Metadata-Version: 2.1
Name: cLoops2
Version: 0.0.2
Summary: Loop-calling and peak-calling for sequencing-based interaction data, including related analysis utilities.
Home-page: https://github.com/YaqiangCao/cLoops2
Author: Yaqiang Cao
Author-email: caoyaqiang0410@gmail.com
License: UNKNOWN
Project-URL: Source, https://github.com/YaqiangCao/cLoops2
Description: ## cLoops2: full stack analysis tool for enriched chromatin interaction data 
        
        -------
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        ## Introduction
        cLoops2 is an extension of our previous work, [cLoops](https://github.com/YaqiangCao/cLoops). From loop-calling based on assumption-free clustering to a full suite of analysis tools for 3D genomic interaction data, cLoops2 has been adapted specifically for data such as Hi-Trac/Trac-looping, for which interactions are enriched over the genome through experimental steps. cLoops2 still supports Hi-C -like data, of which the interaction signals are evenly distributed at enzyme cutting sites.  The changes from cLoops to cLoops2 are designed to address challenges around aiming for higher resolutions with the next-generation of genome architecture mapping technologies. 
        
        cLoops2 is designed with respect reference to [bedtools](https://bedtools.readthedocs.io/en/latest/) and [Samtools](http://www.htslib.org/) for command-line style programming. If you have experience with them, you will find cLoops2 easy and efficient to use and combine commands, integrate as steps in your processing pipeline. 
        
        Please refer to our in-preparing [Hi-Trac method manuscript]() or [cLoops2 manuscript]() for what cLoops2 can do and show. 
        
        If you use cLoops2 in your research (the idea, the algorithm, the analysis scripts or the supplemental data), please give us a star on the GitHub repo page and cite our paper as follows:    
        
        Preprint bioRxiv: Yaqiang Cao et al. "Full-stack analysis for enriched 3D genomic interaction data with cLoops2"   
        
        
        ------
        ------
        ## cLoops2 Main Functions
        Run ***cLoops2*** or ***cLoops2 -h*** can show the main functions of cLoops2 with short descriptions and examples.     
        
        ```
        An enhanced, accurate and flexible peak/domain/loop-calling and analysis tool 
        for 3D genomic interaction data.
        
        Use cLoops2 sub-command -h to see detail options and examples for sub-commands.
        Available sub-commands are: 
            qc: quality control of BEDPE files before analysis.
            pre: preprocess input BEDPE files into cLoops2 data.
            update: update cLoops2 data files locations.
            combine: combine multiple cLooops2 data directories.
            dump: convert cLoops2 data files to others (BEDPE, HIC, washU, bedGraph and
                  contact matrix)
            estEps: estimate eps using Gaussian mixture models or k-distance plot.
            estRes: estimate reasonable contact matrix resolution based on signal 
                    enrichment.
            estDis: estimate significant interactions distance range.
            estSat: estimate sequencing saturation based on contact matrix.
            estSim: estimate similarities among samples based on contact matrix.
            filterPETs: filter PETs based on peaks, loops, singleton mode or knn mode. 
            samplePETs: sample PETs according to specific target size.
            callPeaks: call peaks for ChIP-seq, ATAC-seq, ChIC-seq and CUT&Tag or the 
                       3D genomic data such as Trac-looping, Hi-Trac, HiChIP and more.
            callLoops: call loops for 3D genomic data.
            callDiffLoops: call differentially enriched loops for two datasets. 
            callDomains: call domains for 3D genomic data. 
            plot: plot the interaction matrix, genes, view point plot, 1D tracks, 
                  peaks, loops and domains for a specific region. 
            montage: analysis of specific regions, producing Westworld Season 3 -like 
                     Rehoboam plot. 
            agg: aggregated feature analysis and plots, features can be peaks, view 
                 points, loops and domains.
            quant: quantify peaks, loops and domains.
            anaLoops: anotate loops for target genes.
            findTargets: find target genes of genomic regions through networks from 
                         anaLoops.
        
