4.0, 57.5.0, 58.0.0, 58.0.1, 58.0.2, 58.0.3, 58.0.4, 58.1.0, 58.2.0, 58.3.0, 58.4.0, 58.5.0, 58.5.1, 58.5.2, 58.5.3, 59.0.1, 59.1.0, 59.1.1, 59.2.0, 59.3.0, 59.4.0, 59.5.0, 59.6.0)
ERROR: No matching distribution found for setuptools>=61.0.0

WARNING: Discarding https://files.pythonhosted.org/packages/1d/53/0fc3eb65e7f940422dc0f54910e36d5b88d6c0ac9ed391dfbc98567e4050/pyrle-0.0.39.tar.gz#sha256=1be4be7814d3941db907aaf19f311bd46a407244316cadbf4b73109685c055c5 (from https://pypi.org/simple/pyrle/). Command errored out with exit status 1: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-a879l2vx/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2' Check the logs for full command output.
Using cached pyrle-0.0.38.tar.gz (363 kB)
Installing build dependencies ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-c8_wn_rf/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2'
cwd: None
Complete output (2 lines):
ERROR: Could not find a version that satisfies the requirement setuptools>=61.0.0 (from versions: 0.6b1, 0.6b2, 0.6b3, 0.6b4, 0.6rc1, 0.6rc2, 0.6rc3, 0.6rc4, 0.6rc5, 0.6rc6, 0.6rc7, 0.6rc8, 0.6rc9, 0.6rc10, 0.6rc11, 0.7.2, 0.7.3, 0.7.4, 0.7.5, 0.7.6, 0.7.7, 0.7.8, 0.8, 0.9, 0.9.1, 0.9.2, 0.9.3, 0.9.4, 0.9.5, 0.9.6, 0.9.7, 0.9.8, 1.0, 1.1, 1.1.1, 1.1.2, 1.1.3, 1.1.4, 1.1.5, 1.1.6, 1.1.7, 1.2, 1.3, 1.3.1, 1.3.2, 1.4, 1.4.1, 1.4.2, 2.0, 2.0.1, 2.0.2, 2.1, 2.1.1, 2.1.2, 2.2, 3.0, 3.0.1, 3.0.2, 3.1, 3.2, 3.3, 3.4, 3.4.1, 3.4.2, 3.4.3, 3.4.4, 3.5, 3.5.1, 3.5.2, 3.6, 3.7, 3.7.1, 3.8, 3.8.1, 4.0, 4.0.1, 5.0, 5.0.1, 5.0.2, 5.1, 5.2, 5.3, 5.4, 5.4.1, 5.4.2, 5.5, 5.5.1, 5.6, 5.7, 5.8, 6.0.1, 6.0.2, 6.1, 7.0, 8.0, 8.0.1, 8.0.2, 8.0.3, 8.0.4, 8.1, 8.2, 8.2.1, 8.3, 9.0, 9.0.1, 9.1, 10.0, 10.0.1, 10.1, 10.2, 10.2.1, 11.0, 11.1, 11.2, 11.3, 11.3.1, 12.0, 12.0.1, 12.0.2, 12.0.3, 12.0.4, 12.0.5, 12.1, 12.2, 12.3, 12.4, 13.0.1, 13.0.2, 14.0, 14.1, 14.1.1, 14.2, 14.3, 14.3.1, 15.0, 15.1, 15.2, 16.0, 17.0, 17.1, 17.1.1, 18.0, 18.0.1, 18.1, 18.2, 18.3, 18.3.1, 18.3.2, 18.4, 18.5, 18.6, 18.6.1, 18.7, 18.7.1, 18.8, 18.8.1, 19.0, 19.1, 19.1.1, 19.2, 19.3, 19.4, 19.4.1, 19.5, 19.6, 19.6.1, 19.6.2, 19.7, 20.0, 20.1, 20.1.1, 20.2.2, 20.3, 20.3.1, 20.4, 20.6.6, 20.6.7, 20.6.8, 20.7.0, 20.8.0, 20.8.1, 20.9.0, 20.10.1, 21.0.0, 21.1.0, 21.2.0, 21.2.1, 21.2.2, 22.0.0, 22.0.1, 22.0.2, 22.0.4, 22.0.5, 23.0.0, 23.1.0, 23.2.0, 23.2.1, 24.0.0, 24.0.1, 24.0.2, 24.0.3, 24.1.0, 24.1.1, 24.2.0, 24.2.1, 24.3.0, 24.3.1, 25.0.0, 25.0.1, 25.0.2, 25.1.0, 25.1.1, 25.1.2, 25.1.3, 25.1.4, 25.1.5, 25.1.6, 25.2.0, 25.3.0, 25.4.0, 26.0.0, 26.1.0, 26.1.1, 27.0.0, 27.1.0, 27.1.2, 27.2.0, 27.3.0, 27.3.1, 28.0.0, 28.1.0, 28.2.0, 28.3.0, 28.4.0, 28.5.0, 28.6.0, 28.6.1, 28.7.0, 28.7.1, 28.8.0, 28.8.1, 29.0.0, 29.0.1, 30.0.0, 30.1.0, 30.2.0, 30.2.1, 30.3.0, 30.4.0, 31.0.0, 31.0.1, 32.0.0, 32.1.0, 32.1.1, 32.1.2, 32.1.3, 32.2.0, 32.3.0, 32.3.1, 33.1.0, 33.1.1, 34.0.0, 34.0.1, 34.0.2, 34.0.3, 34.1.0, 34.1.1, 34.2.0, 34.3.0, 34.3.1, 34.3.2, 34.3.3, 34.4.0, 34.4.1, 35.0.0, 35.0.1, 35.0.2, 36.0.1, 36.1.0, 36.1.1, 36.2.0, 36.2.1, 36.2.2, 36.2.3, 36.2.4, 36.2.5, 36.2.6, 36.2.7, 36.3.0, 36.4.0, 36.5.0, 36.6.0, 36.6.1, 36.7.0, 36.7.1, 36.7.2, 36.8.0, 37.0.0, 38.0.0, 38.1.0, 38.2.0, 38.2.1, 38.2.3, 38.2.4, 38.2.5, 38.3.0, 38.4.0, 38.4.1, 38.5.0, 38.5.1, 38.5.2, 38.6.0, 38.6.1, 38.7.0, 39.0.0, 39.0.1, 39.1.0, 39.2.0, 40.0.0, 40.1.0, 40.1.1, 40.2.0, 40.3.0, 40.4.0, 40.4.1, 40.4.2, 40.4.3, 40.5.0, 40.6.0, 40.6.1, 40.6.2, 40.6.3, 40.7.0, 40.7.1, 40.7.2, 40.7.3, 40.8.0, 40.9.0, 41.0.0, 41.0.1, 41.1.0, 41.2.0, 41.3.0, 41.4.0, 41.5.0, 41.5.1, 41.6.0, 42.0.0, 42.0.1, 42.0.2, 43.0.0, 44.0.0, 44.1.0, 44.1.1, 45.0.0, 45.1.0, 45.2.0, 45.3.0, 46.0.0, 46.1.0, 46.1.1, 46.1.2, 46.1.3, 46.2.0, 46.3.0, 46.3.1, 46.4.0, 47.0.0, 47.1.0, 47.1.1, 47.2.0, 47.3.0, 47.3.1, 47.3.2, 48.0.0, 49.0.0, 49.0.1, 49.1.0, 49.1.1, 49.1.2, 49.1.3, 49.2.0, 49.2.1, 49.3.0, 49.3.1, 49.3.2, 49.4.0, 49.5.0, 49.6.0, 50.0.0, 50.0.1, 50.0.2, 50.0.3, 50.1.0, 50.2.0, 50.3.0, 50.3.1, 50.3.2, 51.0.0, 51.1.0, 51.1.0.post20201221, 51.1.1, 51.1.2, 51.2.0, 51.3.0, 51.3.1, 51.3.2, 51.3.3, 52.0.0, 53.0.0, 53.1.0, 54.0.0, 54.1.0, 54.1.1, 54.1.2, 54.1.3, 54.2.0, 56.0.0, 56.1.0, 56.2.0, 57.0.0, 57.1.0, 57.2.0, 57.3.0, 57.4.0, 57.5.0, 58.0.0, 58.0.1, 58.0.2, 58.0.3, 58.0.4, 58.1.0, 58.2.0, 58.3.0, 58.4.0, 58.5.0, 58.5.1, 58.5.2, 58.5.3, 59.0.1, 59.1.0, 59.1.1, 59.2.0, 59.3.0, 59.4.0, 59.5.0, 59.6.0)
ERROR: No matching distribution found for setuptools>=61.0.0

