Overview

OmicVerse provides a complete bulk RNA-seq FASTQ-to-count-matrix pipeline via the ov.alignment module. This skill covers:

SRA data acquisition: prefetch and fqdump (fasterq-dump wrapper), or parallel_fastq_dump (multi-threaded .lite.1 → paired FASTQ)
Quality control: fastp for adapter trimming and QC reports
Path A — alignment-based: STAR aligner with auto-index building + featureCount (subread featureCounts wrapper) for gene quantification. Produces sorted BAMs and a gene × sample count DataFrame. Use when transcript structure / splicing matters or when downstream tools expect BAMs.
Path B — alignment-free (kb-python technology='BULK'): ov.alignment.single.ref builds a kallisto index + t2g + cDNA once per genome; ov.alignment.count(technology='BULK', ...) quantifies each sample directly to gene counts. Much faster than STAR + featureCounts on the same machine, with comparable gene-level accuracy for most DE use cases. This is the t_mapping_kbpython walkthrough.
DE handoff: wiring per-sample outputs into ov.bulk.pyDEG (DESeq2 / edgeR / limma) → volcano plot.

All functions share a common CLI infrastructure (_cli_utils.py) that handles tool resolution, auto-installation via conda/mamba, parallel execution, and streaming output.

Out of scope: single-cell kb-python (technology='10XV2', '10XV3', velocity workflows). See single-cell-kb-alignment for that.

bulk-fastq-quantification

Overview

Instructions