Catchitt

Catchitt is a collection of tools for predicting cell type-specific binding regions of transcription factors (TFs) based on binding motifs and chromatin accessibility assays. The initial implementation of this methodology has been one of the winning approaches of the ENCODE-DREAM challenge ([1]) and is described in a preprint (https://www.biorxiv.org/content/early/2017/12/06/230011 doi: 10.1101/230011). The implementation in Catchitt has been streamlined and slightly simplified to make its application more straight-forward. Specifically, we reduced the set of chromatin accessibility features to the most important ones, we simplified the sampling strategy of initial negative examples in the training step, and we omitted quantile normalization of chromatin accessibility features.

Chatchitt tools

Chatchitt comprises five tools for the individual steps of the pipeline. The tool "labels" computes labels for genomic regions from "conservative" (i.e., IDR-thresholded) and "relaxed" ChIP-seq peaks. The tool "access" computes chromatin accessibility features from DNase-seq or ATAC-seq data, either based on fold-enrichment tracks in Bigwig format (e.g., MACS output) or based on SAM/BAM files of mapped reads. The tool "motif" computes motif-based features from genomic sequence and PWMs in Jaspar or HOCOMOCO format, or motif models from Dimont, including Slim models. The tool "itrain" performs iterative training of a series of classifiers based on labels, chromatin accessibility features, and motif features. The tool "predict" predicts binding probabilities of genomic regions based on trained classifiers and feature files. The feature files may either be measured on the training cell type (e.g., other chromosomes, "within cell type" case) or on a different cell type.

Availability

We provide Catchitt as a pre-compiled JAR file and also publish its sources under GPL 3. For compiling Chatchitt from source files, Jstacs (v. 2.3 and later) and the corresponding external libraries are required.

• JAR download
• Source download and Jstacs Downloads

Usage

Catchitt can be started by calling

java -jar Catchitt.jar

on the command line. This lists the names of the available tools with a short description:

Available tools:

	access - Chromatin accessibility
	motif - Motif scores
	labels - Derive labels
	itrain - Iterative Training
	predict - Prediction

Syntax: java -jar EncodeDREAM.jar <toolname> [<parameter=value> ...]

Further info about the tools is given with
	java -jar EncodeDREAM.jar <toolname> info

Tool parameters are listed with
	java -jar EncodeDREAM.jar <toolname>

Tools

Derive labels

Derive labels computes labels for genomic regions based on ChIP-seq peak files. The input ChIP-seq peak files must be provided in narrowPeak format and may come in 'conservative', i.e., IDR-thresholded, and 'relaxed' flavors. In case only a single peak file is available, both of the corresponding parameters may be set to this one peak file. The parameter for the bin width defines the resolution of genomic regions that is assigned a label, while the parameter for the region width defines the size of the regions considered. If, for instance, the bin width is set to 50 and the region width to 100, regions of 100 bp shifted by 50 bp along the genome are labeled. The labels assigned may be 'S' (summit) is the current bin contains the annotated summit of a conservative peak, 'B' (bound) if the current region overlaps a conservative peak by at least half the region width, 'A' (ambiguous) if the current region overlaps a relaxed peak by at least 1 bp, or 'U' (unbound) if it overlaps with none of the peaks. The output is provided as a gzipped file 'Labels.tsv.gz' with columns chromosome, start position, and label. This output file together with a protocol of the tool run is saved to the specified output directory.

Derive labels may be called with

java -jar Catchitt.jar labels

and has the following parameters

name	comment	type
c	Conservative peaks (NarrowPeak file containing the conservative peaks)	FILE
r	Relaxed peaks (NarrowPeak file containing the relaxed peaks)	FILE
f	FAI of genome (FastA index file of the genome)	FILE
b	Bin width (The width of the genomic bins considered, valid range = [1, 10000], default = 50)	INT
rw	Region width (The width of the genomic regions considered for overlaps, valid range = [1, 10000], default = 50)	INT
outdir	The output directory, defaults to the current working directory (.)	STRING

Example:

java -jar Catchitt.jar labels 

name	comment	type
d	Data source (The format of the input file containing the coverage information, range={BAM/SAM, Bigwig}, default = BAM/SAM) Parameters for selection "BAM/SAM": i Input SAM/BAM (The input file containing the mapped DNase-seq/ATAC-seq reads) FILE Parameters for selection "Bigwig": i Input Bigwig (The input file containing the mapped DNase-seq/ATAC-seq reads) FILE f FastA index (The genome index) FILE
b	Bin width (The width of the genomic bins considered)	INT
outdir	The output directory, defaults to the current working directory (.)	STRING

name	comment	type
m	Motif model (The motif model in Dimont, HOCOMOCO, or Jaspar format, range={Dimont, HOCOMOCO, Jaspar}, default = Dimont) Parameters for selection "Dimont": d Dimont motif (Dimont motif model description) FILE Parameters for selection "HOCOMOCO": h HOCOMOCO PWM (PWM from the HOCOMOCO database) FILE Parameters for selection "Jaspar": j Jaspar PFM (PFM in Jaspar format) FILE
g	Genome (Genome as FastA file)	FILE
f	FAI of genome (FastA index file of the genome)	FILE
b	Bin width (The width of the genomic bins considered)	INT
l	Low-memory mode (Use slower mode with a smaller memory footprint, default = false)	BOOLEAN
outdir	The output directory, defaults to the current working directory (.)	STRING

name	comment	type
a	Accessibility (File containing accessibility features)	FILE
m	Motif (File containing motif features)	FILE
l	Labels (File containing the labels)	FILE
f	FAI of genome (FastA index file of the genome)	FILE
b	Bin width (The width of the genomic bins, valid range = [1, 1000], default = 50)	INT
n	Number of bins (The number of adjacent bins, valid range = [1, 20], default = 5)	INT
abb	Aggregation: bins before (The number of bins before the current one considered in the aggregation, valid range = [1, 20], default = 1)	INT
aba	Aggregation: bins after (The number of bins after the current one considered in the aggregation, valid range = [1, 20], default = 4)	INT
i	Iterations (The number of iterations of the interative training, valid range = [1, 20], default = 5)	INT
t	Training chromosomes (Training chromosomes, separated by commas, OPTIONAL)	STRING
itc	Iterative training chromosomes (Chromosomes with predictions in iterative training, separated by commas, OPTIONAL)	STRING
p	Percentile (Percentile of the prediction scores of positives used as threshold in iterative training, valid range = [0.0, 1.0], default = 0.99)	DOUBLE
outdir	The output directory, defaults to the current working directory (.)	STRING

name	comment	type
c	Classifiers (The classifiers trained by iterative training)	FILE
a	Accessibility (File containing accessibility features)	FILE
m	Motif (File containing motif features)	FILE
f	FAI of genome (FastA index file of the genome)	FILE
p	Prediction chromosomes (Prediction chromosomes, separated by commas, OPTIONAL)	STRING
abb	Aggregation: bins before (Number of bins before the current one considered for aggregation., OPTIONAL)	INT
aba	Aggregation: bins after (Number of bins after the current one considered for aggregation., OPTIONAL)	INT
n	Number of classifiers (Use only the first k classifiers for predictions., OPTIONAL)	INT
outdir	The output directory, defaults to the current working directory (.)	STRING