A docker image containing the source code and dependencies has been published for reproducibility. You can run it using the singularity container runtime.
The entire analysis can be completed in just three steps:
-
Specific the path (with label) of both rawdata and references for your project in a YAML format.
data.yaml
for example(Click to expand)samples: HeLa-WT: input: rep1: - R1: ./rawdata/HeLa-WT-polyA-input-rep1-run1_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-input-rep1-run1_R2.fq.gz - R1: ./rawdata/HeLa-WT-polyA-input-rep1-run2_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-input-rep1-run2_R2.fq.gz rep2: - R1: ./rawdata/HeLa-WT-polyA-input-rep2-run1_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-input-rep2-run1_R2.fq.gz - R1: ./rawdata/HeLa-WT-polyA-input-rep2-run2_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-input-rep2-run2_R2.fq.gz treated: rep1: - R1: ./rawdata/HeLa-WT-polyA-treated-rep1-run1_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-treated-rep1-run1_R2.fq.gz - R1: ./rawdata/HeLa-WT-polyA-treated-rep1-run2_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-treated-rep1-run2_R2.fq.gz rep2: - R1: ./rawdata/HeLa-WT-polyA-treated-rep2-run1_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-treated-rep2-run1_R2.fq.gz - R1: ./rawdata/HeLa-WT-polyA-treated-rep2-run2_R1.fq.gz R2: ./rawdata/HeLa-WT-polyA-treated-rep2-run2_R2.fq.gz references: spike: fa: ./ref/spike_expand.fa bt2: ./ref/spike_expand spikeN: fa: ./ref/spike_degenerate.fa blast: ./ref/spike_degenerate rRNA: fa: ./ref/Homo_sapiens.GRCh38.rRNA.fa bt2: ./ref/Homo_sapiens.GRCh38.rRNA smallRNA: fa: ./ref/Homo_sapiens.GRCh38.smallRNA.fa bt2: ./ref/Homo_sapiens.GRCh38.smallRNA genome: fa: ./ref/Homo_sapiens.GRCh38.genome.fa star: ./ref/Homo_sapiens.GRCh38.genome gtf: ./ref/Homo_sapiens.GRCh38.genome.gtf gtf_collapse: ./ref/Homo_sapiens.GRCh38.genome.collapse.gtf contamination: fa: ./ref/contamination.fa bt2: ./ref/contamination
Read the documentation on how to customize.
-
Run all the analysis by one command:
singularity run docker://y9ch/sacseq:latest
default settings(Click to expand)
- default config file:
data.yaml
- default output dir:
./results
- default jobs in parallel:
48
Read the documentation on how to customize.
- default config file:
-
View the analytics report and use the m6A sites for downstream analysis.
The output of all the steps will be in one folder (
./results
) under the current path. A webpage report of all the analysis will be in./results/report.html
(example).
https://y9c.github.io/m6A-SACseq/
- Ge, R., Ye, C., Peng, Y. et al. m6A-SAC-seq for quantitative whole transcriptome m6A profiling. Nat Protoc (2022). https://doi.org/10.1038/s41596-022-00765-9
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