Instructions

Through the pipeline, several temporary files will be generated, some of them are only used for settings and transitions, others for continuing the next step, the rest for publishing and interpreting a biological story.

Note

a better way to organize your ChIP-seq project

Raw Data

Format Type instruction
FASTQ text single end
FASTQ.gz gz single end
FASTQ text pair end
FASTQ.gz gz pair end

Instructions to usage

Simple mode (The major mode)

Demo data command is as follows:

chilin  simple -p narrow -t foxa1_t1.fastq  -c foxa1_c1.fastq -i local -o local -s hg19  --skip 10,12 --dont_remove

See skip option for details.

This is major and the easiest mode to run ChiLin for single end data with default bwa mapper, for single end data using comma to separate sample replicates for IP and input ChIP-seq sample:

chilin  simple -u your_name -s your_species --threads 8 -i id -o output -t treat1.fastq,treat2.fastq -c control1.fastq,control2.fastq  -p narrow -r tf

For pair end data, use semicolon to separate sample replicates, use comma to separate pairs, do not forget to add quotes(”) of your sample file path:

chilin simple --threads 8 -i H3K27me3_PairEnd -o H3K27me3_PairEnd -u you -s mm9 -t "GSM905438.fastq_R1.gz,GSM905438.fastq_R2.gz" -c "GSM905434.fastq_R1.gz,GSM905434.fastq_R2.gz;GSM905436.fastq_R1.gz,GSM905436.fastq_R2.gz" -p both --pe

See more options about simple by:

chilin simple -h

simple mode useful option

  • -t In simple mode, this is the options for specifying path to treatment.
  • -c In simple mode, this is the options for specifying path to control.
  • -p peaks calling type, narrow or broad or both, #e.g., If your factor is transcription factor, and you want to call narrow peaks only, or broad histone mark with broad peak calling
  • -i prefix of the output name
  • -o output results directory
  • -s species, must be filled, the -s option is corresponding to your filled python config file [section], see section for details, [species].
  • -u user
  • –pe pair end mode
  • –pe pair end mode
  • –maper to choose your mapping tool
  • –threads threads number for mapping tool
  • -r factor type, some default settings for three factor types, tf,histone,dnase

(optional) gen mode

This mode is to generate config file for run-mode. A config file is look like this,

  • The major section user needs to fill is the [basics] section.
chilin gen -o test.conf

[basics]
user = anonymous
id = local
time = 2014-05-09
species = hg19
factor = tf
treat = foxa1_t1.fastq,foxa1_t1.fastq
cont = foxa1_c1.fastq,foxa1_c1.fastq
output = output_directory
version = 2.0.0

run mode usage

After configurating the config files above, you could use run mode with a single command:

chilin  gen -o my_config
## modify tool parameters and run
chilin  run -c my_config

batch mode usage

This mode help user run dataset one by one with one process.

After configurating a batch of the config files above, such as e.g. 1.conf, 2.conf, 3.conf, then you fill in a file called batch.conf:

1.conf
2.conf
3.conf

you could use batch mode with a single command:

chilin  batch -b batch.conf

Step control, mapper choice and threads control, mimic run

Common options can be used for simple mode, run and batch modes. Each step control is tolerant, continue running even tool failed processing.

  • –skip, step control, e.g:

    chilin  simple -s hg19 -i id -p narrow -o output -u user --skip 1,3,5,9,10,11 -t treat1.fastq,treat2.fastq`
    • step 1(can skip): FastQC sequence quality evaluation, reads GC contents evaluation and library contamination, this step can be skipped.
    • step 2: bwa(default), bowtie or star mapping, this step cannot be skipped, because this provided necessary BAM files.
    • step 3: sub-sample bam files and do macs2 fragment size estimation.
    • step 4: sub-sample bam files(if step 3 is run, skip) and do PBC evaluation
    • step 5: call peak for replicates samples, and do replicates peak overlap/correlation analysis
    • step 6: call peak for merged bam file, this step cannot be skipped, because this provided peak for annotation step
    • step 7: calculate FRiP scores for each sample.
    • step 8: use bedAnnotate.py script to evaluate merged peak calling meta regions distribution(promoters, exons, introns, intergenic, dhs, black list regions)
    • step 9: sub-sample bam files(if step 3 is run, skip) and calculate reads ratio in meta regions
    • step 10(can skip): draw Phastcon scores distribution around peak call summits, if you do not have Phastcon score bigwig files, use –skip 10 or leave chilin.conf blank for that reference
    • step 11(can skip): Regulatory potential score calculation on top 10k peaks
    • step 12(can skip): use MDSeqPos to perform motif analysis, for peaks number less than 200, ChiLin skip this step automatically
    • step 13(can skip): generate report, use explicitly skip to skip 10-12 if necessary.

