CisGenome

CisGenome analyzes genome-wide chromatin immunoprecipitation (ChIP) data to identify protein-DNA binding sites and characterize associated sequence motifs for genomic interpretation.

Key Features:

• Data Normalization and Peak Detection: Provides methods for normalizing ChIP data and detecting peaks to identify regions of DNA bound by proteins of interest.
• False Discovery Rate Computation: Includes algorithms to compute false discovery rate for assessing statistical significance of identified binding sites.
• Gene-Peak Association: Associates detected peaks with nearby genes to aid genomic interpretation.
• Sequence and Motif Analysis: Performs sequence analysis and motif discovery to identify DNA motifs within binding regions.
• ChIP-chip and ChIP-seq Compatibility: Implements methods for analyzing both ChIP-chip (microarray) and ChIP-seq (massively parallel sequencing) datasets.
• Support for Negative-Control Evaluation: Enables evaluation of ChIP-seq analyses with or without negative control samples.

Scientific Applications:

• Comparative ChIP-chip versus ChIP-seq analysis: Facilitates comparative analyses of ChIP-chip and ChIP-seq datasets for transcription factors including NRSF/REST.
• Assessment of control strategies: Supports studies evaluating ChIP-seq analysis pipelines with or without negative control samples to assess reliability.
• Motif discovery in regulatory regions: Enables discovery of novel motifs in regions bound by regulatory proteins such as Nanog and Sox2.

Methodology:

Performs data normalization, peak detection, false discovery rate computation, gene-peak association, sequence analysis and motif discovery for ChIP-chip and ChIP-seq datasets, with options to analyze datasets with or without negative control samples.