ATAC-seq bam files to ATAC-seq data matrices

Last updated: 2018-07-25

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File	Version	Author	Date	Message
html	f1b5827	Kevin Luo	2018-07-25	Build site.
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Step 0: Download JASPAR motif database

Download JASPAR motif database http://jaspar.genereg.net/download/CORE/JASPAR2018_CORE_non-redundant_pfms_meme.zip

Install required softwares:

FIMO from MEME suite.
samtools
bedtools
bwtools
UCSC command-line tools: bedGraphToBigWig, bigWigAverageOverBed

Step 1: Find TF motif matches using FIMO

script

cat code_RCC/fimo_jaspar_motif_rcc.sh

#!/bin/bash
#SBATCH --job-name=fimo
#SBATCH --mem=8G
#SBATCH --output=fimo_%J.out
#SBATCH --partition=broadwl

##############################################################################
# get motif matches using FIMO
#
# requires FIMO from MEME suite
# FIMO instructions: http://meme-suite.org/doc/fimo.html?man_type=web
#installation: http://meme-suite.org/doc/install.html?man_type=web
##############################################################################


## parameters
tf_name=$1
pwm_id=$2
thresh_pValue=$3 # 1e-4

###### example ######
# tf_name="CTCF"
# pwm_id="MA0139.1"
# thresh_pValue=1e-4
#####################

flank=100
ver_genome=hg19
max_fimo_sites=1000000

## extract pwm meme file
echo "pwm_id: $pwm_id, tf_name: $tf_name"

pwm_name="${tf_name}_${pwm_id}_${thresh_pValue}"

# directory for Jaspar motifs
dir_pwm="/project/mstephens/ATAC_DNase/motif_database/JASPAR_2018/JASPAR2018_CORE_non-redundant_pfms_meme"
pwm_filename="${dir_pwm}/${pwm_id}.meme"

# reference genome fasta file
genome_filename="/project/mstephens/ATAC_DNase/ref_genome/${ver_genome}.fa"

# output directory for FIMO motif matching results
dir_output="/project/mstephens/ATAC_DNase/motif_sites_JASPAR2018/"
mkdir -p ${dir_output}

## FIMO matching motifs
dir_motif_matches="${dir_output}/FIMO/${pwm_name}"
filename_motif_matches="${dir_motif_matches}/fimo.txt"

mkdir -p ${dir_motif_matches}
echo "Begin FIMO matching motif ..."

fimo --oc ${dir_motif_matches} --verbosity 2 --text \
    --bgfile --uniform-- --thresh ${thresh_pValue} --max-stored-scores ${max_fimo_sites} \
    ${pwm_filename} ${genome_filename}  \
    > ${filename_motif_matches}

echo "Finish FIMO: ${dir_motif_matches}"

run

# match motifs using FIMO ( p-value = 1e-4 ) on RCC

# CTCF MA0139.1
sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/fimo_jaspar_motif_rcc.sh CTCF MA0139.1 1e-4

sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/fimo_jaspar_motif_rcc.sh HIF1A MA1106.1 1e-4

sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/fimo_jaspar_motif_rcc.sh MEF2D MA0773.1 1e-4

Step 2: Get TF candidate binding sites

script

cat code_RCC/sites_jaspar_motif_rcc.sh

#!/bin/bash
#SBATCH --job-name=sites
#SBATCH --mem=8G
#SBATCH --output=sites_%J.out
#SBATCH --partition=broadwl


################################################################################
# The script process FIMO motif matches to get candidate binding sites
#
# requires process_pwm_sites.R to flank motif matches to get candidate sites
# requires bigWigAverageOverBed tool from UCSC to compute mapablity
# requires bedtools to filter out ENCODE blacklist regions
################################################################################

module load R

## parameters
tf_name=$1
pwm_id=$2
thresh_pValue=$3 # 1e-4

###### example ######
# tf_name="CTCF"
# pwm_id="MA0139.1"
# thresh_pValue=1e-4
#####################

flank=100
ver_genome=hg19
max_fimo_sites=1000000

## extract pwm meme file
echo "pwm_id: $pwm_id, tf_name: $tf_name"

pwm_name="${tf_name}_${pwm_id}_${thresh_pValue}"

dir_code=$HOME/projects/ATAC-seq/ATAC-seq_workflow/code_RCC

# directory for ENCODE mapability blacklist
dir_blacklist="/project/mstephens/ATAC_DNase/ENCODE_blacklist/hg19"

# output directory for FIMO motif matching results
dir_output="/project/mstephens/ATAC_DNase/motif_sites_JASPAR2018/"
mkdir -p ${dir_output}

