htseqcount

htseqcount counts sequencing reads overlapping genomic features to quantify gene expression from RNA-Seq alignments for downstream differential expression analyses.

Key Features:

• Integration with HTSeq library: Uses HTSeq Python library parsers and classes to represent genomic coordinates, sequences, sequencing reads, alignments, gene model information, and variant calls.
• Read counting: Computes counts of sequencing reads that overlap genomic features, such as genes, for RNA-Seq preprocessing.
• Input format support: Accepts alignment files in SAM format and feature annotations in GFF format.
• Genomic-coordinate querying: Performs overlap and coordinate-based queries using HTSeq data structures for feature assignment.
• Programmatic API for custom workflows: Provides data structures and parsers that enable development of custom scripts for nonstandard HTS workflows.

Scientific Applications:

• RNA-Seq preprocessing for differential expression: Produces gene-level read counts used as input for differential expression analysis.
• Gene expression quantification: Enables measurement of gene expression levels from mapped RNA-Seq reads.
• Differential expression studies: Supports identification of differentially expressed genes across conditions or treatments.
• Molecular and disease research: Facilitates analyses that inform gene function, regulatory mechanisms, and disease pathology from RNA-Seq data.

Methodology:

htseqcount takes an alignment file in SAM format and a feature file in GFF format, parses them with HTSeq data structures, and counts reads mapping to each genomic feature (e.g., genes) via coordinate-based overlap queries.