htsint

htsint integrates high-throughput sequencing data with functional annotations by computing functional distances using ontology relationships and applying spectral clustering to define gene modules for gene set enrichment analyses.

Key Features:

• Implementation: Implemented as a Python-based package.
• Annotation Compilation: Compiles annotation information from one or more taxa to establish functional context across a specified gene space.
• Functional Distance Calculation: Calculates functional distances among genes within the specified gene space using ontology relationships and compiled annotations.
• Spectral Clustering for Functional Modules: Applies spectral clustering to the functional distance matrix to partition genes into functional modules ranging from pathways to whole genomes.
• Integration with Gene Set Enrichment Frameworks: Generates gene sets that can be tested for enrichment or conditional differences using commonly available gene set enrichment packages.

Scientific Applications:

• RNA-Seq Analysis: Facilitates group-level analysis of genes and variants to integrate annotations and detect coordinated changes between experimental conditions in RNA-Seq studies.
• Pathway and Genome Studies: Supports analysis of targeted gene lists or entire genomes for pathway-level and genome-wide functional investigations.

Methodology:

Compile annotation information across taxa; calculate functional distances among genes using ontology relationships and annotations; apply spectral clustering to partition genes into functional modules; test resulting gene sets for enrichment or conditional differences using compatible gene set enrichment packages.