SBPC is a peak caller for genomic data that implements a Bayesian statistical framework to evaluate the probabilities of regions being peaks. It is designed for CUT&TAG/CUT&RUN sequencing data and provides posterior probabilities for each detected peak region.
sbpc -b <sample>.bam -c <control>.bam > <sample>_peaks.bed
curl -L https://github.com/jakevc/sbpc/releases/download/v0.1.3/sbpc-v0.1.3-x86_64-unknown-linux-gnu.tar.gz | tar xz
sudo mv sbpc /usr/local/bin/curl -L https://github.com/jakevc/sbpc/releases/download/v0.1.3/sbpc-v0.1.3-x86_64-apple-darwin.tar.gz | tar xz
sudo mv sbpc /usr/local/bin/curl -L https://github.com/jakevc/sbpc/releases/download/v0.1.3/sbpc-v0.1.3-aarch64-apple-darwin.tar.gz | tar xz
sudo mv sbpc /usr/local/bin/cargo install sbpcgit clone https://github.com/jakevc/sbpc.git
cd sbpc
cargo build --releaseThe binary will be available at target/release/sbpc.
You can also run SBPC using Docker, which avoids the need to install system dependencies:
# Pull the latest image
docker pull ghcr.io/jakevc/sbpc:latest
# Run SBPC with Docker
docker run --rm -v /path/to/data:/data ghcr.io/jakevc/sbpc:latest -b /data/sample.bam -c /data/control.bam -o /data/output_prefixThis approach eliminates issues with glibc dependencies across di 8000 fferent platforms, making it easier to use SBPC regardless of your operating system.
SBPC requires input BAM files to be coordinate-sorted and indexed. You can prepare your BAM files using samtools:
samtools sort -o sorted.bam input.bam
samtools index sorted.bamBoth the sample and control BAM files must be sorted and have a corresponding .bai index file in the same directory.
Usage: sbpc [OPTIONS] --bam <BAM>
Options:
-b, --bam <BAM> Input BAM file (must be paired-end reads)
-c, --control <CONTROL> Input BAM file with control signal to be normalized (e.g. IgG, Input)
-s, --chromsize <CHROMSIZE> Chromosome sizes for the genome if not found in the bam header
-m, --mdist <MDIST> Merge peaks within <mdist> base pairs [default: 1000]
-r, --minreads <MINREADS> Test genome bins with at least <minreads> read pairs [default: 15]
-p, --posterior-threshold <THRESHOLD> Define posterior probability threshold for peak significance [default: 0.95]
-t, --step <STEP> Bin size for coverage bins [default: 200]
-w, --minwidth <MINWIDTH> Minimum width (bp) of a peak [default: 150]
-v, --version Print the current SBPC version
--broad Run SBPC on broad marks (--step 5000)
--verbose Run SBPC in verbose mode
-h, --help Print help
- Peaks are always printed in BED format to stdout.
- Metrics are printed as JSON to stdout by default. To also write metrics to a file (e.g., _sbpc.json), use the
--metrics-fileflag.
MIT