Useful bash one-liners useful for bioinformatics (and some, more generally useful).
- Sources
- Basic awk & sed
- awk & sed for bioinformatics
- sort, uniq, cut, etc.
- find, xargs, and GNU parallel
- seqtk
- GFF3 Annotations
- Other generally useful aliases for your .bashrc
- Etc.
- http://gettinggeneticsdone.blogspot.com/2013/10/useful-linux-oneliners-for-bioinformatics.html#comments
- http://sed.sourceforge.net/sed1line.txt
- https://github.com/lh3/seqtk
- http://lh3lh3.users.sourceforge.net/biounix.shtml
- http://genomespot.blogspot.com/2013/08/a-selection-of-useful-bash-one-liners.html
- http://biowize.wordpress.com/2012/06/15/command-line-magic-for-your-gene-annotations/
- http://genomics-array.blogspot.com/2010/11/some-unixperl-oneliners-for.html
- http://bioexpressblog.wordpress.com/2013/04/05/split-multi-fasta-sequence-file/
- http://www.commandlinefu.com/
Extract fields 2, 4, and 5 from file.txt:
awk '{print $2,$4,$5}' input.txt
Print each line where the 5th field is equal to ‘abc123’:
awk '$5 == "abc123"' file.txt
Print each line where the 5th field is not equal to ‘abc123’:
awk '$5 != "abc123"' file.txt
Print each line whose 7th field matches the regular expression:
awk '$7 ~ /^[a-f]/' file.txt
Print each line whose 7th field does not match the regular expression:
awk '$7 !~ /^[a-f]/' file.txt
Get unique entries in file.txt based on column 2 (takes only the first instance):
awk '!arr[$2]++' file.txt
Print rows where column 3 is larger than column 5 in file.txt:
awk '$3>$5' file.txt
Sum column 1 of file.txt:
awk '{sum+=$1} END {print sum}' file.txt
Compute the mean of column 2:
awk '{x+=$2}END{print x/NR}' file.txt
Replace all occurances of foo with bar in file.txt:
sed 's/foo/bar/g' file.txt
Trim leading whitespaces and tabulations in file.txt:
sed 's/^[ \t]*//' file.txt
Trim trailing whitespaces and tabulations in file.txt:
sed 's/[ \t]*$//' file.txt
Trim leading and trailing whitespaces and tabulations in file.txt:
sed 's/^[ \t]*//;s/[ \t]*$//' file.txt
Delete blank lines in file.txt:
sed '/^$/d' file.txt
Delete everything after and including a line containing EndOfUsefulData:
sed -n '/EndOfUsefulData/,$!p' file.txt
Remove duplicates while preserving order
awk '!visited[$0]++' file.txt
Returns all lines on Chr 1 between 1MB and 2MB in file.txt. (assumes) chromosome in column 1 and position in column 3 (this same concept can be used to return only variants that above specific allele frequencies):
cat file.txt | awk '$1=="1"' | awk '$3>=1000000' | awk '$3<=2000000'
Basic sequence statistics. Print total number of reads, total number unique reads, percentage of unique reads, most abundant sequence, its frequency, and percentage of total in file.fq:
cat myfile.fq | awk '((NR-2)%4==0){read=$1;total++;count[read]++}END{for(read in count){if(!max||count[read]>max) {max=count[read];maxRead=read};if(count[read]==1){unique++}};print total,unique,unique*100/total,maxRead,count[maxRead],count[maxRead]*100/total}'
Convert .bam back to .fastq:
samtools view file.bam | awk 'BEGIN {FS="\t"} {print "@" $1 "\n" $10 "\n+\n" $11}' > file.fq
Keep only top bit scores in blast hits (best bit score only):
awk '{ if(!x[$1]++) {print $0; bitscore=($14-1)} else { if($14>bitscore) print $0} }' blastout.txt
Keep only top bit scores in blast hits (5 less than the top):
awk '{ if(!x[$1]++) {print $0; bitscore=($14-6)} else { if($14>bitscore) print $0} }' blastout.txt
Split a multi-FASTA file into individual FASTA files:
awk '/^>/{s=++d".fa"} {print > s}' multi.fa
Output sequence name and its length for every sequence within a fasta file:
cat file.fa | awk '$0 ~ ">" {print c; c=0;printf substr($0,2,100) "\t"; } $0 !~ ">" {c+=length($0);} END { print c; }'
Convert a FASTQ file to FASTA:
sed -n '1~4s/^@/>/p;2~4p' file.fq > file.fa
Extract every 4th line starting at the second line (extract the sequence from FASTQ file):
sed -n '2~4p' file.fq
Print everything except the first line
awk 'NR>1' input.txt
Print rows 20-80:
awk 'NR>=20&&NR<=80' input.txt
Calculate the sum of column 2 and 3 and put it at the end of a row:
awk '{print $0,$2+$3}' input.txt
Calculate the mean length of reads in a fastq file:
awk 'NR%4==2{sum+=length($0)}END{print sum/(NR/4)}' input.fastq
Convert a VCF file to a BED file
sed -e 's/chr//' file.vcf | awk '{OFS="\t"; if (!/^#/){print $1,$2-1,$2,$4"/"$5,"+"}}'
Create a tab-delimited transcript-to-gene mapping table from a GENCODE GFF. The substr(x,s,n) returns n characters from string x starting from position s. This gets rid of the quotes and semicolon.
