In order to make installation easier, we write a script, download.sh, run with help instruction. This script could get access to the required data, such as bowtie index for hg19 and mm9, and all stable dependent program. basicly using the command below:
we sample down 1000 reads for testing the ChiLin installation state the test files are in the tests folder
To run the tests, you need simply need to run:
Chilin gen -s hg19
run:
ChiLin run -c ChiLin.conf -t TF
This should be run all dependent program with dependent data.
Here we recommend a dataset from GSE30624 for testing whole pipeline with QC report generated.
Here is one of the simpest ChiLin_ workflow you can make.
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user = testuser
id = testid
time = 2102xxx
species = hg19
factor = ESR1
treat = absolutepath, absolutepath2
control = absolutepath, absolutepath2
output = absolutepath
[bowtie]
path = /usr/local/bin/bowtie
index = /mnt/Storage/data/Bowtie/hg19
bam2fq = /usr/local/bin/bam2fastx
maxalign = 1
[samtools]
path = /usr/local/bin/samtools
chrlen = /mnt/Storage/data/Samtool/chromInfo_hg19.txt
chrbed = /opt/bin/chr_limit/chr_limit_hg19.bed
[macs]
path = /usr/local/bin/macs2
bg2bw = /opt/bin/UCSCTools/bedGraphToBigWig
bedclip = /usr/local/bin/bedClip
[bedtools]
path = /usr/local/bin/bedtools
dhs = /mnt/Storage/data/DHS/DHS_hg19.bed
# for mouse, no velcro, skip
velcro = /opt/bin/wgEncodeHg19ConsensusSignalArtifactRegions.bed
[ceas]
path = /usr/local/bin/ceasBW
exon = /opt/bin/ceas-exon
peaks = 3000
refgene = /mnt/Storage/data/RefGene/hg19.refGene
chrlen =/mnt/Storage/data/sync_cistrome_lib/chromLen/hg19.len
promoter_sizes =
bipromoter_sizes =
rel_dist =
[conservation]
path = /usr/local/bin/conservation_plot.py
peaks = 3000
width = 4000
phast = /mnt/Storage/data/sync_cistrome_lib/conservation/hg19/placentalMammals
[correlation]
path = /opt/bin/wig_correlation_bigwig_input_only.py
wig_correlation_step = 10
wig_correlation_method = mean
wig_correlation_min = 2
wig_correlation_max = 50
[venn]
path = /usr/local/bin/venn_diagram.py
[seqpos]
path = /usr/local/bin/MDSeqPos.py
species = hs
peaks = 1000
mdscan_width = 200
mdscan_top_peaks = 200
seqpos_mdscan_top_peaks_refine = 500
width = 600
pvalue_cutoff = 0.001
db = cistrome.xml
[qc]
path = /mnt/Storage/home/duanxk/FastQC/fastqc
species = hs
|
replace the line 6 to line 9 with your machine configurations. When saved to test.conf, this config file can construct a powerful pipeline via:
> ChiLin run -c test.conf -t TF
detailed output and temporary files will be explained in the Raw Data
For autodc module for running ChiLin, we provide a fork version chilin-mvc_ with tools for auto downloading GEO data and analyzing on server.
Any question on installation or runnning is appreciated, please mail to qinqianhappy@gmail.com.