  • –dont_resume, by default, each re-run would use previous temporary files to resume from the step it crashed. When dont_resume is on, ChiLin would start from first step, so user do not to clean up the work directory.

  • –dont_remove, keep temporary files

  • –dry-run, mimic run chilin command

  • –threads, BWA, Bowtie and FastQC multithreads options.

  • –mapper, to choose mapping tools, should match your genome index in genome index

Instructions to config file

basics

[basics]

Lists all the meta-data of current workflow. Consist of the following options:

user

user name

time

time you start to run

species

The name of species, written to the QCreport and log Limit: a string (1) consist of numbers, alphabets or '_' (2) shorter than 20 characters

id

This is used as output prefix, such as input id: test, output file would be: test_treat.bam

factor

The name of species, writen to DC summary and QCreport, log Limit: a string (1) come from GO standard term

treat

The paths of treatment files Limit: absolute path of files in supported formats

cont

The paths of control files Limit: absolute or relative path of files in supported formats

output

The paths of output directory.

tool

The tool section is like this:

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#ChiLin is dependent on several tools, please specify the absolute path to
#these tools--ALL FIELDS ARE REQUIRED
#put bedClip, bedGraphToBigWig, bowtie, star, bwa, fastqc, bedtools, macs2, samtools, seqtk, wigCorrelate
#in executable PATH
#other system tool includes convert, pdflatex, R, python2.7
[tool]
mdseqpos =
macs2 =
[tool]

Lists all the meta-data of current workflow. Consist of the following options:

mdseqpos

absolute path to MDSeqPos.py

macs2

absolute path to macs2

species

You can add as many species as possible. To add species, first you need to read dependent data section to fill the following. Then, you should fill the config files species section, the rule is like follows, e.g. hg19 assembly.

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[hg19]
genome_index =
# fasta file separated by chromosome, such as chr1.fa
genome_dir =
chrom_len =
dhs =
## blacklist region
velcro =
conservation =
geneTable =

And mm9 assembly,

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[mm9]
genome_index =
# fasta file separated by chromosome, such as chr1.fa
genome_dir =
chrom_len =
dhs =
## blacklist region
velcro =
conservation =
geneTable =

And hg38 assembly,

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[hg38]
genome_index =
# fasta file separated by chromosome, such as chr1.fa
genome_dir =
chrom_len =
dhs =
## blacklist region
velcro =
conservation =
geneTable =
[species]

specific species assembly version you want to analyze Consist of the following options:

genome_index

absolute path to corresponding mappers genome index, if you use default bwa, this should be bwa index.

genome_dir

absolute path to genome fasta files, separated by chromosome, like chr1.fa, chr2.fa, chr3.fa ...

chrom_len

absolute path to chromosome length text file

dhs

absolute path union DHS regions

velcro

absolute path black list regions

conservation

absolute path to the directory containing UCSC Phastcon score bigwig files

geneTable

standard refSeq annotation table from UCSC table browser

contamination

you can add all species you are suspicious of sampling swap or library contamination.

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#------------------------------------------------------------------------------
# Contamination
#------------------------------------------------------------------------------
#OPTIONAL- our contamination module can screen for any species defined below
#specify the species name and the path to the bwa index as follows: e.g.
#ECOLI = /some/path/ecoli
[contamination]
mycoplasma = mycoplasma
# ecoli =
# yeat =
[contamination]

specific species assembly path that you want to screen.

software options

ChiLin has some user-defined parameters for macs2, regulatory potential, conservation score and motif analysis.