WARNING: Discarding https://files.pythonhosted.org/packages/9e/76/52c6604084cf37240ff1450272ee97a8969b7b943833bff923ed9e45400d/pyrle-0.0.38.tar.gz#sha256=8b382947a18c73eb4aeaa9e731cb89d0b755f85f75ccb49fc7e121ae3fb984be (from https://pypi.org/simple/pyrle/). Command errored out with exit status 1: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip install --ignore-installed --no-user --prefix /tmp/pip-build-env-c8_wn_rf/overlay --no-warn-script-location --no-binary :none: --only-binary :none: -i https://pypi.org/simple -- 'setuptools>=61.0.0' wheel cython 'setuptools_scm[toml]>=6.2' Check the logs for full command output.
Using cached pyrle-0.0.37.tar.gz (426 kB)
Installing build dependencies ... done
Getting requirements to build wheel ... done
Preparing metadata (pyproject.toml) ... done
Requirement already satisfied: natsort in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from pyranges->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (8.2.0)
Collecting importlib-resources
Using cached importlib_resources-5.4.0-py3-none-any.whl (28 kB)
Collecting requests>=2.23.0
Using cached requests-2.27.1-py2.py3-none-any.whl (63 kB)
Collecting python-slugify>=4.0.0
Using cached python_slugify-6.1.2-py2.py3-none-any.whl (9.4 kB)
Collecting binaryornot>=0.4.4
Using cached binaryornot-0.4.4-py2.py3-none-any.whl (9.0 kB)
Collecting jinja2-time>=0.2.0
Using cached jinja2_time-0.2.0-py2.py3-none-any.whl (6.4 kB)
Collecting poyo>=0.5.0
Using cached poyo-0.5.0-py2.py3-none-any.whl (10 kB)
Collecting packaging
Using cached packaging-21.3-py3-none-any.whl (40 kB)
Collecting polars
Using cached polars-0.12.5-cp36-abi3-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (10.3 MB)
Requirement already satisfied: typing-extensions>=3.6.4 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from importlib-metadata->click->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (4.1.1)
Requirement already satisfied: zipp>=0.5 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from importlib-metadata->click->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (3.6.0)
Requirement already satisfied: MarkupSafe>=2.0 in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from jinja2->kipoi>=0.5.5->kipoiseq==0.2.5->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 1)) (2.0.1)
Collecting future
Using cached future-1.0.0-py3-none-any.whl (491 kB)
Requirement already satisfied: dataclasses in /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages (from werkzeug>=0.11.10->tensorflow<=1.13.1->mmsplice==1.0.1->-r /home/david/Projects/CADD-scripts-1.7/envs/mambaf5nkdUNOHn1 (line 3)) (0.8)
Collecting cycler>=0.10
Using cached cycler-0.11.0-py3-none-any.whl (6.4 kB)
Collecting pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.3
Using cached pyparsing-3.1.1-py3-none-any.whl (103 kB)
Collecting kiwisolver>=1.0.1
Using cached kiwisolver-1.3.1-cp36-cp36m-manylinux1_x86_64.whl (1.1 MB)
Collecting pillow>=6.2.0
Using cached Pillow-8.4.0-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (3.1 MB)
Collecting chardet>=3.0.2
Using cached chardet-5.0.0-py3-none-any.whl (193 kB)
Collecting arrow
Using cached arrow-1.2.3-py3-none-any.whl (66 kB)
Collecting text-unidecode>=1.3
Using cached text_unidecode-1.3-py2.py3-none-any.whl (78 kB)
Collecting charset-normalizer~=2.0.0
Using cached charset_normalizer-2.0.12-py3-none-any.whl (39 kB)
Collecting certifi>=2017.4.17
Using cached certifi-2024.2.2-py3-none-any.whl (163 kB)
Collecting idna<4,>=2.5
Using cached idna-3.6-py3-none-any.whl (61 kB)
Building wheels for collected packages: spliceai, pybedtools, ncls, pyrle
Building wheel for spliceai (setup.py) ... done
Created wheel for spliceai: filename=spliceai-1.3-py3-none-any.whl size=16700166 sha256=663ca4fa733aa026bf85aef39f6a1bbc8b5656281edd4a4e9d6b51a49a8aefae
Stored in directory: /tmp/pip-ephem-wheel-cache-vkcvl766/wheels/d0/39/70/48a462f1e42f4f0f4cc51c448d91c5ee50220f56507b4504a7
Building wheel for pybedtools (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f/setup.py'"'"'; file='"'"'/tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(file) if os.path.exists(file) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' bdist_wheel -d /tmp/pip-wheel-79cs_dd5
cwd: /tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f/
Complete output (148 lines):
/home/david/micromamba/envs/mmsplice/lib/python3.6/distutils/dist.py:261: UserWarning: Unknown distribution option: 'language_level'
warnings.warn(msg)
running bdist_wheel
The [wheel] section is deprecated. Use [bdist_wheel] instead.
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.6
creating build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/settings.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/filenames.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/paths.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/stats.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/parallel.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/version.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/bedtool.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/logger.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/genome_registry.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/helpers.py -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/init.py -> build/lib.linux-x86_64-3.6/pybedtools
creating build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_contrib.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_helpers.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_issues.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/regression_tests.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_cbedtools.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_len_leak.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_iter.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_1.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/tfuncs.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_gzip_support.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/genomepy_integration.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/test_pathlib.py -> build/lib.linux-x86_64-3.6/pybedtools/test
copying pybedtools/test/init.py -> build/lib.linux-x86_64-3.6/pybedtools/test
creating build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/long_range_interaction.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/bigbed.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/plotting.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/bigwig.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/venn_maker.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/intersection_matrix.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
copying pybedtools/contrib/init.py -> build/lib.linux-x86_64-3.6/pybedtools/contrib
creating build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/init.py -> build/lib.linux-x86_64-3.6/pybedtools/test/data
running egg_info
creating pybedtools.egg-info
writing pybedtools.egg-info/PKG-INFO
writing dependency_links to pybedtools.egg-info/dependency_links.txt
writing requirements to pybedtools.egg-info/requires.txt
writing top-level names to pybedtools.egg-info/top_level.txt
writing manifest file 'pybedtools.egg-info/SOURCES.txt'
reading manifest file 'pybedtools.egg-info/SOURCES.txt'
adding license file 'LICENSE.txt'
writing manifest file 'pybedtools.egg-info/SOURCES.txt'
copying pybedtools/cbedtools.cpp -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/featurefuncs.cpp -> build/lib.linux-x86_64-3.6/pybedtools
creating build/lib.linux-x86_64-3.6/pybedtools/include
copying pybedtools/include/bedFile.cpp -> build/lib.linux-x86_64-3.6/pybedtools/include
copying pybedtools/include/fileType.cpp -> build/lib.linux-x86_64-3.6/pybedtools/include
copying pybedtools/include/gzstream.cpp -> build/lib.linux-x86_64-3.6/pybedtools/include
copying pybedtools/test/data/test.fa -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/hg38-base.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/m1.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/rmsk.hg18.chr21.small.bed.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.1.100.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/democonfig.yaml -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.sorted.bam.bai -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/tag_test2.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/Cp190_Mbn2_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/venn.b.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/mm9.bed12 -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/v.vcf -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/test_tsses.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/BEAF_Mbn2_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/hg38-problem.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/vcf-stderr-test.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.1.100.bam.bai -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/venn.c.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/c.gff -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.gff.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/reads.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/1000genomes-example.vcf -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/issue319.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/issue319.vcf.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/Cp190_Kc_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.cram -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/issue_121.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/SuHw_Kc_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/CTCF_Mbn2_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/a.links.html -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/bedpe2.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/dm3-chr2L-5M.gff.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.sorted.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/vcf-stderr-test.vcf -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/test.fa.fai -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/small.fastq -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/expand_test.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/a.bed.gz.tbi -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/rmsk.hg18.chr21.small.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/a.bed.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/d.gff -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/small.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/BEAF_Kc_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.50.200.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/y.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/exons.gff -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.gff -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/x.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/issue319.out.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/dm3-chr2L-5M-invalid.gff.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.othersort.bam -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/example.narrowPeak -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/164.gtf -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/genome.fa -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/a.igv_script -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/hg19.gff -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/test_bedpe.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/b.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/test_peaks.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/tag_test1.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/SuHw_Mbn2_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/CTCF_Kc_Bushey_2009.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/a.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/snps.bed.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/gdc.50.200.bam.bai -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/x.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/bedpe.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/multibamcov_test.bed -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/test/data/1000genomes-example.vcf.gz -> build/lib.linux-x86_64-3.6/pybedtools/test/data
copying pybedtools/featurefuncs.pyx -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/_Window.pyx -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/cbedtools.pyx -> build/lib.linux-x86_64-3.6/pybedtools
copying pybedtools/cbedtools.pxd -> build/lib.linux-x86_64-3.6/pybedtools
running build_ext
building 'pybedtools.cbedtools' extension
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/pybedtools
creating build/temp.linux-x86_64-3.6/pybedtools/include
/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc -DNDEBUG -fwrapv -O2 -Wall -Wstrict-prototypes -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /home/david/micromamba/envs/mmsplice/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /home/david/micromamba/envs/mmsplice/include -fPIC -Ipybedtools/include/ -I/home/david/micromamba/envs/mmsplice/include/python3.6m -c pybedtools/cbedtools.cpp -o build/temp.linux-x86_64-3.6/pybedtools/cbedtools.o
cc1plus: warning: command-line option '-Wstrict-prototypes' is valid for C/ObjC but not for C++
In file included from pybedtools/cbedtools.cpp:35:
/home/david/micromamba/envs/mmsplice/include/python3.6m/Python.h:39:10: fatal error: crypt.h: No such file or directory
39 | #include <crypt.h>
| ^~~~~~~~~
compilation terminated.
error: command '/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc' failed with exit status 1

