Last updated: 2018-06-19
workflowr checks: (Click a bullet for more information) ✔ R Markdown file: up-to-date
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
✔ Environment: empty
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it’s best to always run the code in an empty environment.
✔ Seed:
set.seed(12345)
The command set.seed(12345)
was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
✔ Session information: recorded
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
✔ Repository version: 2f53108
wflow_publish
or wflow_git_commit
). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rhistory
Ignored: .Rproj.user/
Ignored: output/.DS_Store
Untracked files:
Untracked: data/18486.genecov.txt
Untracked: data/YL-SP-18486-T_S9_R1_001-genecov.txt
Untracked: data/bin200.5.T.nuccov.bed
Untracked: data/bin200.Anuccov.bed
Untracked: data/bin200.nuccov.bed
Untracked: data/gene_cov/
Untracked: data/leafcutter/
Untracked: data/reads_mapped_three_prime_seq.csv
Untracked: data/ssFC200.cov.bed
Untracked: output/picard/
Untracked: output/plots/
Untracked: output/qual.fig2.pdf
Unstaged changes:
Modified: analysis/dif.iso.usage.leafcutter.Rmd
Modified: analysis/explore.filters.Rmd
Modified: code/Snakefile
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
File | Version | Author | Date | Message |
---|---|---|---|---|
Rmd | 2f53108 | Briana Mittleman | 2018-06-19 | filter A code |
I will use this analysis to develop a filtering method to filter reads that map to genomic locations with PolyA stretches. These reads could be due to priming of the poly dT primer in the protocol rather than actual polyA tails. This will be a problem for our differential APA analysis between total and nuclear RNA if mis primming is more likely to happen in the nuclear fraction. I am adapting a script by Ankeeta Shah to detect misprimming in coelesce seq. The script uses the python package pysam to work with bam files in python like samtools.
#!/usr/bin/env python
"""
Usage: python extractReadsWithMismatchesin6FirstNct_noS.py <input_bam> <output_bam>
"""
import sys, pysam, re
iBAM = pysam.Samfile(sys.argv[1], 'r') # reads from the standard input
oBAM = pysam.Samfile(sys.argv[2], 'w', template=iBAM) # output
for line in iBAM:
if (line.is_read2): #for paired end reads, if mate 2
string = line.cigarstring
regex=re.compile('^[0-9]*M') #only look for reads that have M (meaning match or mismatch) at the front of the cigar string
if re.match(regex, string):
md=re.findall(r'\d+', [tag[1] for tag in line.tags if tag[0]=='MD'][0]) #get md tag
if len(md) == 1 : # if there are no mismatches
oBAM.write(line) # write the alignment into the output file
else:
if (not line.is_reverse) and (int(md[0]) >= 6): # if the first mismatch occurs after the 6th nt (from the 5' end)
oBAM.write(line) # write the alignment into the output file
elif (line.is_reverse) and (int(md[-1]) >= 6): # same as above but for reads that align to the reverse strand
oBAM.write(line)
# close files
iBAM.close()
oBAM.close()
I need to make the following changes to this script:
Remove first if statement because I do not have paired end reads
get all of the places that have an M in the cigar string. Then look at the one with the longest integer attached. This will correspond to the longest region of the read mapping.
Add a reg exp. to check if mapping region includes 6 A’s.
This should write out a bam with just the reads mapping to 6 A’s.
#!/usr/bin/env python
"""
Usage: python filter6As.py <input_bam> <output_bam>
"""
import sys, pysam, re
iBAM = pysam.Samfile(sys.argv[1], 'r') # reads from the standard input
oBAM = pysam.Samfile(sys.argv[2], 'w', template=iBAM) # output
for line in iBAM:
string = line.cigarstring
regex=re.compile('[0-9]*M') #only look for reads that have M (meaning match or mismatch) at the front of the cigar string
test.string="AAAAAA"
if len(re.findall(regex, string))>=1:
#find the logest mapping string
match=re.findall(regex, string)
maxM=0
matchind=0
numM=re.compile('[0-9]*')
for M in range(len(match)):
if re.findall(numM,match[M]) > maxM:
maxM= re.findall(numM,match[M])
matchind=M
longestmatch=match[M]
#query_alignment_sequence
md=re.findall(r'\d+', [tag[1] for tag in line.tags if tag[0]=='MD'][0]) #get md tag
if len(md) == 1 : # if there are no mismatches
oBAM.write(line) # write the alignment into the output file
<!-- else: -->
<!-- if (not line.is_reverse) and (int(md[0]) >= 6): # if the first mismatch occurs after the 6th nt (from the 5' end) -->
<!-- oBAM.write(line) # write the alignment into the output file -->
<!-- elif (line.is_reverse) and (int(md[-1]) >= 6): # same as above but for reads that align to the reverse strand -->
<!-- oBAM.write(line) -->
# close files
iBAM.close()
oBAM.close()
Try to not use the cigar string method. Just look at the mapped reads.
