Building a CNV Analysis Pipeline from Your Own Whole-Genome Data
A practical walkthrough for calling and filtering copy number variants from a 30x whole-genome CRAM, with the limits of what each caller can see.
5 posts
A practical walkthrough for calling and filtering copy number variants from a 30x whole-genome CRAM, with the limits of what each caller can see.
A working pipeline that turns raw CNV calls from a personal genome into an annotated and prioritized table, with visual confirmation.
A working pipeline for calling deletions, duplications, inversions, and insertions from your own short-read whole-genome sequencing data, including which callers to run, how to merge them, and how to judge whether a call is real.
Genome mapping means at least four different things: historical linkage maps, aligning your reads to a reference, optical genome mapping for structural variants, and the colloquial sense of getting your genome sequenced. Here is how to tell them apart, what each costs, and the pipeline we would run on your own data.
What structural variants are, which callers to run on short-read and long-read whole-genome data, the flags that matter, and how to tell a real call from an alignment artifact.