ERROR: Failed building wheel for pybedtools
Running setup.py clean for pybedtools
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f/setup.py'"'"'; file='"'"'/tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(file) if os.path.exists(file) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' clean --all
cwd: /tmp/pip-install-ozi6fd6w/pybedtools_0702261744774585a489c55457fc797f
Complete output (8 lines):
/home/david/micromamba/envs/mmsplice/lib/python3.6/distutils/dist.py:261: UserWarning: Unknown distribution option: 'language_level'
warnings.warn(msg)
usage: setup.py [global_opts] cmd1 [cmd1_opts] [cmd2 [cmd2_opts] ...]
or: setup.py --help [cmd1 cmd2 ...]
or: setup.py --help-commands
or: setup.py cmd --help

error: option --all not recognized

ERROR: Failed cleaning build dir for pybedtools
Building wheel for ncls (setup.py) ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python -u -c 'import io, os, sys, setuptools, tokenize; sys.argv[0] = '"'"'/tmp/pip-install-ozi6fd6w/ncls_5afd03a8fbf1472bb9835fba26cde143/setup.py'"'"'; file='"'"'/tmp/pip-install-ozi6fd6w/ncls_5afd03a8fbf1472bb9835fba26cde143/setup.py'"'"';f = getattr(tokenize, '"'"'open'"'"', open)(file) if os.path.exists(file) else io.StringIO('"'"'from setuptools import setup; setup()'"'"');code = f.read().replace('"'"'\r\n'"'"', '"'"'\n'"'"');f.close();exec(compile(code, file, '"'"'exec'"'"'))' bdist_wheel -d /tmp/pip-wheel-8fqst6xf
cwd: /tmp/pip-install-ozi6fd6w/ncls_5afd03a8fbf1472bb9835fba26cde143/
Complete output (40 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.6
creating build/lib.linux-x86_64-3.6/ncls
copying ncls/version.py -> build/lib.linux-x86_64-3.6/ncls
copying ncls/init.py -> build/lib.linux-x86_64-3.6/ncls
creating build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/init.py -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/ncls32.pyx -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/fncls.pyx -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/ncls.pyx -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/cfncls.pxd -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/cncls.pxd -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/cncls32.pxd -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/cgraph.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/intervaldb32.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/utarray.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/fintervaldb.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/default.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/intervaldb.h -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/ncls32.c -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/fintervaldb.c -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/intervaldb32.c -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/fncls.c -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/intervaldb.c -> build/lib.linux-x86_64-3.6/ncls/src
copying ncls/src/ncls.c -> build/lib.linux-x86_64-3.6/ncls/src
running build_ext
building 'ncls.src.ncls' extension
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/ncls
creating build/temp.linux-x86_64-3.6/ncls/src
/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc -DNDEBUG -fwrapv -O2 -Wall -Wstrict-prototypes -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /home/david/micromamba/envs/mmsplice/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /home/david/micromamba/envs/mmsplice/include -fPIC -I/tmp/pip-install-ozi6fd6w/ncls_5afd03a8fbf1472bb9835fba26cde143/ncls/src -I/tmp/pip-install-ozi6fd6w/ncls_5afd03a8fbf1472bb9835fba26cde143 -I. -I/home/david/micromamba/envs/mmsplice/include/python3.6m -c ncls/src/ncls.c -o build/temp.linux-x86_64-3.6/ncls/src/ncls.o
In file included from ncls/src/ncls.c:36:
/home/david/micromamba/envs/mmsplice/include/python3.6m/Python.h:39:10: fatal error: crypt.h: No such file or directory
39 | #include <crypt.h>
| ^~~~~~~~~
compilation terminated.
error: command '/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc' failed with exit status 1

ERROR: Failed building wheel for ncls
Running setup.py clean for ncls
Building wheel for pyrle (pyproject.toml) ... error
ERROR: Command errored out with exit status 1:
command: /home/david/micromamba/envs/mmsplice/bin/python /home/david/micromamba/envs/mmsplice/lib/python3.6/site-packages/pip/_vendor/pep517/in_process/_in_process.py build_wheel /tmp/tmps5uvnr7t
cwd: /tmp/pip-install-ozi6fd6w/pyrle_1d7c5326a1c34d23a9eee2958b361fba
Complete output (38 lines):
running bdist_wheel
running build
running build_py
creating build
creating build/lib.linux-x86_64-3.6
creating build/lib.linux-x86_64-3.6/tests
copying tests/test_subset_coverage.py -> build/lib.linux-x86_64-3.6/tests
copying tests/hypothesis_helper.py -> build/lib.linux-x86_64-3.6/tests
copying tests/helpers.py -> build/lib.linux-x86_64-3.6/tests
copying tests/test_hypothesis_coverage.py -> build/lib.linux-x86_64-3.6/tests
copying tests/init.py -> build/lib.linux-x86_64-3.6/tests
copying tests/test_hypothesis.py -> build/lib.linux-x86_64-3.6/tests
creating build/lib.linux-x86_64-3.6/pyrle
copying pyrle/rledict.py -> build/lib.linux-x86_64-3.6/pyrle
copying pyrle/version.py -> build/lib.linux-x86_64-3.6/pyrle
copying pyrle/methods.py -> build/lib.linux-x86_64-3.6/pyrle
copying pyrle/rle.py -> build/lib.linux-x86_64-3.6/pyrle
copying pyrle/init.py -> build/lib.linux-x86_64-3.6/pyrle
creating build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/init.py -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/getitem.pyx -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/rle.pyx -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/coverage.pyx -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/rle.c -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/coverage.c -> build/lib.linux-x86_64-3.6/pyrle/src
copying pyrle/src/getitem.c -> build/lib.linux-x86_64-3.6/pyrle/src
running build_ext
building 'pyrle.src.rle' extension
creating build/temp.linux-x86_64-3.6
creating build/temp.linux-x86_64-3.6/pyrle
creating build/temp.linux-x86_64-3.6/pyrle/src
/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc -DNDEBUG -fwrapv -O2 -Wall -Wstrict-prototypes -march=nocona -mtune=haswell -ftree-vectorize -fPIC -fstack-protector-strong -fno-plt -O2 -ffunction-sections -pipe -isystem /home/david/micromamba/envs/mmsplice/include -DNDEBUG -D_FORTIFY_SOURCE=2 -O2 -isystem /home/david/micromamba/envs/mmsplice/include -fPIC -I. -I/home/david/micromamba/envs/mmsplice/include/python3.6m -c pyrle/src/rle.c -o build/temp.linux-x86_64-3.6/pyrle/src/rle.o
In file included from pyrle/src/rle.c:29:
/home/david/micromamba/envs/mmsplice/include/python3.6m/Python.h:39:10: fatal error: crypt.h: No such file or directory
39 | #include <crypt.h>
| ^~~~~~~~~
compilation terminated.
error: command '/home/david/micromamba/envs/mmsplice/bin/x86_64-conda-linux-gnu-cc' failed with exit status 1

ERROR: Failed building wheel for pyrle
Successfully built spliceai
Failed to build pybedtools ncls pyrle
ERROR: Could not build wheels for pyrle, which is required to install pyproject.toml-based projects
critical libmamba pip failed to install packages

Hi,

Are there any plans to migrate this software away from Python 2.7?

A colleague has asked about using CADD and I am unsure why there are Conda environments that still use Python 2.7 and that the YAML files to create those are hard coded to Python 2.7.

As the EOL for Python 2.7 was over four years ago, it's hard to recommend CADD usage for sustainability reasons.

In CADD v1.6, scoring via prescoring only return the first line that is the variant. When returning scores with annotation, this leads to futher annotation lines being missed.

I would specify in the installation guide that for setting up the environment for v1.5 the correct command is:
conda env create -f src/environment_v1.5.yml

Hello, I was wondering whether there is a REST-like API for querying vcf files or single mutations for CADD scores?

Hi. I am trying to install CADD on our cluster. Where is CADD.zip? Is it this file: https://krishna.gs.washington.edu/download/CADD/v1.6/GRCh38/annotationsGRCh38_v1.6.tar.gz

Hello,
I have attached markdown output where I have done my best to illustrate and debug the issue I am having where the annotated output file only contains annotation for a small number of SNVs and the rest only these columns: Chr, Pos, A1, A2, RawScore, PHRED.
CADD_debug_08042021.pdf

This may be expected behavior, but I thought it would be good to have it documented. I noticed that for larger indels, CADD fails at the RegSeq step. I believe the cutoff is 249 bases. Can be reproduced with the following variants:

(should succeed)
1 1516567 CACACCTGGCTAATTTTTATATTTTTAGTAGAGTCGGGGTTTCACCATGTTGGCCAGCCTGGTCTTGAACTCCTGACTTCAAGTGATCCACCTGCCTCGGCCTCCCAAAGTGCTGGGATTACAGGCTTGTGCCACTGTGCCTGCCTTGTTTCATATTATTATTTTTTTATAGACAGAGTCTTAGTCTGTCTTCCAGGCCGGTGTGCAGTGGCGTGATCTCAGCTCACCGCAACCTCTACCTCCCGGGTT C

(should fail)
1 1516567 CACACCTGGCTAATTTTTATATTTTTAGTAGAGTCGGGGTTTCACCATGTTGGCCAGCCTGGTCTTGAACTCCTGACTTCAAGTGATCCACCTGCCTCGGCCTCCCAAAGTGCTGGGATTACAGGCTTGTGCCACTGTGCCTGCCTTGTTTCATATTATTATTTTTTTATAGACAGAGTCTTAGTCTGTCTTCCAGGCCGGTGTGCAGTGGCGTGATCTCAGCTCACCGCAACCTCTACCTCCCGGGTTCA C

Hi, I found the warning:
Provided cores: 1 (use --cores to define parallelism)
Rules claiming more threads will be scaled down.
Because I also found the progress in my own vcf files are very slow, I want to request multiple cores. Do you have any suggestion how to do it?