bioawk -c gff '$feature=="transcript" {print $group}' gencode.v28.annotation.gtf | awk -F ' ' '{print substr($4,2,length($4)-3) "\t" substr($2,2,length($2)-3)}' > txp2gene.tsv
extract specific reads from fastq file according to reads name :
zcat a.fastq.gz | awk 'BEGIN{RS="@";FS="\n"}; $1~/readsName/{print $2; exit}'
count missing sample in vcf file per line:
bcftools query -f '[%GT\t]\n' a.bcf | awk '{miss=0};{for (x=1; x<=NF; x++) if ($x=="./.") {miss+=1}};{print miss}' > nmiss.count
Interleave paired-end fastq files:
paste <(paste - - - - < reads-1.fastq) \
<(paste - - - - < reads-2.fastq) \
| tr '\t' '\n' \
> reads-int.fastq
Decouple an interleaved fastq file:
paste - - - - - - - - < reads-int.fastq \
| tee >(cut -f 1-4 | tr '\t' '\n' > reads-1.fastq) \
| cut -f 5-8 | tr '\t' '\n' > reads-2.fastq
Number each line in file.txt:
cat -n file.txt
Count the number of unique lines in file.txt
cat file.txt | sort -u | wc -l
Find lines shared by 2 files (assumes lines within file1 and file2 are unique; pipe to wd -l to count the number of lines shared):
sort file1 file2 | uniq -d
# Safer
sort -u file1 > a
sort -u file2 > b
sort a b | uniq -d
# Use comm
comm -12 file1 file2
Sort numerically (with logs) (g) by column (k) 9:
sort -gk9 file.txt
Find the most common strings in column 2:
cut -f2 file.txt | sort | uniq -c | sort -k1nr | head
Pick 10 random lines from a file:
shuf file.txt | head -n 10
Print all possible 3mer DNA sequence combinations:
echo {A,C,T,G}{A,C,T,G}{A,C,T,G}
Untangle an interleaved paired-end FASTQ file. If a FASTQ file has paired-end reads intermingled, and you want to separate them into separate /1 and /2 files, and assuming the /1 reads precede the /2 reads:
cat interleaved.fq |paste - - - - - - - - | tee >(cut -f 1-4 | tr "\t" "\n" > deinterleaved_1.fq) | cut -f 5-8 | tr "\t" "\n" > deinterleaved_2.fq
Take a fasta file with a bunch of short scaffolds, e.g., labeled >Scaffold12345, remove them, and write a new fasta without them:
samtools faidx genome.fa && grep -v Scaffold genome.fa.fai | cut -f1 | xargs -n1 samtools faidx genome.fa > genome.noscaffolds.fa
Display hidden control characters:
python -c "f = open('file.txt', 'r'); f.seek(0); file = f.readlines(); print file"
Download GNU parallel at https://www.gnu.org/software/parallel/.
