SigFuge

SigFuge identifies genomic loci with differential transcription patterns across cohorts of RNA-seq data, enabling unsupervised discovery of alternative splicing and isoform expression differences.

Key Features:

• Unsupervised discovery: Operates without predefined class labels to identify transcriptionally altered loci across RNA-seq samples.
• Integration of clustering and hypothesis testing: Combines clustering techniques with hypothesis testing to detect genes exhibiting alternative splicing or isoform expression differences.
• Application to large cohorts: Has been applied to large RNA-seq cohorts such as The Cancer Genome Atlas, including 177 lung and 279 head and neck squamous cell carcinoma samples.
• Identification of biomarkers: Has identified cases of differential isoform usage including the tumor suppressor gene CDKN2A, frequently inactivated in lung squamous cell tumors.

Scientific Applications:

• Cancer genomics: Enables unsupervised screening for transcriptionally altered loci in cancer cohorts to support discovery of molecular alterations.
• Biomarker and target discovery: Supports identification of novel biomarkers and potential therapeutic targets through detection of differential transcription patterns.
• Alternative splicing and isoform analysis: Facilitates study of alternative splicing events and isoform expression differences across samples.

Methodology:

Performs unsupervised screening of RNA-seq loci by combining clustering techniques with hypothesis testing to detect alternative splicing and isoform expression differences.