In addition, there is another waring:
Activating conda environment: ../../../software/CADD/CADD-scripts-master/envs/9f2ffdd26e4a9896cd40b8b91d251805_
Possible precedence issue with control flow operator at /wynton/group/rajkovic/jiahua/software/CADD/CADD-scripts-master/envs/9f2ffdd26e4a9896cd40b8b91d251805_/lib/site_perl/5.26.2/Bio/DB/IndexedBase.pm line 805.
Do you know whether this is important and how we can solve it?
Thank you.

I am running CADD in a virtual environment. I believe I have installed all dependencies, however, I keep getting this error and wonder if someone could provide insights in how to solve it? This occurs when running the sample file, command:

./CADD.sh -a -g GRCh37 -o output_inclAnno_GRCh37.tsv.gz -----/driverpowerEnv/CADD-scripts-master/test/input.vcf

Output:

Job counts:
count jobs
1 annotation
1 imputation
1 join
1 prepare
1 prescore
1 score
6
[Sun Apr 11 11:53:33 2021]
Error in rule prepare:
jobid: 2
output: /scratch/tmp/tmp.ksJO4PiOzk/input.prepared.vcf
conda-env: -------/driverpowerEnv/CADD-scripts-master/envs/99ccf3ab2dba635be40bcab17c5b364d
shell:

    cat /scratch/tmp/tmp.ksJO4PiOzk/input.vcf         | python $CADD/src/scripts/VCF2vepVCF.py         | sort -k1,1 -k2,2n -k4,4 -k5,5         | uniq > /scratch/tmp/tmp.ksJO4PiOzk/input.prepared.vcf
    
    (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)

Exiting because a job execution failed. Look above for error message

Thank you so much!

Hi, from the manual installation guide, I went to the web page, https://cadd.bihealth.org/download, but found there are many different files for the same genome version. I want to use Genome build GRCh38 / hg38. Although their file names are kind of informative, there's no descriptive document to describe their difference. Their name likely indicated that some files are redundant to some degree and some files are too large, so should we download all files to run the program fast? Thank you.

Hi,

Is it possible to add gnomAD AF annotations for GRCh38 using offline setup?

Cheers,
Hagen

Could I use micromamba to install the required packages for the offline installation instead of miniconda?

Hi,

This isn't quite an issue, but I am having trouble working this out from the VEP help pages and I hope you can help. Do you know if vep (I'm using v100) is able to annotate the new 1.6 CADD scores? I'm assuming if I download the pre-scored files it should work ok? Do you know if it is able to score novel indels or will it just take the pre-scored files and look up the relevant affects? Or would I need to download and run the CADD code if I wanted a CADD score for novel indels?

Thanks a lot

Dan

I have a vcf files of just SNVs. When I run CADD pipeline it produces an empty imputation file. But when I include deletions and insertions in my vcf file, it produces an imputation file with deletions + insertions but not SNVs. Why is that? Could you provide some insights on this.

Hi, I was going through release notes of CADD v1.6. In this version, 134 annotations are used. And n-level categorical values, such as reference allele identity, are converted to n individual Boolean flags. When I expand these annotations I end up getting 214 features for each variant. Whereas, in the original article 949 features are mentioned. Can you briefly explain how do you expand these annotations to get 949 features?
Thank you!

Hi there, I'm attempting to run CADD on a VM, and I've ran the install.sh script. When I try to run CADD on the test provided, it gives me this error read out:

Running snakemake pipeline: snakemake /tmp/tmp.fGiFALQq9Y/input.tsv.gz --use-conda --conda-prefix /home/wphu/CADD-scripts-master/envs --cores 1 --configfile /home/wphu/CADD-scripts-master/config/config_GRCh38_v1.6_noanno.yml --snakefile /home/wphu/CADD-script s-master/Snakefile -q Job counts: count jobs 1 annotation 1 imputation 1 join 1 prepare 1 prescore 1 score 6 /bin/bash: activate: No such file or directory /bin/bash: activate: No such file or directory Opening /home/wphu/CADD-scripts-master/data/prescored/GRCh38_v1.6/no_anno/gnomad.genomes.r3.0.indel.tsv.gz... Opening /home/wphu/CADD-scripts-master/data/prescored/GRCh38_v1.6/no_anno/whole_genome_SNVs.tsv.gz... /bin/bash: activate: No such file or directory /bin/bash: line 1: vep: command not found Traceback (most recent call last): File "/home/wphu/CADD-scripts-master/src/scripts/annotateVEPvcf.py", line 3, in <module> from ConfigParser import ConfigParser ModuleNotFoundError: No module named 'ConfigParser' [Wed Oct 7 23:34:47 2020] Error in rule annotation: jobid: 4 output: /tmp/tmp.fGiFALQq9Y/input.anno.tsv.gz conda-env: /home/wphu/CADD-scripts-master/envs/457093c1 RuleException: CalledProcessError in line 55 of /home/wphu/CADD-scripts-master/Snakefile: Command 'source activate /home/wphu/CADD-scripts-master/envs/457093c1; set -euo pipefail; cat /tmp/tmp.fGiFALQq9Y/input.novel.vcf | vep --quiet --cache --offline --dir $CADD/data/annotation s/GRCh38_v1.6/vep --buffer 1000 --no_stats --species homo_sapiens --db_version=95 --assembl y GRCh38 --format vcf --regulatory --sift b --polyphen b --per_gene --ccds --domains --numb ers --canonical --total_length --vcf --force_overwrite --output_file STDOUT | python $CADD/src/scripts/anno tateVEPvcf.py -c $CADD/config/references_GRCh38_v1.6.cfg | gzip -c > /tmp/tmp.fGiFALQq9Y/input. anno.tsv.gz ' returned non-zero exit status 1. File "/home/wphu/CADD-scripts-master/Snakefile", line 55, in __rule_annotation File "/home/wphu/miniconda3/envs/cadd/lib/python3.6/concurrent/futures/thread.py", line 56, in run Exiting because a job execution failed. Look above for error message

The top issue seems to be that I'm missing some packages. I've tried installing them with pip, but I think that the conda environment CADD is running in is distinct from the environment the machine is sitting in. I've tried deleting and reinstalling the CADD folder multiple times, with the same result.

Could you help with what is probably environment issues?

The Readme file needs an update for the location of the annotation files...

This line need to be changed from:

wget -c http://krishna.gs.washington.edu/download/CADD/v1.6/annotationsGRCh38_v1.6.tar.gz
to:

wget -c https://krishna.gs.washington.edu/download/CADD/v1.6/GRCh38/annotationsGRCh38_v1.6.tar.gz

Similar for 37.

Hello,

I'm using CADDv1.5 (GRCh38) to score a large number of SNVs and indels, and wanted to know how to interpret output and an error message when an indel in my VCF is potentially not found in the prescored file. I can't be sure, but it seems as though CADD returns indels that are upstream/downstream of that position if the ref/alt alleles match what was in my VCF?

Here are the commands and previews of my files:
% ./CADD.sh -a -g GRCh38 -o CADD_ExampleOutput_withAnno.tsv.gz ExampleInput.vcf.gz
CADD-v1.5 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health 2013-2019. All rights reserved.
Opening /shared/CADD/CADD-scripts/data/prescored/GRCh38_v1.5/incl_anno/InDels_inclAnno.tsv.gz...
Opening /shared/CADD/CADD-scripts/data/prescored/GRCh38_v1.5/incl_anno/whole_genome_SNVs_inclAnno.tsv.gz...
Input file /tmp/tmp.sVxd4dNddm/ExampleInput.csv.gz is empty.

CADD scored variants written to file: CADD_ExampleOutput_withAnno.tsv.gz

My input VCF (file attached):
10 104817 . C CCA
10 104818 . C A
10 104818 . C T
10 104820 . C CCA

CADD output (file attached w/full anno):
10 104816 C CCA INS ...
10 104817 C CCA INS ...
10 104818 C A SNV ...
10 104818 C CCA INS ...
10 104818 C T SNV ...
10 104819 C CCA INS ...

I had thought CADD was matching strictly on chr:pos_ref/alt, but that wouldn't explain the output that I'm getting, since the positions for the indels don't match my input VCF, even when you account for the length of the insertion. This output also seems different than what's produced using the test/input.vcf (in terms of positions being returned that weren't in my input VCF), and the issue also doesn't occur for every indel in my dataset. Since CADD uses Ensembl, I ran the most recent version of Ensembl-VEP (98.3) with my same input VCF and got the following result (file attached). However, I realize that CADDv1.5 is using Ensembl 95, so it's not a direct comparison:

% ./vep --cache --dir_cache .vep/ -i ExampleInput.vcf.gz --show_ref_allele --symbol --per_gene --no_stats -o Ensembl_ExampleOutput

10_104818_-/CA 10:104817-104818
10_104818_C/A 10:104818
10_104818_C/T 10:104818
10_104821_-/CA 10:104820-104821

I also got an odd error message when running CADD with my example input VCF (above), which seems to correspond to a tmp CSV file that's being created (and is subsequently empty) when calling the 'trackTransformation.py' in the 'CADD.sh' script.

