hacksig

hacksig computes single-sample enrichment scores for gene expression signatures to support analysis of cancer transcriptomics.

Key Features:

• R implementation: Implemented as an R package for computing gene expression signature scores.
• Unified framework: Integrates multiple single-sample enrichment methods to apply signatures consistently across datasets.
• Tidy output: Produces signature scores in a tidy data format suitable for downstream analysis in R.
• Curated gene signatures: Includes manually curated gene signatures derived from cancer transcriptomics literature.

Scientific Applications:

• Cancer transcriptomics analysis: Enables computation of per-sample signature scores for studies of tumor biology using transcriptomic data.
• Clinical outcome prediction: Supports use of gene expression signatures for predicting patient outcomes from transcriptomic profiles.
• Therapeutic target identification: Facilitates application of curated signatures to identify potential therapeutic targets in cancer datasets.

Methodology:

Implemented in R and integrates various single-sample enrichment methods to compute per-sample gene expression signature scores and output them in a tidy format.