Pycallingcards

Pycallingcards analyzes Calling Cards data to identify transcription factor (TF) binding events captured by transposon insertions and to relate TF binding to mRNA expression.

Key Features:

• CCcaller and MACCs peak callers: Implements CCcaller and MACCs algorithms to improve identification of TF binding sites from Calling Cards data.
• Single-cell and bulk support: Processes both single-cell and bulk Calling Cards datasets for TF binding analysis.
• Detection of transient TF binding via transposons: Analyzes transposon insertion patterns that record transient TF–DNA interactions.
• Motif finding and comparative analysis: Supports motif discovery and comparative analyses with genomic datasets such as RNA-seq and ChIP-seq.
• Temporal integration and mRNA linkage: Integrates TF binding events across time points and links TF insertions to mRNA expression in single-cell data.
• Cross-species applicability: Applicable to Calling Cards datasets from multiple species.

Scientific Applications:

• Transcriptional program exploration: Enables analysis of relationships between TF binding and gene expression to explore transcriptional programs.
• Reanalysis of biological datasets: Has been applied to mouse cortex and glioblastoma datasets to uncover cell-type-specific binding sites and potential sex-linked TF regulators.

Methodology:

Captures transient TF–DNA interactions using transposons that are read out later, enabling simultaneous measurement of TF binding and mRNA expression from single-cell Calling Cards data and integration of binding events across time points without cell purification.