Please let me know if you have any questions, and I greatly appreciate any help in clarifying this issue! Thanks in advance,
Jackie

CADD_ExampleOutput_withAnno.tsv.gz
ExampleInput.vcf.gz
Ensembl_ExampleOutput.txt

Hello there,

When I ran ./install.sh and elected to download the indel set for GRCh37, it echoed this message (which said GRCh38 instead of GRCh37) but never actually downloaded the indels:

 - Downloading prescored InDels without annotations for GRCh38 (1 GB) http://krishna.gs.washington.edu/download/CADD/v1.4/GRCh37/InDels.tsv.gz

I'm pretty sure I see the issue in the script and will open a PR soon.

Thanks

Hi,

I executed the command "./CADD.sh test/input.vcf" and got the following error.

"""
Activating conda environment: envs/56b93169d3e29fd592952535267703b3_
[E::hts_hopen] Failed to open file /home/user/CADD-scripts-1.6.post1/data/annotations/GRCh38_v1.6//phastCons/hg38.phastCons.bg.gz
[E::hts_open_format] Failed to open file "/home/user/CADD-scripts-1.6.post1/data/annotations/GRCh38_v1.6//phastCons/hg38.phastCons.bg.gz" : Exec format error
Traceback (most recent call last):
File "/home/user/CADD-scripts-1.6.post1/src/scripts/annotateVEPvcf.py", line 94, in
annotation.load(args)
File "/home/user/script/CADD-scripts-1.6.post1/src/scripts/lib/Annotations.py", line 30, in load
self.tabix = pysam.TabixFile(self.path,'r'),None,None,None,None,None,None,"%s annotation" % self.name
File "pysam/libctabix.pyx", line 350, in pysam.libctabix.TabixFile.cinit
File "pysam/libctabix.pyx", line 391, in pysam.libctabix.TabixFile._open
IOError: could not open file /home/user/CADD-scripts-1.6.post1/data/annotations/GRCh38_v1.6//phastCons/hg38.phastCons.bg.gz
"""

The same error for another file occurred when the command "./CADD.sh -a -g GRCh37 -o output_inclAnno_GRCh37.tsv.gz test/input.vcf" of version GRCh37.

"""
IOError: could not open file /home/user/CADD-scripts-1.6.post1/data/annotations/GRCh37_v1.6//mutation_density/mutDensity_gnomAD/variant_density.gnomad.2.0.1.100.bg.gz
"""

If I open the file in that location directly, it will open normally.
What's the problem?

Thank you.

Hi,

I am trying to install CADD-scripts on my local env and the legacy dependency of mmsplice 1.0.1 with concise is giving me problems installing. Since mmsplice 2.x the concise dependency has be integrated into the core api and much of the predictions are 1:1 with the legacy api. would it be possible to bump the version of mmsplice to the most recent version?

I am trying to have local installation of CADD v1.7.

Dear,

Could you please point me to the definitions for the NA values for the Splice-AI.

There are duplicate records for a variant due to the relation with more than one gene or one transcript.

there are scores sometimes for one of the genes and for the other one you have NA. So I am a bit confused and I would like to know what is the logic behind this.

Here is an example.

10 73483791 T A NA ENSR00000980981 NA NA NA NA NA
10 73483791 T A ENSG00000214688 ENST00000441508 C10orf105 NA NA NA NA
10 73483791 T A ENSG00000107736 ENST00000224721 CDH23 0.07 0.04 0 0
10 73483791 T C NA ENSR00000980981 NA NA NA NA NA
10 73483791 T C ENSG00000107736 ENST00000224721 CDH23 0.02 0.02 0 0
10 73483791 T C ENSG00000214688 ENST00000441508 C10orf105 NA NA NA NA

Thanks in advance

Hi.

1. I ran CADD v1.6 on a VCF file using hg38 as the reference like this:

./CADD-scripts/CADD.sh -c 6 -a -g GRCh38 -o split.M.vcf.cadd.gz split.M.vcf.gz

2. Everything seemed OK, but I looked a critical SNV at position 11253 on chrM and CADD reported it as Intergenic.

M 11253 T C SNV 0 Intergenic INTERGENIC 0 intergenic 0.477 0.04 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 10000000 10000000 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 1.92 0.46 1.34 0.57 1.20 0.31 2.54 0.49 2.25 0.70 1.36 0.48 1.96 0.36 1.16 0.35 1.49 0.29 1.77 0.34 2.49 1.10 32624.20 6828.83 342.64 134.35 NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA NA 204 412 0.475676 6.248

3. However, this is clearly a CDS SNV that is associated with a known phenotype. Here is the link to this position in the UCSC browser.

https://genome.ucsc.edu/cgi-bin/hgTracks?db=hg38&lastVirtModeType=default&lastVirtModeExtraState=&virtModeType=default&virtMode=0&nonVirtPosition=&position=chrM%3A11252%2D11254&hgsid=1629186917_hNnPacm0uiOrlOAhCGcWeEHn6xy7

Could CADD be reporting this wrong or did I do something wrong?

Thanks,
Alex

Hi,

I noticed that many synonymous variants are scored higher in the CADD 1.7.
for instance "21_46272794_C_T" new PHRED_Score = 18.55, v1.6 PHRED_Score = 12.00
The variant is synonymous. (pulled from the prescored files)

Hi, would it be possible to use CADD-scripts as a python library to annotate dataframes of variants, without writing files to disk?
For example, something like this:

>>> variants_df.columns
["chrom", "pos", "ref", "alt", "vep_consequences"]

>>> import cadd_scripts
>>> cadd_scripts.annotate(variants_df)
["chrom", "pos", "ref", "alt", "vep_consequences", "other", "annotations", ...]

Hi -

the URL for the GRCh38 prescored InDels in the installer script seems to be wrong

InDels_SNVs.tsv.gz does not exist. InDels.tsv.gz does and that is incidentally also the name of the file for GRCh37.

Hi,

I get this error below - how can I resolve this?

Cheers

Hi,
I came across this error when I install CADD using ./install.sh

snakemake: error: unrecognized arguments: --create-envs-only

I'm wondering if this is because the version of snakemake i'm using. I'm using the latest version of 5.30.1. and they seem to change the parameter name to --conda-create-envs-only. Should I downgrade snakemake to any specific version?

Thanks!

Hi,

Previously I had no problem of running CADD. However, after recent re-installation, I got the following error

CADD-scripts-master$ snakemake test/input.vcf --use-conda --conda-create-envs-only --conda-prefix ./envs -j1 --configfile config/config_GRCh38_v1.6.yml --snakefile Snakefile

Building DAG of jobs...
MissingInputException in line 4 of ~/CADD-scripts-master/Snakefile:
Missing input files for rule decompress:
test/input.vcf.gz

I did not quite understand this issue, because my input file does not have .gz extension.
Any help is appreciated

conda 4.9.2
snakemake 6.0.0

I am running CADD script on my system to get annotations for my vcf file. However, CADD.sh seems to remove the imputation file at the end. I want to retain the imputation file too. How can I do that? I made changes to snakeMake file whereby I remove the last two rules and in CADD.sh as I give $Name.csv.gz as TMP_OUTFILE. But this produces an empty imputation file. Is there another way to obtain imputation file?

Dear CADD Team,
Thank you for providing this useful resource. I have been using CADD1.3 for some time, but had to update to 1.6.
Here are my installation notes with the hope they may help someone; please feel free to edit as you see fit.

• use miniconda3, otherwise cannot install snakemake
  UnsatisfiableError:
  The following specifications were found to be incompatible with the existing python installation in your environment:
  snakemake -> python[version='3.4.|3.5.|>=3.5,<3.6.0a0|>=3.6,<3.7.0a0|3.6.*']
  Your python: python=2.7
• unset PYTHONPATH, otherwise a warning about potential python conflicts
• edit install.sh, replace --create-envs-only with --conda-create-envs-only
  otherwise: snakemake: error: unrecognized arguments: --create-envs-only

wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
unset PYTHONPATH
bash Miniconda3-latest-Linux-x86_64.sh -p $HOME/miniconda3 -b
export PATH=$HOME/miniconda3/bin:$PATH
conda install -c conda-forge -c bioconda snakemake

go to https://github.com/kircherlab/CADD-scripts/ , "Clone", “Download ZIP”, copy to destination, unzip
edit install.sh, replace --create-envs-only with --conda-create-envs-only

• downloading only GRCh38 SNP datasets (takes some time, make sure you have enough space)
  ./install.sh
  Do you want to install the virtual environments with all CADD dependencies via conda? (y)/n y
  Do you want to install CADD v1.6 for GRCh37/hg19? (y)/n n
  Do you want to install CADD v1.6 for GRCh38/hg38? (y)/n y
  Do you want to load annotations (Annotations can also be downloaded manually from the website)? (y)/n y
  Do you want to load prescored variants (Makes SNV calling faster. Can also be loaded/installed later.)? y/(n) y
  Do you want to load prescored variants for scoring with annotations (Warning: These files are very big)? y/(n) n
  Do you want to load prescored variants for scoring without annotations? y/(n) y
  Do you also want to load prescored InDels? We provide scores for well known InDels from sources like ClinVar, gnomAD/TOPMed etc. y/(n) n

• run a test
  ./CADD.sh test/input.vcf

I am not sure if I have to load annotations (the 4th entry above) if I only want to produce a file with the CADD scores for a list of SNPs (no annotations). Can you please comment?

