SICER

SICER, which stands for Spatial Clustering for Identification of ChIP-Seq Enrichment Regions, is a software package designed to analyze ChIP-Seq data and identify regions of genomic enrichment. It is particularly suited for detecting broad enrichment domains often associated with histone modifications, as opposed to the narrow, sharp peaks typically produced by transcription factors.

The method works by partitioning the genome into fixed-size windows and counting reads within each window to assess enrichment. After normalizing for sequencing depth and potential background signals, SICER identifies windows that show significant enrichment relative to a control sample. These enriched windows are then joined into larger regions, or islands, using a spatial clustering approach that accounts for the proximity of neighboring enriched windows. The resulting islands are filtered by user-defined criteria, such as minimum length and enrichment score, and can be assigned statistical measures like p-values and false discovery rates to control for multiple testing.

Input requirements typically include aligned reads (for example, BAM files) and, optionally, a control sample (input DNA) to improve background estimation. Output consists of a list of enrichment islands with genomic coordinates and associated statistics, suitable for downstream visualization or downstream analyses such as overlap with gene annotations or other genomic features.

SICER is commonly used in studies of histone modifications and chromatin states where broad domains are of interest. It is distributed as an open-source software package and is available for researchers as a command-line tool, often accompanied by documentation and example datasets. While effective for broad enrichment, SICER may be less appropriate for detecting sharp, narrow peaks where alternative peak-calling methods are more suitable.