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#the only thing you can affect here is the number of threads used.
[macs2]
#refer to the macs2 help message to find out what these mean, species for effective genome size
extsize = 146
# effecitive genome sizes, support hs, mm, other species, please refer to chromInfo
species = 
type = both
fdr = 0.01
keep_dup = 1

[reg]
## regulatory potential score prediction top peaks
peaks = 10000
dist = 100000

[conservation]
## for tf/dnase we suggest 400bp width around summit, for histone 4000
type = tf
peaks = 5000
width = 400

[seqpos]
peaks = 5000
mdscan_width = 200
mdscan_top_peaks = 200
seqpos_mdscan_top_peaks_refine = 500
width = 600
pvalue_cutoff = 0.001
db = cistrome.xml
[macs2]

macs2 parameters

extsize

fixed extension size for macs2 peak calling

type [for macs2]

peak calling types, user can choose narrow, broad and both, we suggest user use narrow for TF and active histone marks, use broad for broad histone marks, use both for chromatin regulators.

fdr

FDR cutoff for macs2 peak calling

keep_dup

duplicates level, suggest 1 for removing redundancy, or all for preserving all redudancy for DNase-seq

[reg]

specific species assembly version you want to analyze

peaks [for reg]

top peaks number(sorted by macs2 score) for estimating regulatory score.

dist

distance to TSS cutoff when calculating regulatory potential score

[conservation]

specific species assembly version you want to analyze

type [for conservation]

transcription factor or histone mark

peaks

top peaks (sorted by macs2 score) for plotting conservation distribution

width

window width around peaks summits for plotting conservation

[seqpos]

specific species assembly version you want to analyze

peaks [for conservation]

top peaks number for seqpos (search in the motif database)

mdscan_width

motif scan window width around peak summit

mdscan_top_peaks

top peaks for denovo motif scan

width

seqpos width

seqpos_mdscan_top_peaks_refine

seqpos and mdscan top peaks refine, see mdseqpos

db

choose mdseqpos motif database, default cistrome.xml

pvalue_cutoff

cutoff for motif analysis

Instructions to results

The output prefix is from:

  • simple-mode -i id specified, or run-mode filled in [basics] section id part.
  • The output directory is simple mode -o output specified or 2. run-mode filled in [basics] section output part.
  • For a fully test dataset with replicates of treatments and replicates of controls, the results folder are like following, which are generated with -dont_remove option, to preserve all temporary files, use -dont_remove option.

Without –dont_remove option, the work directory would be cleaned up:

id
|-- attic
|   |-- json
|   |   |-- id_conserv.json
|   |   |-- id_contam.json
|   |   |-- id_dhs.json
|   |   |-- id_enrich_meta.json
|   |   |-- id_fastqc.json
|   |   |-- id_frag.json
|   |   |-- id_frip.json
|   |   |-- id_macs2.json
|   |   |-- id_macs2_rep.json
|   |   |-- id_map.json
|   |   |-- id_meta.json
|   |   |-- id_pbc.json
|   |   `-- id_rep.json
|   |-- id_conserv.pdf
|   |-- id_control.bam
|   |-- id_control_rep1.bam
|   |-- id_control_rep2.bam
|   |-- id_gene_score.txt
|   |-- id_treat_rep1.bam
|   |-- id_treat_rep2.bam
|   `-- id_treatment.bam
|-- id_report.pdf
|-- id_control.bw
|-- id_peaks.xls
|-- id_sort_peaks.narrowPeak
|-- id_sort_summits.bed
|-- id_treat.bw
|-- id_treat_rep1_control.bw
|-- id_treat_rep1_peaks.xls
|-- id_treat_rep1_sort_peaks.narrowPeak
|-- id_treat_rep1_treat.bw
|-- id_treat_rep2_control.bw
|-- id_treat_rep2_peaks.xls
|-- id_treat_rep2_sort_peaks.narrowPeak
`-- id_treat_rep2_treat.bw