I installed version 1.6 CADD and while testing the installation using the command

./CADD.sh test/input.vcf

and i getting the error

`CADD-v1.6 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health 2013-2020. All rights reserved.
Running snakemake pipeline:
snakemake /tmp/tmp.H9ILdzavwI/input.tsv.gz --use-conda --conda-prefix /home/sreeshma/CADD/CADD-scripts-master/envs --cores 1
--configfile /home/sreeshma/CADD/CADD-scripts-master/config/config_GRCh38_v1.6_noanno.yml --snakefile /home/sreeshma/CADD/CADD-scripts-master/Snakefile -q
Building DAG of jobs...
Using shell: /usr/bin/bash
Provided cores: 1 (use --cores to define parallelism)
Rules claiming more threads will be scaled down.
Job stats:
job count min threads max threads

annotation 1 1 1
imputation 1 1 1
join 1 1 1
prepare 1 1 1
prescore 1 1 1
score 1 1 1
total 6 1 1

Select jobs to execute...
Activating conda environment: envs/592bdf516157604235519e81ddd225c7_
Select jobs to execute...
Activating conda environment: envs/592bdf516157604235519e81ddd225c7_
Removing temporary output /tmp/tmp.H9ILdzavwI/input.prepared.vcf.
Select jobs to execute...
Activating conda environment: envs/592bdf516157604235519e81ddd225c7_
Possible precedence issue with control flow operator at /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/lib/site_perl/5.26.2/Bio/DB/IndexedBase.pm line 805.

-------------------- EXCEPTION --------------------
MSG: ERROR: No cache found for homo_sapiens, version 95

STACK Bio::EnsEMBL::VEP::CacheDir::dir /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/CacheDir.pm:328
STACK Bio::EnsEMBL::VEP::CacheDir::init /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/CacheDir.pm:227
STACK Bio::EnsEMBL::VEP::CacheDir::new /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/CacheDir.pm:111
STACK Bio::EnsEMBL::VEP::AnnotationSourceAdaptor::get_all_from_cache /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/AnnotationSourceAdaptor.pm:115
STACK Bio::EnsEMBL::VEP::AnnotationSourceAdaptor::get_all /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/AnnotationSourceAdaptor.pm:91
STACK Bio::EnsEMBL::VEP::BaseRunner::get_all_AnnotationSources /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/BaseRunner.pm:175
STACK Bio::EnsEMBL::VEP::Runner::init /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/Runner.pm:123
STACK Bio::EnsEMBL::VEP::Runner::run /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/share/ensembl-vep-95.1-0/modules/Bio/EnsEMBL/VEP/Runner.pm:194
STACK toplevel /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/bin/vep:225
Date (localtime) = Mon Dec 25 14:46:12 2023
Ensembl API version = 95

Traceback (most recent call last):
File "/home/sreeshma/CADD/CADD-scripts-master/src/scripts/annotateVEPvcf.py", line 33, in
vcf_reader = vcf.Reader(sys.stdin)
File "/home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7_/lib/python2.7/site-packages/vcf/parser.py", line 300, in init
self.parse_metainfo()
File "/home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7/lib/python2.7/site-packages/vcf/parser.py", line 317, in parse_metainfo
line = next(self.reader)
StopIteration
[Mon Dec 25 14:46:12 2023]
Error in rule annotation:
jobid: 5
input: /tmp/tmp.H9ILdzavwI/input.novel.vcf
output: /tmp/tmp.H9ILdzavwI/input.anno.tsv.gz
conda-env: /home/sreeshma/CADD/CADD-scripts-master/envs/592bdf516157604235519e81ddd225c7
shell:

    cat /tmp/tmp.H9ILdzavwI/input.novel.vcf         | vep --quiet --cache --offline --dir $CADD/data/annotations/GRCh38_v1.6/vep             --buffer 1000 --no_stats --species homo_sapiens             --db_version=95 --assembly GRCh38             --format vcf --regulatory --sift b --polyphen b --per_gene --ccds --domains             --numbers --canonical --total_length --vcf --force_overwrite --output_file STDOUT         | python $CADD/src/scripts/annotateVEPvcf.py             -c $CADD/config/references_GRCh38_v1.6.cfg         | gzip -c > /tmp/tmp.H9ILdzavwI/input.anno.tsv.gz
    
    (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)

Removing output files of failed job annotation since they might be corrupted:
/tmp/tmp.H9ILdzavwI/input.anno.tsv.gz
Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message
Complete log: .snakemake/log/2023-12-25T144611.003618.snakemake.log`

But the cache directory homo_sapiens is present inside folder (CADD/CADD-scripts-master/data/annotations/GRCh37_v1.6/vep/homo_sapiens). what to do here in this situation?

Thank you in Advance.

I'm calling

# ./CADD.sh -o >(zcat) -g GRCh37 -v v1.4 test/input.vcf  | head

and the resulting columns contain no extra annotations for SNVs but they are present for indel (see below). I would expect the indel lines to contain no annotations as well.

CADD-v1.5 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health 2013-2019. All rights reserved.
Opening /vol/local/data/CADD/data/prescored/GRCh37_v1.4/no_anno/InDels_inclAnno.tsv.gz...
Opening /vol/local/data/CADD/data/prescored/GRCh37_v1.4/no_anno/InDels.tsv.gz...
Opening /vol/local/data/CADD/data/prescored/GRCh37_v1.4/no_anno/whole_genome_SNVs.tsv.gz...

CADD scored variants written to file: /dev/fd/63
##CADD GRCh37-v1.4 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health 2013-2019. All rights reserved.
#Chrom  Pos     Ref     Alt     RawScore        PHRED
1       10001   T       A       0.118631        4.575
1       10001   T       TC      INS     1       Intergenic      DOWNSTREAM      1       downstream      0.448933333333  0.00993288590604        NA      NA      NA      NA      NA      NA       ENSG00000227232 ENST00000438504 WASH7P  NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      1869    3670    NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      994     NA      NA      NA      NA      0.008   0.000   0.000   0.000   0.016   0.000   0.024   0.087   0.472   0.000   0.000   0.000    0.000   0.000   0.394   NA      NA      0       0       NA      NA      NA      NA      NA      GM1     10.04   2.84    8.0     NA      NA      NA      NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      NA      NA      2773    NA      NA      NA      NA      NA      NA      3       2       32      NA      NA      -0.083014       1.567
1       10001   T       TC      INS     1       Intergenic      UPSTREAM        1       upstream        0.448933333333  0.00993288590604        NA      NA      NA      NA      NA      NA       ENSG00000223972 ENST00000456328 DDX11L1 NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      1869    3670    NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      994     NA      NA      NA      NA      0.008   0.000   0.000   0.000   0.016   0.000   0.024   0.087   0.472   0.000   0.000   0.000    0.000   0.000   0.394   NA      NA      0       0       NA      NA      NA      NA      NA      GM1     10.04   2.84    8.0     NA      NA      NA      NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      NA      NA      2773    NA      NA      NA      NA      NA      NA      3       2       32      NA      NA      -0.083014       1.567
1       10001   T       TC      INS     1       RegulatoryFeature       REGULATORY      4       regulatory      0.448933333333  0.00993288590604        NA      NA      NA      NA      NA       NA      NA      ENSR00000344265 NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      NA      1869    3670    NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      994     NA      NA      NA      NA      0.008   0.000   0.000   0.000   0.016   0.000   0.024   0.087   0.472   0.000   0.000   0.000    0.000   0.000   0.394   NA      NA      0       0       NA      NA      NA      NA      NA      GM1     10.04   2.84    8.0     NA      NA      NA      NA      NA      NA      NA       NA      NA      NA      NA      NA      NA      NA      NA      2773    NA      NA      NA      NA      NA      NA      3       2       32      NA      NA      -0.083014       1.567
1       10008   A       AA      -0.082931       1.568

A workaround is simply to use the -a and then cut out the appropriate columns. I think that it would also be nice if the copyright lines were printed to stderr and not stdout.

> ./CADD.sh -a -o >(zcat) -g GRCh37 -v v1.4 test/input.vcf  | tail -n +5 | cut -f 1-4,106,107 | head
Opening /vol/local/data/CADD/data/prescored/GRCh37_v1.4/incl_anno/whole_genome_SNVs_inclAnno.tsv.gz...
#Chrom  Pos     Ref     Alt     RawScore        PHRED
1       10001   T       A       0.118631        4.575
1       10001   T       A       0.118631        4.575
1       10001   T       A       0.118631        4.575
1       10001   T       TC      -0.083014       1.567
1       10001   T       TC      -0.083014       1.567
1       10001   T       TC      -0.083014       1.567
1       10008   A       AA      -0.082931       1.568
1       10008   A       AA      -0.082931       1.568
1       10008   A       AA      -0.082931       1.568

I read the README file, but it's unclear from the description if prescored files are a superset of the information in the basic files or whether they contain distinct information. In other words, do I download either "All possible SNVs of GRCh38/hg38 (80 GB)" or "All possible SNVs of GRCh38/hg38 incl. all annotations (292 GB)" (and similarly for indels) or is it necessary to download both kinds of files?

Hi all,

I'm having trouble getting CADD to run on multiple cores. In the help description, there's an option for multiple cores, but in CADD.sh the option for multiple cores on line 38 was originally v) CORES=$OPTARG, which I modified to c) CORES=$OPTARG, in line with the documentation. This allows the program to report that Snakemake is using up multiple cores, but checked CPU usage does not reflect that. Are there only certain parts of the code that have multi-core support?

Thanks.

