SEACR is intended to call peaks and enriched regions from sparse CUT&RUN or chromatin profiling data in which background is dominated by "zeroes" (i.e. regions with no read coverage). It requires R (https://www.r-project.org) and Bedtools (https://bedtools.readthedocs.io/en/latest/) to be available in your path, and it requires bedgraphs from paired-end sequencing as input, which can be generated from read pair BED files (i.e. BED coordinates reflecting the 5' and 3' termini of each read pair) using bedtools genomecov with the "-bg" flag, or alternatively from name-sorted paired-end BAM files as described in "Preparing input bedgraph files" below.
A description of the method can be found in the following manuscript:
Meers MP, Bryson TD, Henikoff S. A streamlined protocol and analysis pipeline for CUT&RUN chromatin profiling. bioRxiv doi: https://doi.org/10.1101/569129
Direct link: https://www.biorxiv.org/content/10.1101/569129v1
bash SEACR_1.0.sh experimental bedgraph [control bedgraph | numeric threshold] ["norm" | "non"] ["union" | "AUC"] output prefix
Field 1: Target data bedgraph file in UCSC bedgraph format (https://genome.ucsc.edu/goldenpath/help/bedgraph.html) that omits regions containing 0 signal.
Field 2: Control (IgG) data bedgraph file to generate an empirical threshold for peak calling. Alternatively, a numeric threshold n between 0 and 1 returns the top n fraction of peaks based on total signal within peaks.
Field 3: “norm” denotes normalization of control to target data, “non” skips this behavior. "norm" is recommended unless experimental and control data are already rigorously normalized to each other (e.g. via spike-in).
Field 4: “union” forces implementation of a maximum signal threshold in addition to the total signal threshold, and corresponds to the “union” mode described in the text, whereas “AUC” avoids this behavior, and corresponds to “AUC only” mode.
Field 5: Output prefix
Bedgraph files should reflect density across read pairs rather than individual reads. If starting from BAM files, we recommend converting to paired end BED files using bedtools bamtobed with the -bedpe flag, then selecting the 5' and 3' coordinates of the read pair to generate a new BED3 file, and finally converting that file to a bedgraph using bedtools genomecov.
<output prefix>.auc.threshold.merge.bed (BED file of enriched regions)
<chr> <start> <end> <total signal> <max signal> <max signal region>
Field 1: Chromosome
Field 2: Start coordinate
Field 3: End coordinate
Field 4: Total signal contained within denoted coordinates
Field 5: Maximum bedgraph signal attained at any base pair within denoted coordinates
Field 6: Region representing the farthest upstream and farthest downstream bases within the denoted coordinates that are represented by the maximum bedgraph signal
bash SEACR_1.0.sh target.bedgraph IgG.bedgraph norm AUC output
Calls enriched regions in target data using normalized IgG control track with AUC threshold
bash SEACR_1.0.sh target.bedgraph IgG.bedgraph non union output
Calls enriched regions in target data using non-normalized IgG control track with AUC and max signal thresholds
bash SEACR_1.0.sh target.bedgraph 0.01 non AUC output
Calls enriched regions in target data by selecting the top 1% of regions by AUC