With –dont_remove option,

output
|-- json  ## qc statistics
|   |-- id_conserv.json  ## conservation scores
|   |-- id_contam.json   ## library contamination evaluation
|   |-- id_dhs.json      ## union dhs overlap
|   |-- id_enrich_meta.json ## meta regions reads ratio
|   |-- id_fastqc.json      ## fastqc evaluation
|   |-- id_frag.json        ## fragment size evaluation
|   |-- id_frip.json        ## FRiP scores
|   |-- id_macs2.json       ## merged macs2 peak calling number
|   |-- id_macs2_rep.json   ## macs2 replicates peaks number
|   |-- id_map.json         ## mapping ratio statistics
|   |-- id_meta.json        ## peak meta regions distribution
|   |-- id_pbc.json         ## PBC score
|   `-- id_rep.json         ## replicates consistency
|-- latex  ## rendered latex document
|   |-- id_begin.tex
|   |-- id_conserv.tex
|   |-- id_contam.tex
|   |-- id_end.tex
|   |-- id_fastqc.tex
|   |-- id_fastqc_gc.tex
|   |-- id_frip.tex
|   |-- id_map.tex
|   `-- id_summary_table.tex
|-- id.aux ## latex log file
|-- id.cor ## correlation analysis temporary file
|-- id.dhs ## dhs overlap analysis temporary file
|-- id.log ## latex log file
|-- id.meta ## meta regions peak distribution temporary file
|-- id.out  ## latex log file
|-- id_report.pdf  ## pdf document generated
|-- id.tex  ## file latex file
|-- id_0_1.overlap  ## replicates peak overlap
|-- id_bwa_compare.R ## R script for comparing new data to historic data
|-- id_bwa_compare.pdf ## pdf generated by R script above
|-- id_conserv.R  ## conservation plot R code
|-- id_conserv.pdf ## pdf generated by R script above
|-- id_conserv.txt ## 7 or 5 point conservation scores around summits
|-- id_conserv_cluster.R ## conservation scores clustering plot
|-- id_conserv_compare.pdf  ## conservation pdf generated by R script above
|-- id_conserv_img.pdf  ## low resolution image of conservation plot
|-- id_control.bam      ## merged control bam files
|-- id_control.bw       ## control bigwiggle file
|-- id_control_lambda.bdg  ## control bedgraph file
|-- id_control_lambda.bdg.tmp  ## bedClip filtered bedgraph file
|-- id_control_rep1.bam   ## sorted, mapping quality 1 filtered replicate 1st bam file
|-- id_control_rep1.enrich.dhs   ## reads ratio in DHS regions
|-- id_control_rep1.enrich.exon  ## reads ratio in exon regions
|-- id_control_rep1.enrich.promoter  ## reads ratio in promoter regions
|-- id_control_rep1.fastq  ## copied fastq file
|-- id_control_rep1.frip   ## FRiP score from replicate control 1st
|-- id_control_rep1.hist   ## read locations histogram of replicate control 1st
|-- id_control_rep1.nochrM  ## chromosome information without chrM
|-- id_control_rep1.pbc  ## bwa PBC score
|-- id_control_rep1.sai  ## bwa sai file
|-- id_control_rep1.sam  ## bwa sam file
|-- id_control_rep1.tmp.bam     ## mapping quality filtered bam files, without sorting
|-- id_control_rep1_100k.fastq  ## subsampled fastq reads
|-- id_control_rep1_100k_fastqc ## fastqc temporary results
|   |-- Icons
|   |   |-- error.png
|   |   |-- fastqc_icon.png
|   |   |-- tick.png
|   |   `-- warning.png
|   |-- Images
|   |   |-- duplication_levels.png
|   |   |-- kmer_profiles.png
|   |   |-- per_base_gc_content.png
|   |   |-- per_base_n_content.png
|   |   |-- per_base_quality.png
|   |   |-- per_base_sequence_content.png
|   |   |-- per_sequence_gc_content.png
|   |   |-- per_sequence_quality.png
|   |   `-- sequence_length_distribution.png
|   |-- fastqc_data.txt
|   |-- fastqc_report.html
|   `-- summary.txt
|-- id_control_rep1_100k_fastqc.zip
|-- id_control_rep1_4000000.bam   ## subsampled 4M reads bam file