CADD.sh gives an "Unknown file format" error message if the input VCF filename is something like samplename.vcf_altered.vcf.gz where ".vcf" occurs multiple times. Sometimes I get VCFs from upstream that look like this and it would be nice to not have to always rename them. I'll send a PR over with a suggested fix.

Hi

I did an install with the install script, with a Conda environment, everything seemed fine until I tried running the first test and I got this error (added some lines

(cadd-env) ➜  CADD-scripts git:(master) ./CADD.sh test/input.vcf
CADD-v1.5 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health 2013-2019. All rights reserved.
/home/nuin/anaconda3/etc/profile.d/conda.sh: line 29: PS1: unbound variable
(cadd-env) ➜  CADD-scripts git:(master) nano /home/nuin/anaconda3/etc/profile.d/conda.sh
(cadd-env) ➜  CADD-scripts git:(master) echo $PS1
(cadd-env) %(?:%{%}➜ :%{%}➜ ) %{$fg[cyan]%}%c%{$reset_color%} $(git_prompt_info)

Same result with ZSH and BASH.

Any help appreciated

Thanks

Hi there ,

regarding the new version of CADD v1.7 installation on docker, i have faced a problem " The following environment variables are requested by the workflow but undefined. Please make sure that they are correctly defined before running Snakemake:
0.802 CADD
"
when i try to install it on docker.

previous version perfectly could be installed , but new one i can not. i will appreciate it if you offer me any suggestions? hints?

snakemake version i use is v.7 and FROM mambaorg/micromamba:1.5.8

full error:
RUN cd /opt && curl -L https://github.com/kircherlab/CADD-scripts/archive/refs/tags/v1.7.tar.gz | tar xz && cd CADD-scripts-1.7 && ln -s CADD.sh cadd.sh 1.1s
=> ERROR [5/5] RUN cd /opt/CADD-scripts-1.7 && snakemake -j 1 test/input.tsv.gz --use-conda --conda-create-envs-only --conda-prefix envs --configfile config/config_GRCh38_v1.7.yml --snakefile Snakefile 0.8s

[5/5] RUN cd /opt/CADD-scripts-1.7 && snakemake -j 1 test/input.tsv.gz --use-conda --conda-create-envs-only --conda-prefix envs --configfile config/config_GRCh38_v1.7.yml --snakefile Snakefile:
0.714 WorkflowError in file /opt/CADD-scripts-1.7/Snakefile, line 20:
0.714 The following environment variables are requested by the workflow but undefined. Please make sure that they are correctly defined before running Snakemake:
0.714 CADD
0.714 File "/opt/CADD-scripts-1.7/Snakefile", line 20, in

##########################################################################
if i just create docker without CADD and then entering the docker image and installing CADD by ./install and then commit it in new image it wseems it works , but i have faced new error, (i have all folders in /usr/bin and all are bind to the annotation on my pc) but it seems CADD can not find some files.
MissingInputException in rule annotate_esm in file /usr/bin/Snakefile, line 123:
Missing input files for rule annotate_esm:
output: /tmp/tmp.9DnBOrJwwP/input.esm_missens.vcf.gz, /tmp/tmp.9DnBOrJwwP/input.esm_frameshift.vcf.gz, /tmp/tmp.9DnBOrJwwP/input.esm.vcf.gz
wildcards: file=/tmp/tmp.9DnBOrJwwP/input
affected files:
data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_1.pt
data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_5.pt
data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_2.pt
data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_4.pt
data/annotations/GRCh38_v1.7/esm/esm1v_t33_650M_UR90S_3.pt
data/annotations/GRCh38_v1.7/esm/pep.110.fa

Thanks

I found CADD-splice has been implemented in CADD v1.6.
I downloaded prescored annotated SNV and indel.

I have some new indels and SNVs for splicing test.

I tried to get scores from webserver. But there are only Rawscore and PHRED in output.

I'm now using standalone script. But there are few documents mentioned how to get CADD-splice score.

May I ask how to get these scores? Thanks

It would be nice to have the latest changes of the install.sh in a release so the downstream conda package can benefit from this.

It would be nice if this was handled a bit more gracefully than a Snakemake crash.

I installed CADD 1.7 from master. After installation I attempted to run CADD on the provided test variants via ./CADD.sh test/input.vcf. Unfortunately, this fails at the regseq step. The variants in the test/input.vcf file were not sorted; after sorting them I still encountered the same error included below:

CADD-v1.7 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health at Charité - Universitätsmedizin Berlin 2013-2023. All rights reserved.
Running snakemake pipeline:
snakemake /tmp/tmp.N3bzddIax6/input.tsv.gz --use-conda --conda-prefix /home/david/Projects/CADD-scripts-1.7-master/envs/conda --cores 1
--configfile /home/david/Projects/CADD-scripts-1.7-master/config/config_GRCh38_v1.7_noanno.yml --snakefile /home/david/Projects/CADD-scripts-1.7-master/Snakefile -q
Building DAG of jobs...
Your conda installation is not configured to use strict channel priorities. This is however crucial for having robust and correct environments (for details, see https://conda-forge.org/docs/user/tipsandtricks.html). Please consider to configure strict priorities by executing 'conda config --set channel_priority strict'.
Using shell: /usr/bin/bash
Provided cores: 1 (use --cores to define parallelism)
Rules claiming more threads will be scaled down.
Job stats:
job         count
--------  -------
join            1
prepare         1
prescore        1
total           3

Select jobs to execute...
Activating conda environment: envs/conda/6286c07397830d220a93727bfb2db5d3_
Select jobs to execute...
Activating conda environment: envs/conda/6286c07397830d220a93727bfb2db5d3_
Removing temporary output /tmp/tmp.N3bzddIax6/input.prepared.vcf.
Select jobs to execute...
Activating conda environment: envs/conda/49b0bd0c0764f34655987e41beb1d3d0_
Smartmatch is experimental at /home/david/Projects/CADD-scripts-1.7-master/envs/conda/49b0bd0c0764f34655987e41beb1d3d0_/share/ensembl-vep-110.1-0/modules/Bio/EnsEMBL/VEP/AnnotationSource/File.pm line 472.
Removing temporary output /tmp/tmp.N3bzddIax6/input.novel.vcf.
Select jobs to execute...
Activating conda environment: envs/conda/2708e22ad39a84f1657b8582098aec8c_
Removing temporary output /tmp/tmp.N3bzddIax6/input.vep.vcf.gz.
Removing temporary output /tmp/tmp.N3bzddIax6/input.esm_missens.vcf.gz.
Removing temporary output /tmp/tmp.N3bzddIax6/input.esm_frameshift.vcf.gz.
Select jobs to execute...
Activating conda environment: envs/conda/c1e6153218582c24ef7133fa74016642_
[Wed Mar 20 12:49:41 2024]
Error in rule annotate_regseq:
    jobid: 9
    input: /tmp/tmp.N3bzddIax6/input.esm.vcf.gz, data/annotations/GRCh38_v1.7/regseq/reference.fa, data/annotations/GRCh38_v1.7/regseq/reference.fa.genome, data/annotations/GRCh38_v1.7/regseq/Hyperopt400InclNegatives.json, data/annotations/GRCh38_v1.7/regseq/Hyperopt400InclNegatives.h5
    output: /tmp/tmp.N3bzddIax6/input.regseq.vcf.gz
    log: /tmp/tmp.N3bzddIax6/input.annotate_regseq.log (check log file(s) for error details)
    conda-env: /home/david/Projects/CADD-scripts-1.7-master/envs/conda/c1e6153218582c24ef7133fa74016642_
    shell:

        python /home/david/Projects/CADD-scripts-1.7-master/src/scripts/lib/tools/regulatorySequence/predictVariants.py         --variants /tmp/tmp.N3bzddIax6/input.esm.vcf.gz         --model data/annotations/GRCh38_v1.7/regseq/Hyperopt400InclNegatives.json         --weights data/annotations/GRCh38_v1.7/regseq/Hyperopt400InclNegatives.h5         --reference data/annotations/GRCh38_v1.7/regseq/reference.fa         --genome data/annotations/GRCh38_v1.7/regseq/reference.fa.genome         --output /tmp/tmp.N3bzddIax6/input.regseq.vcf.gz &> /tmp/tmp.N3bzddIax6/input.annotate_regseq.log

        (one of the commands exited with non-zero exit code; note that snakemake uses bash strict mode!)