#!/usr/bin/env python
"""
Usage: python filter6As.py <input_bam> <output_bam>
"""
import sys, pysam, re
iBAM = pysam.Samfile('/project2/gilad/briana/threeprimeseq/data/sort/YL-SP-19257-T_S25_R1_001-sort.bam', 'r') # reads from the standard input
oBAM = pysam.Samfile('test.bam', 'w', template=iBAM) # output
for line in iBAM:
seq=line.query_alignment_sequence
Aseq=re.compile("AAAAAA")
if len(re.findall(Aseq, seq))>=1:
oBAM.write(line)
iBAM.close()
oBAM.close()
What I need to do is combine both of these ideas. I need to test for mismatches using the cigar string, then extract the sequence and test for the multiple As in that section. I could seperate the alligned sequence and the coresponding cigar sequence into a list of tuples. Then I can find the largest mapping section, test for the mismatches and sequence of AAAAAs in this section.
Try on /project2/gilad/briana/threeprimeseq/data/sort/YL-SP-19257-T_S25_R1_001-sort.bam
An alternative way to think about this is that we expect directly upstream of the read to be 6 A’s. I am going to write a script that changes the bed file to give me the 6 basepairs before the read. This is start -6 to start on the fwd strand and end to encd +6 on rhe reverse strand. I can then use the bedtools nuc tool for these. I will filter the lines that have 100% As on the fwd strand and 100% Ts on the rev strand.
Script to look at positions upstream 6 bases. 6up_bed.sh
#!/bin/bash
#SBATCH --job-name=6upbed
#SBATCH --time=8:00:00
#SBATCH --output=6upbed.out
#SBATCH --error=6upbed.err
#SBATCH --account=pi-yangili1
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
#imput sorted bed file
bed=$1
describer=$(echo ${bed} | sed -e 's/.*\YL-SP-//' | sed -e "s/-sort.bed$//")
awk '{if($6== "+") print($1 "\t" $2-6 "\t" $2 "\t" $4 "\t" $5 "\t" $6 ); else print($1 "\t" $3 "\t" $3 + 6 "\t" $4 "\t" $5 "\t" $6)}' $1 | awk '{if($2 <0) print($1 "\t" "0" "\t" $3 "\t" $4 "\t" $5 "\t" $6) ; else print($1 "\t" $2 "\t" $3"\t" $4 "\t" $5 "\t" $6)}' > /project2/gilad/briana/threeprimeseq/data/bed_6up/sixup.${describer}.6up.sort.bed
Write wrapper w_6up.sh:
#!/bin/bash
#SBATCH --job-name=w_6up
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=w_6up.out
#SBATCH --error=w_6up.err
#SBATCH --partition=broadwl
#SBATCH --mem=8G
#SBATCH --mail-type=END
for i in $(ls /project2/gilad/briana/threeprimeseq/data/bed_sort/*.bed); do
sbatch 6up_bed.sh $i
done
Write the nuc script:
#!/bin/bash
#SBATCH --job-name=nuc6up
#SBATCH --account=pi-yangili1
#SBATCH --time=8:00:00
#SBATCH --output=nuc6up.out
#SBATCH --error=nuc6up.err
#SBATCH --partition=broadwl
#SBATCH --mem=20G
#SBATCH --mail-type=END
module load Anaconda3
source activate three-prime-env
#imput 6up sorted bed file
bed=$1
describer=$(echo ${bed} | sed -e 's/.*sixup.//' | sed -e "s/.6up.sort.bed$//")
bedtools nuc -s -fi /project2/gilad/briana/genome_anotation_data/genome/Homo_sapiens.GRCh37.75.dna_sm.all.fa -bed $1 > /project2/gilad/briana/threeprimeseq/data/nuc_6up/sixupnuc.${describer}.bed
test with /project2/gilad/briana/threeprimeseq/data/bed_6up/sixup.18486-N_S10_R1_001.6up.sort.bed
Error: malformed BED entry at line 5671859. Start was greater than end. Exiting. The problem is adding 6 on the end goes outisde the boundaries of the chromosome. I need the lengths of the chromosomes and I need to check for this when I make the file.
The hacky way will be to seperate the into seperate chromosomes and check both ends, then put back together.
6308726 - 5671859
sessionInfo()
R version 3.4.2 (2017-09-28)
Platform: x86_64-apple-darwin15.6.0 (64-bit)
Running under: macOS Sierra 10.12.6
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/3.4/Resources/lib/libRlapack.dylib
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_0.12.17 digest_0.6.15
[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_1.2.2 whisker_0.3-2 R.oo_1.22.0
[13] R.utils_2.6.0 rmarkdown_1.8.5 tools_3.4.2
[16] stringr_1.3.1 yaml_2.1.19 compiler_3.4.2
[19] htmltools_0.3.6 knitr_1.18
This reproducible R Markdown analysis was created with workflowr 1.0.1