|-- id_control_rep1_4000000_nochrM.bam  ## subsampled non-chrM 4M reads bam file
|-- id_control_rep1_mapped.bwa  ## replicate control 1st mapped reads statistics
|-- id_control_rep1_nochrM.bam  ## sorted, mapping quality filtered bam file
|-- id_control_rep1_nochrM.sam  ## mapped sam files without chrM
|-- id_control_rep1_nochrM.sam.4000000  ## subsampled 4M reads without chrM
|-- id_control_rep1_total.bwa  ## total reads statistics from bwa
|-- id_control_rep1_u.sam  ## unique reads SAM file
|-- id_control_rep1_u.sam.4000000  ## subsampled unique reads SAM file
|-- id_control_rep1mbr.bam  ## cross species mapping to mbr, or species you specified
|-- id_control_rep1mbr.sai
|-- id_control_rep1mbr.sam
|-- id_control_rep1mbr.tmp.bam
|-- id_control_rep1mbr_mapped.bwa
|-- id_control_rep1mbr_total.bwa
|-- id_control_rep2.bam   ## control replicates 2nd bam file
|-- id_control_rep2.enrich.dhs
|-- id_control_rep2.enrich.exon
|-- id_control_rep2.enrich.promoter
|-- id_control_rep2.fastq
|-- id_control_rep2.frip
|-- id_control_rep2.hist
|-- id_control_rep2.nochrM
|-- id_control_rep2.pbc
|-- id_control_rep2.sai
|-- id_control_rep2.sam
|-- id_control_rep2.tmp.bam
|-- id_control_rep2_100k.fastq
|-- id_control_rep2_100k_fastqc
|   |-- Icons
|   |   |-- error.png
|   |   |-- fastqc_icon.png
|   |   |-- tick.png
|   |   `-- warning.png
|   |-- Images
|   |   |-- duplication_levels.png
|   |   |-- kmer_profiles.png
|   |   |-- per_base_gc_content.png
|   |   |-- per_base_n_content.png
|   |   |-- per_base_quality.png
|   |   |-- per_base_sequence_content.png
|   |   |-- per_sequence_gc_content.png
|   |   |-- per_sequence_quality.png
|   |   `-- sequence_length_distribution.png
|   |-- fastqc_data.txt
|   |-- fastqc_report.html
|   `-- summary.txt
|-- id_control_rep2_100k_fastqc.zip
|-- id_control_rep2_4000000.bam
|-- id_control_rep2_4000000_nochrM.bam
|-- id_control_rep2_mapped.bwa
|-- id_control_rep2_nochrM.bam
|-- id_control_rep2_nochrM.sam
|-- id_control_rep2_nochrM.sam.4000000
|-- id_control_rep2_total.bwa
|-- id_control_rep2_u.sam
|-- id_control_rep2_u.sam.4000000
|-- id_control_rep2mbr.bam
|-- id_control_rep2mbr.sai
|-- id_control_rep2mbr.sam
|-- id_control_rep2mbr.tmp.bam
|-- id_control_rep2mbr_mapped.bwa
|-- id_control_rep2mbr_total.bwa
|-- id_gene_score.txt  ## regulatory potential for top 10000 peaks
|-- id_peaks.narrowPeak  ## merged peak call for narrowPeak or broadPeak
|-- id_peaks.xls ## macs2 excel file
|-- id_peaks_top_conserv.bed  ## top peaks for conservation plot
|-- id_peaks_top_reg.bed  ## top peaks for regulatory potential score calculation
|-- id_raw_sequence_qc.R  ## median raw sequence quality plot
|-- id_raw_sequence_qc.pdf
|-- id_sort_peaks.narrowPeak ## sorted merged peak calling
|-- id_sort_summits.bed  ## sorted summits of peaks
|-- id_summary.txt  ## plain text for qc summary
|-- id_summits.bed  ## merged peak calling summits file
|-- id_treat.bw  ## merged pileup treatment bigwiggle file
|-- id_treat_pileup.bdg  ## merged pileup treatment bedgraph file
|-- id_treat_pileup.bdg.tmp  ## merged pileup treatment bedgraph temporary file
|-- id_treat_rep1   ## MACS2 predictd R script
|-- id_treat_rep1.bam  ## bam file generated by bwa and samtools
|-- id_treat_rep1.enrich.dhs
|-- id_treat_rep1.enrich.exon
|-- id_treat_rep1.enrich.promoter
|-- id_treat_rep1.fastq
|-- id_treat_rep1.frip
|-- id_treat_rep1.hist
|-- id_treat_rep1.nochrM
|-- id_treat_rep1.pbc
|-- id_treat_rep1.sai
|-- id_treat_rep1.sam
|-- id_treat_rep1.tmp.bam
|-- id_treat_rep1_100k.fastq
|-- id_treat_rep1_100k_fastqc
|   |-- Icons
|   |   |-- error.png
