EcTracker

EcTracker detects and characterizes ectopic gene expression and cell- or tissue-specific transcripts in single-cell RNA sequencing (scRNA-seq) datasets to support analysis of aberrant and context-specific transcriptional programs.

Key Features:

• CellEnrich: Identifies genes specifically enriched in particular cell types within scRNA-seq datasets.
• TissueEnrich: Detects tissue-specific gene expression patterns across sampled cells.
• Ectopic Expression Analysis: Identifies genes activated outside their normal regulatory contexts, including those arising from genomic alterations or pathological states.
• Regulon Analysis: Pinpoints transcription factors that regulate selected gene signatures and aids mapping of regulatory networks.
• Processing Speed and Add-on Modules: Implements rapid processing and supports modular add-on components to extend analytical functionality.

Scientific Applications:

• Analysis of genomic perturbations (CRISPRi): Detects ectopic and altered expression signatures resulting from CRISPR interference perturbations.
• Pathological state investigation: Identifies aberrant gene activation patterns associated with disease contexts.
• Reanalysis of developmental datasets: Reassesses datasets such as human embryonic stem cell differentiation into endoderm with SMAD2 knockout to resolve ambiguities in cellular identity and gene expression.

Methodology:

EcTracker leverages large-scale scRNA-seq data to perform integrative analyses that quantitatively assess cell- and tissue-specific transcripts, qualitatively identify ectopic expressions, and perform regulon analysis to map transcriptional regulatory networks.