## FIMO matching motifs
dir_motif_matches="${dir_output}/FIMO/${pwm_name}"
filename_motif_matches="${dir_motif_matches}/fimo.txt"

## get candidate sites after taking flanking windows around motif matches

# output directory for candidate sites
dir_sites="${dir_output}/candidate_sites/${thresh_pValue}"
mkdir -p ${dir_sites}

sites="${dir_sites}/${pwm_name}_flank${flank}_fimo_sites.bed"

## mapability downloaded from http://hgdownload.soe.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/
echo "Flank motif sites and compute mapability..."
filename_mapability="${dir_blacklist}/wgEncodeDukeMapabilityUniqueness20bp.bigWig"
Rscript ${dir_code}/process_pwm_sites.R ${tf_name} ${pwm_id} ${filename_motif_matches} ${flank} ${thresh_pValue} ${dir_sites} ${filename_mapability}

## filter ENCODE blacklist regions
echo "Filter ENCODE blacklist regions..."
blacklist_filename="${dir_blacklist}/wgEncodeDacMapabilityConsensusExcludable.bed"
bedtools intersect -v -a ${sites} -b ${blacklist_filename} > ${sites}.filtered.tmp
head -1 ${sites} | cat - ${sites}.filtered.tmp > ${sites}.filtered
mv ${sites}.filtered ${sites}
rm ${sites}.filtered.tmp

echo "Complete candidate sites processing."

run


## use the bigWigAverageOverBed tool from UCSC to compute mapablity
## https://genome.ucsc.edu/goldenpath/help/bigWig.html

## use the bedtools intersect to filter out ENCODE blacklist regions

sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/sites_jaspar_motif_rcc.sh CTCF MA0139.1 1e-4

sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/sites_jaspar_motif_rcc.sh HIF1A MA1106.1 1e-4

sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/sites_jaspar_motif_rcc.sh MEF2D MA0773.1 1e-4

Step 3: Count ATAC-seq genome-wide cleavage, and build tagcount bigwig file

script

cat code_RCC/genome_coverage_bamToBigwig.sh

#!/bin/bash

#SBATCH --job-name=coverage
#SBATCH --output=coverage_%J.out
#SBATCH --mem=10G
#SBATCH --partition=broadwl

################################################################################
# get 5' end coverage for bam files
# Compute the DNase or ATAC-seq cleavage (5' end) coverge along the genome
#
# requires samtools, bedtools, and bedGraphToBigWig (from UCSC)
################################################################################

bam_file=$1

dir_results="/project/mstephens/ATAC_DNase/ATAC-seq_Olivia_Gray/results/ATAC-seq_tagcounts/"

echo "Compute genome coverage for ${bam_file}"
echo "Output directory: ${dir_results}"

## fetch chrom size from UCSC
# ver_genome="hg19"
# echo "fetch chrom size for ${ver_genome}"
# mkdir -p "${dir_results}/genome_size/"
# genome_chrom_sizes="${dir_results}/genome_size/${ver_genome}.chrom.sizes"
# fetchChromSizes ${ver_genome} > ${genome_chrom_sizes}

## or download from UCSC
# cd ${dir_results}/genome_size/
# wget http://hgdownload.cse.ucsc.edu/goldenPath/hg19/bigZips/hg19.chrom.sizes

genome_chrom_sizes="/project/compbio/jointLCLs/reference_genomes/hg19/hg19.chrom.sizes"

## sort bam file
bam_dir_name=$(dirname ${bam_file})
bam_basename=$(basename ${bam_file} .bam)

cd ${bam_dir_name}

echo "base bamfile: ${bam_basename}"
echo "sort and index bam file"

samtools sort -o ${bam_basename}.sorted.bam ${bam_basename}.bam

samtools index ${bam_basename}.sorted.bam

samtools idxstats ${bam_basename}.sorted.bam > ${bam_basename}.idxstats.txt

bam_sorted_name="${bam_dir_name}/${bam_basename}.sorted.bam"

