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View Code? Open in Web Editor NEWQuasiModo: Assessing viral genomic analysis methods on HCMV strain mixture
License: GNU General Public License v3.0
QuasiModo: Assessing viral genomic analysis methods on HCMV strain mixture
License: GNU General Public License v3.0
The new metaQUAST 5.10 allows --reuse-combined-alignments option to ensure the evaluation metrics can be calculated based on unique mapping.
Add the structure (tree view) of the output folder in the readme.
Reuse the script from the HCMV evaluation pipeline for custom data
Remove largest alignment and mismatch plot in the assembly figure. And summarize the rank of assemblers on different metrics with given weights. The important and indispensable metrics are genome fraction, L50, N50, number of misassembly.
Since the values vary massively, for better comparison a log scale of y might be more clear
The Savage
process is too computational intensive and time costly, so the contigs should be attached along with this repo. User do not need to execute it from scratch. Other results including assembles, vcf, even the output of metaquast will also be added in the repo. Then an option that allows users to just visualize all benchmarking results will be implemented as well.
replace venndiagram to upsetplot for more than 4 sets on custom dataset.
Hi all
is there a particular structure/way to prepare custom data for quasimodo?
I run three variant callers and tried to run vareval but not sure what data/structure is missing
Or is quasimodo running the callers as part of benchmark?
Last, about
"! Due to the high computational and time cost, by default this program do not run the whole benchmark for HCMV dataset from scratch (based on reads), instead it benchmarks the variant call and assembly based on the VCF files and scaffolds provided within this program under data directory." : how can we run from scratch using fastq.gz (where do we use the --slow parameter?)
Thanks, ibseq
I am trying to use Quasimodo to compare variant calling from different variant callers in a synthetic dataset. I ran the Quasimodo successfully,(python3 run_benchmark.py vareval) however, the vcf files in "tp" folder did not have any entries except the headers, whereas the vcf files in the โfpโ folder has SNP/indel entries (at least some them should be correct calls). Can you advice what is going wrong, and why vcf files in "tp" folder doesn't have any entries. Ideally, we are trying to identify the SNPs/indels which fall into the 4 different category (TP, FP, TN, FN).
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