cLoops2: full stack analysis tool for chromatin interactions
Allocate an interactive session and run the program.
Sample session (user input in bold):
[user@biowulf]$ sinteractive [user@cn4274 ~]$ module load cloops2 [+] Loading cloops2 0.0.4 on cn4326 [+] Loading singularity 3.10.5 on cn4326
Execute cLoops2
[user@cn4274 ~]$ cLoops2 -h
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,
contact matrix or virtual 4C signal)
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.
Annotate an SV:
[user@cn4338] cp -a /usr/local/apps/duphold/0.2.3/test_data . [user@cn4338 test_data]$ duphold \ --threads 4 \ --vcf sparse_in.vcf \ --bam sparse.cram \ --fasta sparse.fa \ --output output.bcf #To view output, load samtools and view with bcftools [user@cn4338 test_data] module load samtools [user@cn4338 test_data] bcftools view test-out.bcf ##fileformat=VCFv4.2 ... ##bcftools_viewVersion=1.4-19-g1802ff3+htslib-1.4-29-g42bfe70 ##bcftools_viewCommand=view CHM1_CHM13/full.37d5.vcf.gz; Date=Mon Sep 24 13:48:04 2018 ... ##bcftools_viewVersion=1.17+htslib-1.17 ##bcftools_viewCommand=view test-out.bcf; Date=Thu May 25 12:49:34 2023 #CHROM POS ID REF ALT QUAL FILTER INFO FORMAT Eluc-CR2.F NW_017858824.1 135118 72454 N DEL 5875.46 . SVTYPE=DEL;END=135332;CIPOS=0,0;CIEND=0,0;CIPOS95=0,0;CIEND95=0,0;GCF=0.306977 GT:DP:DHFC:DHFFC:DHBFC:DHSP 0/1:200:1.91667:0.597403:1.76923:0
| For more information on pre and post processing, please visit the cLoops2 Github |