## count genome coverage, 5' end, save in bedGraph format, then convert to bigWig format

bw_file="${dir_results}/${bam_basename}.5p.0base.tagcount"

## forward strand
echo "Count genome coverage on + strand"
samtools view -b ${bam_sorted_name} | \
genomeCoverageBed -bg -5 -strand "+" -ibam stdin -g ${genome_chrom_sizes} > ${bw_file}.bedGraph

echo "coverting bedGraph to BigWig..."
sort -k1,1 -k2,2n ${bw_file}.bedGraph > ${bw_file}.sorted.bedGraph
bedGraphToBigWig ${bw_file}.sorted.bedGraph ${genome_chrom_sizes} ${bw_file}.fwd.bw
rm ${bw_file}.bedGraph ${bw_file}.sorted.bedGraph

## reverse strand
echo "Count genome coverage on - strand"
samtools view -b ${bam_sorted_name} | \
genomeCoverageBed -bg -5 -strand "-" -ibam stdin -g ${genome_chrom_sizes} > ${bw_file}.bedGraph

echo "coverting bedGraph to BigWig..."
sort -k1,1 -k2,2n ${bw_file}.bedGraph > ${bw_file}.sorted.bedGraph
bedGraphToBigWig ${bw_file}.sorted.bedGraph ${genome_chrom_sizes} ${bw_file}.rev.bw
rm ${bw_file}.bedGraph ${bw_file}.sorted.bedGraph

echo "Finished computing genome coverage => ${bw_file}.bw"

run


## bam files
bamfiles=("H1_nomito_rdup.bam" "H2_nomito_rdup.bam" "H3_nomito_rdup.bam" "N1_nomito_rdup.bam" "N2_nomito_rdup.bam" "N3_nomito_rdup.bam")

for bam_name in "${bamfiles[@]}"
do
   echo "${bam_name}"
   sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/genome_coverage_bamToBigwig.sh /project/mstephens/ATAC_DNase/ATAC-seq_Olivia_Gray/ATAC-seq_BAMfiles/"${bam_name}"
done

Step 4: match ATAC-seq tagcount matrices for each motif

script

cat code_RCC/get_motif_count_matrices.sh

#!/bin/bash

#SBATCH --job-name=extract_counts
#SBATCH --output=extract_counts_%J.out
#SBATCH --partition=broadwl
#SBATCH --mem=8G

################################################################################
# The script takes bigwig files of DNase or ATAC-seq genome-wide count coverages
# then, it extracts tagcounts for a TF with 100bp flanks around motif
# and save in a tagcount matrix.
#
# requires bigwig tagcount files (in the earlier step)
# requires bwtool to extract counts from bigwig files
# requires rev_tagcount_bwtool.R to reverse counts on reverse strand
################################################################################

module load R

tf_name=$1
pwm_id=$2
bam_name=$3

thresh_pValue="1e-4"
flank=100
ver_genome="hg19"

pwm_name="${tf_name}_${pwm_id}_${thresh_pValue}"

dir_code=$HOME/projects/ATAC-seq/ATAC-seq_workflow/code_RCC
dir_tagcounts=/project/mstephens/ATAC_DNase/ATAC-seq_Olivia_Gray/results/ATAC-seq_tagcounts/
dir_count_matrix=/project/mstephens/ATAC_DNase/ATAC-seq_Olivia_Gray/results/ATAC-seq_count_matrix/${pwm_name}/
dir_sites=/project/mstephens/ATAC_DNase/motif_sites_JASPAR2018/candidate_sites/${thresh_pValue}/
filename_sites=${dir_sites}/${pwm_name}_flank${flank}_fimo_sites.bed

echo "PWM name: ${pwm_name}"
echo "Candidate sites: ${filename_sites}"
echo "Bam filename: ${bam_name}"