        Examples:
            cLoops2 qc -f trac_rep1.bedpe.gz,trac_rep2.bedpe,trac_rep3.bedpe.gz \
                       -o trac_stat -p 3
            cLoops2 pre -f ../test_GM12878_chr21_trac.bedpe -o trac
            cLoops2 update -d ./trac
            cLoops2 combine -ds ./trac1,./trac2,./trac3 -o trac_combined -keep 1
            cLoops2 dump -d ./trac -o trac -hic
            cLoops2 estEps -d trac -o trac_estEps_gmm -p 10 -method gmm
            cLoops2 estRes -d trac -o trac_estRes -p 10 -bs 25000,5000,1000,200
            cLoops2 estDis -d trac -o trac -plot -bs 1000 
            cLoops2 estSim -ds Trac1,Trac2 -o trac_sim -p 10 -bs 2000 -m pcc -plot
            cLoops2 filterPETs -d trac -peaks trac_peaks.bed -o trac_peaksFiltered -p 10
            cLoops2 samplePETs -d trac -o trac_sampled -t 5000000 -p 10
            cLoops2 callPeaks -d H3K4me3_ChIC -bgd IgG_ChIC -o H3K4me3_cLoops2 -eps 150 \
                              -minPts 10
            cLoops2 callLoops -d Trac -eps 200,500,1000 -minPts 3 -filter -o Trac -w -j \
                              -cut 2000
            cLoops2 callLoops -d HiC -eps 1000,5000,10000 -minPts 10,20,50,100 -w -j \
                              -trans -o HiC_trans 
            cLoops2 callDiffLoops -tloop target_loop.txt -cloop control_loop.txt \
                                  -td ./target -cd ./control -o target_diff
            cLoops2 callDomains -d trac -o trac -bs 10000 -ws 200000
            cLoops2 plot -f test/chr21-chr21.ixy -o test -bs 500 -start 34840000 \
                         -end 34895000 -triu -1D -loop test_loops.txt -log \
                         -gtf hg38.gtf -bws ctcf.bw -beds enhancer.bed
            cLoops2 montage -f test/chr21-chr21.ixy -o test -bed test.bed
            cLoops2 agg -d trac -loops trac.loop -peaks trac_peaks.bed \
                        -domains hic_domains.bed -bws CTCF.bw,ATAC.bw -p 20 -o trac 
            cLoops2 quant -d trac -peaks trac_peaks.bed -loops trac.loop \
                          -domains trac_domain.txt -p 20 -o trac
            cLoops2 anaLoops -loops test_loop.txt -gtf gene.gtf -net -o test
            cLoops2 findTargets -net test_ep_net.sif -tg test_targets.txt \
                                -bed GWAS.bed -o test 
            More usages and examples are shown when run with cLoops2 sub-command -h.
            
        
        optional arguments:
          -h, --help  show this help message and exit
          -d PREDIR   Assign data directory generated by cLoops2 pre to carry out analysis. 
          -o FNOUT    Output data directory / file name prefix, default is cLoops2_output.
          -p CPU      CPUs used to run the job, default is 1, set -1 to use all CPUs
                      available. Too many CPU could cause out-of-memory problem if there are
                      too many PETs.
          -cut CUT    Distance cutoff to filter cis PETs, only keep PETs with distance
                      >=cut. Default is 0, no filtering.
          -mcut MCUT  Keep the PETs with distance <=mcut. Default is -1, no filtering.
          -v          Show cLoops2 verison number and exit.
          ---         Following are sub-commands specific options. This option just show
                      version of cLoops2.
        
        Bug reports are welcome and can be put as issue at github repo or sent to 
        caoyaqiang0410@gmail.com or yaqiang.cao@nih.gov. Thank you.
        ```
        
        --------
        --------
        ## cLoops2 citations
        
        --------
        --------
        ## cLoops2 updates
        
        
Keywords: peak-calling loop-calling Hi-Trac interaction visualization
Platform: UNKNOWN
Classifier: Environment :: Console
Classifier: Operating System :: MacOS :: MacOS X
Classifier: Operating System :: POSIX
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Python: >=3
Description-Content-Type: text/markdown