Shutting down, this might take some time.
Exiting because a job execution failed. Look above for error message
Complete log: .snakemake/log/2024-03-20T124933.732867.snakemake.log

It looks like there's some version in incompatibilities in the 1.5 release yml. Wondering if there's a solution or work around ?

apple@hsc-buildbox CADD-scripts]$ conda env create -f src/environment_v1.5.yml
Collecting package metadata (repodata.json): done
Solving environment: -
Found conflicts! Looking for incompatible packages.
This can take several minutes. Press CTRL-C to abort.
failed

UnsatisfiableError: The following specifications were found to be incompatible with each other:

Package ncurses conflicts for:
pandas==0.20.3=py27_1 -> python=2.7 -> sqlite[version='>=3.20.1,<4.0a0'] -> ncurses==5.9
scikit-learn==0.20.1=py27h22eb022_0 -> python[version='>=2.7,<2.8.0a0'] -> ncurses[version='5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
pysam==0.15.2=py27h0380709_0 -> python[version='>=2.7,<2.8.0a0'] -> ncurses[version='5.9.|>=5.9,<5.10.0a0|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
pyvcf==0.6.8=py27_0 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.20.1,<4.0a0'] -> ncurses==5.9
python==2.7.13=0 -> ncurses=5.9
pyvcf==0.6.8=py27_0 -> python[version='>=2.7,<2.8.0a0'] -> ncurses[version='5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
scipy==1.0.1=py27_blas_openblas_200 -> python=2.7 -> sqlite[version='>=3.20.1,<4.0a0'] -> ncurses==5.9
numpy==1.14.2=py27_blas_openblas_200 -> python=2.7 -> sqlite[version='>=3.20.1,<4.0a0'] -> ncurses==5.9
numpy==1.14.2=py27_blas_openblas_200 -> python=2.7 -> ncurses[version='5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
pysam==0.15.2=py27h0380709_0 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.25.3,<4.0a0'] -> ncurses==5.9
scikit-learn==0.20.1=py27h22eb022_0 -> python[version='>=2.7,<2.8.0a0'] -> sqlite[version='>=3.20.1,<4.0a0'] -> ncurses==5.9
pandas==0.20.3=py27_1 -> python=2.7 -> ncurses[version='5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
samtools==1.9=h91753b0_5 -> ncurses[version='>=6.1,<6.2.0a0']
scipy==1.0.1=py27_blas_openblas_200 -> python=2.7 -> ncurses[version='5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
ensembl-vep==95.1=pl526ha4d7672_0 -> htslib -> curl[version='>=7.64.1,<8.0a0'] -> krb5[version='>=1.16.3,<1.17.0a0'] -> libedit[version='>=3.1.20170329,<3.2.0a0'] -> ncurses[version='5.9|5.9.|6.0.|>=6.0,<7.0a0|>=6.1,<6.2.0a0|>=6.1,<7.0a0']
samtools==1.9=h91753b0_5 -> curl[version='>=7.59.0,<8.0a0'] -> krb5[version='>=1.16.1,<1.17.0a0'] -> libedit[version='>=3.1.20170329,<3.2.0a0'] -> ncurses[version='>=6.1,<7.0a0']
Package libopenblas conflicts for:
pandas==0.20.3=py27_1 -> numpy[version='>=1.7'] -> openblas[version='>=0.3.3,<0.3.4.0a0'] -> libopenblas[version='0.3.3|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.7|0.3.7|0.3.7|0.3.7|>=0.3.6,<0.3.7.0a0|>=0.3.6,<1.0a0|>=0.3.7,<0.3.8.0a0|>=0.3.7,<1.0a0',build='h6e990d7_3|h6e990d7_1|h5a2b251_2|h5a2b251_1|h5a2b251_0|h5a2b251_1|h5a2b251_2|h5a2b251_3|h6e990d7_3|h6e990d7_4|h6e990d7_5|h6e990d7_6|h6e990d7_0|h6e990d7_2']
scipy==1.0.1=py27_blas_openblas_200 -> openblas[version='0.2.20|0.2.20.'] -> libopenblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.3,<1.0a0']
pysam==0.15.2=py27h0380709_0 -> bcftools=1.9 -> gsl[version='>=2.5,<2.6.0a0'] -> libblas[version='>=3.8.0,<4.0a0'] -> libopenblas[version='>=0.3.6,<0.3.7.0a0|>=0.3.6,<1.0a0|>=0.3.7,<0.3.8.0a0|>=0.3.7,<1.0a0']
pysam==0.15.2=py27h0380709_0 -> bcftools=1.9 -> gsl[version='>=2.5,<2.6.0a0'] -> libblas[version='>=3.8.0,<4.0a0'] -> openblas[version='>=0.3.6,<0.3.7.0a0'] -> libopenblas[version='0.3.3|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.7|0.3.7|0.3.7|0.3.7|>=0.2.20,<0.2.21.0a0|>=0.3.2,<0.3.3.0a0',build='h6e990d7_3|h6e990d7_1|h5a2b251_2|h5a2b251_1|h5a2b251_0|h5a2b251_1|h5a2b251_2|h5a2b251_3|h6e990d7_3|h6e990d7_4|h6e990d7_5|h6e990d7_6|h6e990d7_0|h6e990d7_2']
numpy==1.14.2=py27_blas_openblas_200 -> openblas[version='0.2.20|0.2.20.'] -> libopenblas[version='>=0.2.20,<0.2.21.0a0']
pandas==0.20.3=py27_1 -> numpy[version='>=1.7'] -> libopenblas[version='>=0.2.20,<0.2.21.0a0|>=0.3.2,<0.3.3.0a0|>=0.3.3,<1.0a0']
scikit-learn==0.20.1=py27h22eb022_0 -> libopenblas[version='>=0.3.3,<1.0a0']
scipy==1.0.1=py27_blas_openblas_200 -> numpy[version='>=1.9'] -> libblas[version='>=3.8.0,<4.0a0'] -> libopenblas[version='>=0.3.2,<0.3.3.0a0|>=0.3.6,<0.3.7.0a0|>=0.3.6,<1.0a0|>=0.3.7,<0.3.8.0a0|>=0.3.7,<1.0a0']
scikit-learn==0.20.1=py27h22eb022_0 -> blas=[build=openblas] -> openblas -> libopenblas[version='0.3.3|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.6|0.3.7|0.3.7|0.3.7|0.3.7|>=0.2.20,<0.2.21.0a0|>=0.3.2,<0.3.3.0a0|>=0.3.6,<0.3.7.0a0|>=0.3.6,<1.0a0|>=0.3.7,<0.3.8.0a0|>=0.3.7,<1.0a0',build='h6e990d7_3|h6e990d7_1|h5a2b251_2|h5a2b251_1|h5a2b251_0|h5a2b251_1|h5a2b251_2|h5a2b251_3|h6e990d7_3|h6e990d7_4|h6e990d7_5|h6e990d7_6|h6e990d7_0|h6e990d7_2']
Package tk conflicts for:
ensembl-vep==95.1=pl526ha4d7672_0 -> perl-bioperl[version='>=1.7.2'] -> perl-bio-tools-run-alignment-tcoffee -> t_coffee -> python=3.4 -> tk=8.5
numpy==1.14.2=py27_blas_openblas_200 -> python=2.7 -> tk[version='8.5.|8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
pandas==0.20.3=py27_1 -> python=2.7 -> tk[version='8.5.|8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
samtools==1.9=h91753b0_5 -> curl[version='>=7.59.0,<8.0a0'] -> krb5[version='>=1.16.1,<1.17.0a0'] -> tk[version='8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
ensembl-vep==95.1=pl526ha4d7672_0 -> htslib -> curl[version='>=7.64.1,<8.0a0'] -> krb5[version='>=1.16.3,<1.17.0a0'] -> tk[version='8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
pyvcf==0.6.8=py27_0 -> python[version='>=2.7,<2.8.0a0'] -> tk[version='8.5.|8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
python==2.7.13=0 -> tk=8.5
pysam==0.15.2=py27h0380709_0 -> python[version='>=2.7,<2.8.0a0'] -> tk[version='8.5.|8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
scikit-learn==0.20.1=py27h22eb022_0 -> python[version='>=2.7,<2.8.0a0'] -> tk[version='8.5.|8.6.|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']
scipy==1.0.1=py27_blas_openblas_200 -> python=2.7 -> tk[version='8.5.|8.6.*|>=8.6.7,<8.7.0a0|>=8.6.8,<8.7.0a0|>=8.6.9,<8.7.0a0']

Dear,

I noticed that there are minus signs for some of the SpliceAI scores, specifically in the hg19 data.

I assume this could be a bug, please take a look.

regards
Amin

Dear @holtgrewe @EvanTheB @makirc @visze @aerval

Thanks for the great tools!

I use the https://cadd.gs.washington.edu/score to get CADD score

chr1    752566  .       G       A       . 
chrX    119589419       .       ACA     A       . 
chrX    119602961       .       G       T       .

BUT variants on chrX have no CADD score.

##CADD GRCh37-v1.7 (c) University of Washington, Hudson-Alpha Institute for Biotechnology and Berlin Institute of Health at Charite - Universitaetsmedizin Berlin 2013-2023. All rights reserved.
#Chrom	Pos	Ref	Alt	RawScore	PHRED
1	752566	G	A	-0.192970	0.723

How to get CADD scores for variants on chrX ?

Thanks in advanced!

I'm trying to run CADD on my own vcf file, and it is giving me "Encountered uncovered chromosome" messages and the resulting analysis is empty. In addition, one of the temporary files generated is empty - "Input file /tmp/tmp.pdJOZKL5qm/CADD_split_vsmall.csv.gz is empty." When I submit this file to the CADD server for analysis, it does return a score and result. Is there any advice for input files when I run it myself? Thanks.

I've installed gnomad.genomes.r3.0.indel_inclAnno.tsv.gz and whole_genome_SNVs_inclAnno.tsv.gz under prescored/GRCh38_v1.6/incl_anno.

command line:
./CADD.sh -a -g GRCh38 -o ~/data/output.txt ~/data/input.vcf

It reports with following message:

Encountered uncovered chromosome
Encountered uncovered chromosome
Encountered uncovered chromosome
Encountered uncovered chromosome
Possible precedence issue with control flow operator at /home/tomas/CADD/CADD-scripts-master/envs/bbfedf5e67480733367291efe3002c46/lib/site_perl/5.26.2/Bio/DB/IndexedBase.pm line 805.

What happened here?

btw. I notice test.vcf does not have any headers and columns after ALT. Is it necessary to reformat my vcf?