Search for .bam files anywhere in the current directory recursively:
find . -name "*.bam"
Delete all .bam files (Irreversible: use with caution! Confirm list BEFORE deleting):
find . -name "*.bam" | xargs rm
Find the largest file in a directory:
find . -type f -printf '%s %p\n' | sort -nr | head -1 | cut -d' ' -f2-
Count the number of lines in all files with a specific extension in a directory
find . -type f -name '*.txt' -exec wc -l {} \; | awk '{total += $1} END {print total}'
Find all directories in the current directory that contain files with the extension ".log" and compress them into a tar archive:
find . -type f -name "*.log" -printf "%h\0" | sort -uz | xargs -0 tar -czvf logs.tar.gz
Rename all .txt files to .bak (backup *.txt before doing something else to them, for example):
find . -name "*.txt" | sed "s/\.txt$//" | xargs -i echo mv {}.txt {}.bak | sh
Chastity filter raw Illumina data (grep reads containing :N:, append (-A) the three lines after the match containing the sequence and quality info, and write a new filtered fastq file):
find *fq | parallel "cat {} | grep -A 3 '^@.*[^:]*:N:[^:]*:' | grep -v '^\-\-$' > {}.filt.fq"
Run FASTQC in parallel 12 jobs at a time:
find *.fq | parallel -j 12 "fastqc {} --outdir ."
Index your bam files in parallel, but only echo the commands (--dry-run) rather than actually running them:
find *.bam | parallel --dry-run 'samtools index {}'
Download seqtk at https://github.com/lh3/seqtk. Seqtk is a fast and lightweight tool for processing sequences in the FASTA or FASTQ format. It seamlessly parses both FASTA and FASTQ files which can also be optionally compressed by gzip.
Convert FASTQ to FASTA:
seqtk seq -a in.fq.gz > out.fa
Convert ILLUMINA 1.3+ FASTQ to FASTA and mask bases with quality lower than 20 to lowercases (the 1st command line) or to N (the 2nd):
seqtk seq -aQ64 -q20 in.fq > out.fa
seqtk seq -aQ64 -q20 -n N in.fq > out.fa
Fold long FASTA/Q lines and remove FASTA/Q comments:
seqtk seq -Cl60 in.fa > out.fa
Convert multi-line FASTQ to 4-line FASTQ:
seqtk seq -l0 in.fq > out.fq
Reverse complement FASTA/Q:
seqtk seq -r in.fq > out.fq
Extract sequences with names in file name.lst, one sequence name per line:
seqtk subseq in.fq name.lst > out.fq
Extract sequences in regions contained in file reg.bed:
seqtk subseq in.fa reg.bed > out.fa
Mask regions in reg.bed to lowercases:
seqtk seq -M reg.bed in.fa > out.fa
Subsample 10000 read pairs from two large paired FASTQ files (remember to use the same random seed to keep pairing):
seqtk sample -s100 read1.fq 10000 > sub1.fq
seqtk sample -s100 read2.fq 10000 > sub2.fq
Trim low-quality bases from both ends using the Phred algorithm:
seqtk trimfq in.fq > out.fq
Trim 5bp from the left end of each read and 10bp from the right end:
seqtk trimfq -b 5 -e 10 in.fa > out.fa
Untangle an interleaved paired-end FASTQ file. If a FASTQ file has paired-end reads intermingled, and you want to separate them into separate /1 and /2 files, and assuming the /1 reads precede the /2 reads:
seqtk seq -l0 -1 interleaved.fq > deinterleaved_1.fq
seqtk seq -l0 -2 interleaved.fq > deinterleaved_2.fq
Print all sequences annotated in a GFF3 file.
cut -s -f 1,9 yourannots.gff3 | grep $'\t' | cut -f 1 | sort | uniq
Determine all feature types annotated in a GFF3 file.
grep -v '^#' yourannots.gff3 | cut -s -f 3 | sort | uniq
Determine the number of genes annotated in a GFF3 file.
grep -c $'\tgene\t' yourannots.gff3
Extract all gene IDs from a GFF3 file.
grep $'\tgene\t' yourannots.gff3 | perl -ne '/ID=([^;]+)/ and printf("%s\n", $1)'
Print length of each gene in a GFF3 file.
grep $'\tgene\t' yourannots.gff3 | cut -s -f 4,5 | perl -ne '@v = split(/\t/); printf("%d\n", $v[1] - $v[0] + 1)'
FASTA header lines to GFF format (assuming the length is in the header as an appended "_length" as in Velvet assembled transcripts):
grep '>' file.fasta | awk -F "_" 'BEGIN{i=1; print "##gff-version 3"}{ print $0"\t BLAT\tEXON\t1\t"$10"\t95\t+\t.\tgene_id="$0";transcript_id=Transcript_"i;i++ }' > file.gff
Get a prompt that looks like user@hostname:/full/path/cwd/:$
export PS1="\u@\h:\w\\$ "
Never type cd ../../.. again (or use autojump, which enables you to navigate the filesystem faster):
alias ..='cd ..'
