chromVAR

chromVAR quantifies per-cell deviations in chromatin accessibility associated with DNA sequence motifs and genomic annotations from single-cell ATAC-seq (scATAC-seq) data to infer regulatory variation while controlling for technical biases.

Key Features:

• Sparse Data Analysis: Targets the sparse nature of scATAC-seq data by aggregating signal across peaks that share motifs or annotations to detect accessibility changes.
• Motif and Annotation-Based Estimation: Estimates changes in accessibility by analyzing peaks grouped by DNA sequence motifs or genomic annotations.
• Technical Bias Control: Incorporates methods to control for technical biases in single-cell epigenomic datasets to distinguish biological variation from experimental artifacts.
• Clustering Capabilities: Enables clustering of scATAC-seq profiles to identify cell populations with distinct chromatin-accessibility landscapes.
• Motif Characterization: Supports both known and de novo motif analysis to associate transcription factor binding sites with accessibility variation.

Scientific Applications:

• Transcription Factor Activity Profiling: Infers transcription factor activity from motif-associated chromatin accessibility deviations.
• Cellular Heterogeneity Studies: Identifies distinct cell types or states by clustering scATAC-seq profiles based on accessibility variation.
• Regulatory Element Discovery: Facilitates discovery of known and novel regulatory elements and transcription factor binding sites from single-cell accessibility patterns.

Methodology:

Computes per-cell deviations in chromatin accessibility for sets of peaks grouped by DNA sequence motifs or genomic annotations, corrects for technical biases, supports known and de novo motif analysis, and performs clustering of scATAC-seq profiles; implemented as an R package.