Tag: quality-control

A practical guide to QUAL, hard filters, and genotype masking with bcftools filter and bcftools view, including the failure modes that silently drop variants from your own genome.

A step-by-step method for deciding whether a failing FastQC module means your library is broken, your sequencer had a bad run, or the plot is simply behaving as designed.

A step-by-step bioinformatics workflow for taking bulk RNA sequencing FASTQs from your own blood sample through quantification, quality control, normalization, and interpretation, with the tools, flags, and failure modes named.

A practical walkthrough of working with raw sequencing reads: reading the format, checking quality, aligning to a reference, and knowing when the data is good enough to call variants.

A working guide to turning raw RNA sequencing reads from your own blood into quality-controlled gene and transcript quantifications, with the specific tools, flags, and reference files we would use, plus the failure modes that silently corrupt results.

Read depth in RNA-seq is the number of reads assigned to your sample and, per gene, the number of reads supporting each transcript. This page explains how to compute it from your own files, why 30x means nothing here, and what depth to ask for.

A practical trimming workflow for personal whole-genome and RNA-seq FASTQs: how to find the real adapter, which tool and flags we use, how gently to trim, and how to verify that trimming helped rather than shifted your expression estimates.

A practical guide to computing principal components from RNA-seq counts in R. Covers the transform, gene selection and what each component means.