https://github.com/fenglin0/benchmarking_variant_callers

In this study, we perform systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We evaluate the performances of these tools in different read depths, genomic contexts, functional regions and variant allele frequencies.
https://github.com/fenglin0/benchmarking_variant_callers

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In this study, we perform systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We evaluate the performances of these tools in different read depths, genomic contexts, functional regions and variant allele frequencies.

• Host: GitHub
• URL: https://github.com/fenglin0/benchmarking_variant_callers
• Owner: fenglin0
• Created: 2019-10-15T17:31:53.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2019-10-16T07:48:43.000Z (about 5 years ago)
• Last Synced: 2024-02-15T11:32:06.739Z (10 months ago)
• Language: Shell
• Homepage:
• Size: 8.79 KB
• Stars: 13
• Watchers: 1
• Forks: 7
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# benchmarking_variant_callers

In this study, we perform systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We evaluate the performances of these tools in different read depths, genomic contexts, functional regions and variant allele frequencies.