|   |   |-- fastqc_icon.png
|   |   |-- tick.png
|   |   `-- warning.png
|   |-- Images
|   |   |-- duplication_levels.png
|   |   |-- kmer_profiles.png
|   |   |-- per_base_gc_content.png
|   |   |-- per_base_n_content.png
|   |   |-- per_base_quality.png
|   |   |-- per_base_sequence_content.png
|   |   |-- per_sequence_gc_content.png
|   |   |-- per_sequence_quality.png
|   |   `-- sequence_length_distribution.png
|   |-- fastqc_data.txt
|   |-- fastqc_report.html
|   `-- summary.txt
|-- id_treat_rep1_100k_fastqc.zip
|-- id_treat_rep1_4000000.bam
|-- id_treat_rep1_4000000_nochrM.bam
|-- id_treat_rep1_control.bw
|-- id_treat_rep1_control_lambda.bdg
|-- id_treat_rep1_control_lambda.bdg.tmp
|-- id_treat_rep1_frag_sd.R  ## fragment analysis script for parsing macs2 R script
|-- id_treat_rep1_mapped.bwa
|-- id_treat_rep1_model.R  ## MACS2 R script for analyzing fragment size
|-- id_treat_rep1_nochrM.bam
|-- id_treat_rep1_nochrM.sam
|-- id_treat_rep1_nochrM.sam.4000000
|-- id_treat_rep1_peaks.narrowPeak  ## replicate 1 peak calling
|-- id_treat_rep1_peaks.xls
|-- id_treat_rep1_sort_peaks.narrowPeak
|-- id_treat_rep1_summits.bed
|-- id_treat_rep1_total.bwa
|-- id_treat_rep1_treat.bw
|-- id_treat_rep1_treat_pileup.bdg
|-- id_treat_rep1_treat_pileup.bdg.tmp
|-- id_treat_rep1_u.sam  ## uniquely mapping sam file, defined by mapping quality above 1
|-- id_treat_rep1_u.sam.4000000
|-- id_treat_rep1mbr.bam
|-- id_treat_rep1mbr.sai
|-- id_treat_rep1mbr.sam
|-- id_treat_rep1mbr.tmp.bam
|-- id_treat_rep1mbr_mapped.bwa
|-- id_treat_rep1mbr_total.bwa
|-- id_treat_rep2
|-- id_treat_rep2.bam
|-- id_treat_rep2.enrich.dhs
|-- id_treat_rep2.enrich.exon
|-- id_treat_rep2.enrich.promoter
|-- id_treat_rep2.fastq
|-- id_treat_rep2.frip
|-- id_treat_rep2.hist
|-- id_treat_rep2.nochrM
|-- id_treat_rep2.pbc
|-- id_treat_rep2.sai
|-- id_treat_rep2.sam
|-- id_treat_rep2.tmp.bam
|-- id_treat_rep2_100k.fastq
|-- id_treat_rep2_100k_fastqc
|   |-- Icons
|   |   |-- error.png
|   |   |-- fastqc_icon.png
|   |   |-- tick.png
|   |   `-- warning.png
|   |-- Images
|   |   |-- duplication_levels.png
|   |   |-- kmer_profiles.png
|   |   |-- per_base_gc_content.png
|   |   |-- per_base_n_content.png
|   |   |-- per_base_quality.png
|   |   |-- per_base_sequence_content.png
|   |   |-- per_sequence_gc_content.png
|   |   |-- per_sequence_quality.png
|   |   `-- sequence_length_distribution.png
|   |-- fastqc_data.txt
|   |-- fastqc_report.html
|   `-- summary.txt
|-- id_treat_rep2_100k_fastqc.zip
|-- id_treat_rep2_4000000.bam
|-- id_treat_rep2_4000000_nochrM.bam
|-- id_treat_rep2_control.bw
|-- id_treat_rep2_control_lambda.bdg
|-- id_treat_rep2_control_lambda.bdg.tmp
|-- id_treat_rep2_frag_sd.R
|-- id_treat_rep2_mapped.bwa
|-- id_treat_rep2_model.R
|-- id_treat_rep2_nochrM.bam
|-- id_treat_rep2_nochrM.sam
|-- id_treat_rep2_nochrM.sam.4000000
|-- id_treat_rep2_peaks.narrowPeak
|-- id_treat_rep2_peaks.xls
|-- id_treat_rep2_sort_peaks.narrowPeak
|-- id_treat_rep2_summits.bed
|-- id_treat_rep2_total.bwa
|-- id_treat_rep2_treat.bw
|-- id_treat_rep2_treat_pileup.bdg
|-- id_treat_rep2_treat_pileup.bdg.tmp
|-- id_treat_rep2_u.sam   ## uniquely mapping sam file, defined by mapping quality above 1
|-- id_treat_rep2_u.sam.4000000
|-- id_treat_rep2mbr.bam
|-- id_treat_rep2mbr.sai
|-- id_treat_rep2mbr.sam
|-- id_treat_rep2mbr.tmp.bam
|-- id_treat_rep2mbr_mapped.bwa
|-- id_treat_rep2mbr_total.bwa
`-- id_treatment.bam  ## samtools merged filtered bam files

Built-in tools

  • conservation_plot.py for generating conservation profiles
  • bedAnnotate.py is used to calculate meta gene distribuiton.