## Extract counts around motif matches into tagcount matrices
## Check the existence of tagcount bigwig files and candidate sites
bam_basename=$(basename ${bam_name} .bam)
bw_file="${dir_tagcounts}/${bam_basename}.5p.0base.tagcount"
file_tagcount_fwd=${bw_file}.fwd.bw
file_tagcount_rev=${bw_file}.rev.bw
echo "Tagcount fwd name: ${file_tagcount_fwd}"
echo "Tagcount rev name: ${file_tagcount_rev}"

if [ ! -s ${file_tagcount_fwd} ] || [ ! -s ${file_tagcount_rev} ]; then
  echo "ERROR: Tagcount bigwig files for: ${bam_name} does not exist!"
elif [ ! -s ${filename_sites} ]; then
  echo "ERROR: Candidate sites ${filename_sites} does not exist!"
else

  echo "Counting cuts around the candidate sites of ${pwm_name} with ${flank}bp flanking windows ..."

  mkdir -p ${dir_count_matrix}

  file_count_matrix_fwd="${dir_count_matrix}/${pwm_name}_${bam_basename}_fwdcounts.m"
  file_count_matrix_rev="${dir_count_matrix}/${pwm_name}_${bam_basename}_revcounts.m"

  ## count matrix around the candidate sites
  echo "match matrix of ${file_count_matrix_fwd} ..."
  cut -f 1-4 ${filename_sites} | bwtool extract bed stdin ${file_tagcount_fwd} ${file_count_matrix_fwd} -fill=0 -decimals=0 -tabs

  echo "match matrix of ${file_count_matrix_rev} ..."
  cut -f 1-4 ${filename_sites} | bwtool extract bed stdin ${file_tagcount_rev} ${file_count_matrix_rev} -fill=0 -decimals=0 -tabs

  Rscript ${dir_code}/rev_tagcount_bwtool.R ${file_count_matrix_fwd} ${file_count_matrix_rev} ${filename_sites}

  # compress the files to .gz
  gzip -f ${file_count_matrix_fwd} ${file_count_matrix_rev}
  echo "Finished counting for ${pwm_name} in ${bam_name}."

fi

run


## bam files
bamfiles=("H1_nomito_rdup.bam" "H2_nomito_rdup.bam" "H3_nomito_rdup.bam" "N1_nomito_rdup.bam" "N2_nomito_rdup.bam" "N3_nomito_rdup.bam")

## CTCF
for bam_name in "${bamfiles[@]}"
do
   echo "${bam_name}"
   sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/get_motif_count_matrices.sh CTCF MA0139.1 "${bam_name}"
done

## HIF1A::ARNT
for bam_name in "${bamfiles[@]}"
do
   echo "${bam_name}"
   sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/get_motif_count_matrices.sh HIF1A::ARNT MA0259.1 "${bam_name}"
done


## HIF1A
for bam_name in "${bamfiles[@]}"
do
   echo "${bam_name}"
   sbatch ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/get_motif_count_matrices.sh HIF1A MA1106.1 "${bam_name}"
done


## MEF2D
for bam_name in "${bamfiles[@]}"
do
   echo "${bam_name}"
   sbatch --mem=15G ~/projects/ATAC-seq/ATAC-seq_workflow/code_RCC/get_motif_count_matrices.sh MEF2D MA0773.1 "${bam_name}"
done

Session information

sessionInfo()

R version 3.3.3 (2017-03-06)
Platform: x86_64-apple-darwin13.4.0 (64-bit)
Running under: macOS  10.13.4

locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

loaded via a namespace (and not attached):
 [1] workflowr_1.0.1   Rcpp_0.12.14      digest_0.6.13    
 [4] rprojroot_1.3-2   R.methodsS3_1.7.1 backports_1.1.2  
 [7] git2r_0.21.0      magrittr_1.5      evaluate_0.10.1  
[10] stringi_1.1.5     whisker_0.3-2     R.oo_1.21.0      
[13] R.utils_2.6.0     rmarkdown_1.9     tools_3.3.3      
[16] stringr_1.2.0     yaml_2.1.16       htmltools_0.3.6  
[19] knitr_1.18

This reproducible R Markdown analysis was created with workflowr 1.0.1

ATAC-seq bam files to ATAC-seq data matrices

Kaixuan Luo

6/13/2018

Step 0: Download JASPAR motif database

Step 1: Find TF motif matches using FIMO

run

Step 2: Get TF candidate binding sites

run

Step 3: Count ATAC-seq genome-wide cleavage, and build tagcount bigwig file

run

Step 4: match ATAC-seq tagcount matrices for each motif

run

Session information