BIOAWK – biological data manipulation

DataScience Workbook / 03: Introduction to Command Line / 3. Useful text manipulation programs / 3.4. BIOAWK – biological data manipulation

Introduction

Bioawk is an extension of the UNIX core utility command awk. It provides several features for biological data manipulation in a similar way as that of awk. This tutorial will give a brief introduction and examples for some common tasks that can be done with this command.

Bioawk is developed by Heng Li. You can download and install it from the Git repository. On Lightning3/Condo, it has already been installed, just load the bioawk module to start using it.

Features

• It can automatically recognize some popular formats and will parse different features associated with those formats. The format option is passed to bioawk using -carg flag. Here arg can be bed, sam, vcf, gff or fastx (for both fastq and FASTA). It can also deal with other types of table formats using the -c header option. When header is specified, the field names will used for variable names, thus greatly expanding the utility.
• There are several builtin functions (other than the standard awk built-ins), that are specific to biological file formats. When a format is read with bioawk, the fields get automatically parsed. You can apply several functions on these variables to get the desired output. Let’s say, we read fasta format, now we have $name and $seq that holds sequence name and sequence respectively. You can use the print function (awk builtin) to print $name and $seq. You can also use bioawk built-in with the print function to get length, reverse complement etc by just using '{print length($seq)}'. Other functions include reverse, revcomp, trimq, and, or, xor etc.
• It can automatically read gzipped/compressed files

Options

• -t to set input and output filed separator as tab
• -cfmt to read and parse the file in desired format
• -vvar=value initialize a variable and value [std to awk as well]
• -H retain header in the output file (for files like SAM)
• And all standard awk flags will work with bioawk

Variables for each format

For the -c you can either specify bed, sam, vcf, gff, fastx or header. Bioawk will parse these variables for the respective format

bed	sam	vcf	gff	fastx
chrom	qname	chrom	seqname	name
start	flag	pos	source	seq
end	rname	id	feature	qual
name	pos	ref	start	comment
score	mapq	alt	end
strand	cigar	qual	score
thickstart	rnext	filter	filter
thickend	pnext	info	strand
rgb	tlen	group
blockcount	seq	attribute
blocksizes	qual
blockstarts

If -c header is specified, the field names (first line) will be used as variables (spaces and special character will be changed to under_score).

1. For FASTA files

Once the input file is read, the defline for the FASTA will be $name variable and the sequence will be $seq variable. you can use any of the standard awk functions on these as well as the bioawk functions. Some_eg.,_

Get length for sequences

bioawk -c fastx '{ print $name, length($seq) }' input.fasta

Get %GC for sequences

bioawk -c fastx '{ print $name, gc($seq) }' input.fasta

Get reverse complement for all sequences

bioawk -c fastx '{ print ">"$name;print revcomp($seq) }' input.fasta

Print sequences with length greater than 100 bases

bioawk -c fastx 'length($seq) > 100{ print ">"$name; print $seq }'  input.fasta

Add a prefix/suffix to the sequence defline

bioawk -c fastx '{ print ">PREFIX"$name; $seq }' input.fasta
bioawk -c fastx '{ print ">"$name"|SUFFIX"; $seq }' input.fasta

Convert FASTA to tabular format

bioawk -t -c fastx '{ print $name, $seq }' input.fasta

Extract sequences based on ids in a file

#for large scale use cdbyank instead
bioawk -cfastx 'BEGIN{while((getline k <"IDs.txt")>0)i[k]=1}{if(i[$name])print ">"$name"\n"$seq}' input.fasta

These are just some examples, we can do many more with other standard awk functions.

2. For fastq files

Here, the -c fastx option remains same but bioawk will automatically recognize the fastq format and build the required variables, such as $name $seq $qual and $comment

Count the number of records (reads)

bioawk -t -c fastx 'END {print NR}' input.fastq
# note that when fastq is specified, each record is 4 lines

Convert fastq to FASTA

bioawk -c fastx '{print ">"$name; print $seq}' input.fastq

Get the mean Phred quality score from fastq

bioawk -c fastx '{print ">"$name; print meanqual($qual)}' input.fastq

Filter reads shorter than 10 bp (or any bp)

bioawk -cfastx 'length($seq) > 10 {print "@"$name"\n"$seq"\n+\n"$qual}' input.fastq

Trim fastq files based on quality

bioawk -c fastx ' trimq(30, 0, 5){print $0}' input.fastq
# trims fastq bases 0 to 5 (beginning to end), scores less than 30.

3. For BED files

Print the feature length

bioawk -c bed '{ print $end - $start }' test.bed

4. For SAM files

Extract unmapped reads

bioawk -c sam 'and($flag,4)' input.sam

Extract mapped reads

bioawk -c sam -H '!and($flag,4)' input.sam

Create FASTA from SAM

bioawk -c sam '{ s=$seq; if(and($flag, 16)) {s=revcomp($seq) } print ">"$qname"\n"s}' input.sam > output.fasta

5. For VCF files

Print the genotypes of sample foo and bar from a VCF

grep -v ^## in.vcf | bioawk -tc hdr '{print $foo,$bar}'

6. For GFF files

Will be added soon!

7. For other types of files

Say, if your input file is as follows:

name	phone	email	age
Joe	6407	a@g.com	24
Doe	4506	b@g.com	26

List records less than 25 years age

bioawk -t -c header '$age < "25" {print $0}' input.txt

Further Reading

DIFF, COMM, CMP – comparing and collating two files with Unix
UNIX Commands

MODULE 04: Development Environment