How to Call Mutations From Your Own Whole-Genome Sequencing Data
A working pipeline that turns 30x whole-genome FASTQs into a filtered and benchmarked VCF, plus what changes when the variants are somatic.
9 posts
A working pipeline that turns 30x whole-genome FASTQs into a filtered and benchmarked VCF, plus what changes when the variants are somatic.
A step-by-step WGS pipeline for a single human genome: alignment with bwa-mem2, variant calling with DeepVariant, structural variants with Manta, annotation with VEP, and the QC numbers that tell you whether any of it worked.
A working pipeline from FASTQ to annotated VCF for one human genome, with DeepVariant and GATK calling and benchmarking against GIAB truth sets.
A working pipeline that turns 30x whole-genome FASTQ or CRAM into a filtered and annotated variant call set, with the tools and checks we would use.
A working pipeline for analyzing the SNPs in your own whole-genome sequence: alignment, variant calling with DeepVariant, QC thresholds that catch real failures, annotation, and the queries worth running first.
A step-by-step pipeline from raw FASTQ to a filtered, benchmarked VCF for a single human genome, with the tool choices, parameters, and quality checks we would use.
A practical comparison of DeepVariant, GATK HaplotypeCaller, bcftools mpileup, Strelka2, and Clair3 for calling SNPs from your own whole-genome data, with commands, benchmarks, and the failure modes that matter.
A step-by-step guide from raw FASTQ to a filtered, benchmarked and annotated single-sample VCF. Covers the tools, flags and quality numbers.
A working end-to-end guide to going from FASTQ to a filtered, benchmarked VCF on a personal 30x human genome, with the specific tools, flags, reference files, and failure modes we would use.