alias ...='cd ../../'
alias ....='cd ../../../'
alias .....='cd ../../../../'
alias ......='cd ../../../../../'
Browse 'up' and 'down'
alias u='clear; cd ../; pwd; ls -lhGgo'
alias d='clear; cd -; ls -lhGgo'
Ask before removing or overwriting files:
alias mv="mv -i"
alias cp="cp -i"
alias rm="rm -i"
My favorite ls aliases:
alias ls="ls -1p --color=auto"
alias l="ls -lhGgo"
alias ll="ls -lh"
alias la="ls -lhGgoA"
alias lt="ls -lhGgotr"
alias lS="ls -lhGgoSr"
alias l.="ls -lhGgod .*"
alias lhead="ls -lhGgo | head"
alias ltail="ls -lhGgo | tail"
alias lmore='ls -lhGgo | more'
Use cut on space- or comma- delimited files:
alias cuts="cut -d \" \""
alias cutc="cut -d \",\""
Pack and unpack tar.gz files:
alias tarup="tar -zcf"
alias tardown="tar -zxf"
Or use a generalized extract function:
# as suggested by Mendel Cooper in "Advanced Bash Scripting Guide"
extract () {
if [ -f $1 ] ; then
case $1 in
*.tar.bz2) tar xvjf $1 ;;
*.tar.gz) tar xvzf $1 ;;
*.tar.xz) tar Jxvf $1 ;;
*.bz2) bunzip2 $1 ;;
*.rar) unrar x $1 ;;
*.gz) gunzip $1 ;;
*.tar) tar xvf $1 ;;
*.tbz2) tar xvjf $1 ;;
*.tgz) tar xvzf $1 ;;
*.zip) unzip $1 ;;
*.Z) uncompress $1 ;;
*.7z) 7z x $1 ;;
*) echo "don't know how to extract '$1'..." ;;
esac
else
echo "'$1' is not a valid file!"
fi
}
Use mcd to create a directory and cd to it simultaneously:
function mcd { mkdir -p "$1" && cd "$1";}
Go up to the parent directory and list it's contents:
alias u="cd ..;ls"
Make grep pretty:
alias grep="grep --color=auto"
Refresh your .bashrc:
alias refresh="source ~/.bashrc"
Edit your .bashrc:
alias eb="vi ~/.bashrc"
Common typos:
alias mf="mv -i"
alias mroe="more"
alias c='clear'
alias emacs='vim'
Show your $PATH in a prettier format:
alias showpath='echo $PATH | tr ":" "\n" | nl'
Use pandoc to convert a markdown file to PDF:
# USAGE: mdpdf document.md document.md.pdf
alias mdpdf="pandoc -s -V geometry:margin=1in -V documentclass:article -V fontsize=12pt"
Find text in any file (ft "mytext" *.txt):
function ft { find . -name "$2" -exec grep -il "$1" {} \;; }
Run the last command as root:
sudo !!
Place the argument of the most recent command on the shell:
'ALT+.' or '<ESC> .'
Type partial command, kill this command, check something you forgot, yank the command, resume typing:
<CTRL+u> [...] <CTRL+y>
Jump to a directory, execute a command, and jump back to the current directory:
(cd /tmp && ls)
Stopwatch (Enter or ctrl-d to stop):
time read
Create a script of the last executed command:
echo "!!" > foo.sh
Reuse all parameter of the previous command line:
!*
List or delete all files in a folder that don't match a certain file extension (e.g., list things that are not compressed; remove anything that is not a .foo or .bar file):
ls !(*.gz)
rm !(*.foo|*.bar)
Insert the last command without the last argument:
!:- <new_last_argument>
Rapidly invoke an editor to write a long, complex, or tricky command:
fc
Print a specific line (e.g. line 42) from a file:
sed -n 42p <file>
Terminate a frozen SSH session (enter a new line, type the ~ key then the . key):
[ENTER]~.
Remove blank lines from a file using grep and save output to new file:
grep . filename > newfilename
Find large files (e.g., >500M):
find . -type f -size +500M
Exclude a column with cut (e.g., all but the 5th field in a tab-delimited file):
cut -f5 --complement
Find files containing text (-l outputs only the file names, -i ignores the case -r descends into subdirectories)
grep -lir "some text" *
