NAME

Bio::ViennaNGS - A Perl extension for Next-Generation Sequencing data analysis

SYNOPSIS

use Bio::ViennaNGS;

# split a single-end  or paired-end BAM file by strands
@result = split_bam($bam_in,$rev,$want_uniq,$want_bed,$destdir,$logfile);

# extract unique and multi mappers from a BAM file
@result = uniquify_bam($bam_in,$outdir,$logfile);

# make bigWig from BED or BAM
$type = "bam";
$strand = "+";
$bwfile = bed_or_bam2bw($type,$infile,$cs_in,$strand,$destdir,$wantnorm,$size_p,$scale,$logfile);

# make bigBed from BED
my $bb = bed2bigBed($bed_in,$cs_in,$destdir,$logfile);

# sort a BED file 
sortbed($bed_in,$destdir,$bed_out,$rm_orig,$logfile)

# compute transcript abundance in TPM
$meanTPM = computeTPM($sample,$readlength);

# parse a bedtools multicov compatible file
$conds = parse_multicov($infile);

# write bedtools multicov compatible file
write_multicov("TPM",$destdir,$basename);

DESCRIPTION

Bio::ViennaNGS is a collection of utilities and subroutines for building efficient Next-Generation Sequencing (NGS) data analysis pipelines.

ROUTINES

split_bam($bam,$reverse,$want_uniq,$want_bed,$dest_dir,$log)

Splits BAM file $bam according to [+] and [-] strand. $reverse, $want_uniq and $want_bed are switches with values of 0 or 1, triggering forced reversion of strand mapping (due to RNA-seq protocol constraints), filtering of unique mappers (identified via NH:i:1 SAM argument), and forced output of a BED file corresponding to strand-specific mapping, respectively. $log holds name and path of the log file.

Strand-splitting is done in a way that in paired-end alignments, FIRST and SECOND mates (reads) are treated as _one_ fragment, ie FIRST_MATE reads determine the strand, while SECOND_MATE reads are assigned the opposite strand per definitionem. This also holds if the reads are not mapped in proper pairs and even if there is no mapping partner at all.

Sometimes the library preparation protocol causes inversion of the read assignment (with respect to the underlying annotation). In those cases, the natural mapping of the reads can be obtained by the $reverse flag.

This routine returns an array whose fist two elements are the file names of the newly generate BAM files with reads mapped to the positive, and negative strand, respectively. Elements three and four are the number of fragments mapped to the positive and negative strand. If the $want_bed option was given elements fiveand six are the file names of the output BED files for positive and negative strand, respectively.

NOTE: Filtering of unique mappers is only safe for single-end experiments; In paired-end experiments, read and mate are treated separately, thus allowing for scenarios where eg. one read is a multi-mapper, whereas its associate mate is a unique mapper, resulting in an ambiguous alignment of the entire fragment.

uniquify_bam($bam,$dest,$log)

Extract unique and multi mapping reads from BAM file $bam. New BAM files for unique and multi mappers are created in the output folder $dest, which are named basename.uniq.bam and basename.mult.bam, respectively. If defined, a logfile named $log is created in the output folder.

This routine returns an array holding file names of the newly created BAm files for unique and multi mappers, respectively.

bed_or_bam2bw($type,$infile,$chromsizes,$strand,$dest,$want_norm,$size,$scale,$log)

Creates stranded, normalized BigWig coverage profiles from strand-specific BAM or BED files (provided via $infile). The routine expects a file type 'bam' or 'bed' via the $type argument. $chromsizes is the chromosome.sizes files, $strand is either "+" or "-" and $dest contains the output path for results. For normlization of bigWig profiles, additional attributes are required: $want_norm triggers normalization with values 0 or 1. $size is the number of fragments/elements in the BAM or BED file and $scale gives the number to which data is normalized (ie. every bedGraph entry is multiplied by a factor ($scale/$size). $log is expected to contain either the full path and file name of log file or 'undef'. The routine returns the full file name of the newly generated bigWig file.

While this routine can handle non-straned BAM/BED files (in which case $strand should be set to "+" and hence all coverage profiles will be created with a positive sign, even if they map to the negative strand), usage of strand-specific data is highly recommended. For BAM file, this is easily achieved by calling the bam_split routine (see above) prior to this one, thus creating dedicated BAM files containing exclusively reads mapped to the positive or negative strand, respectively.

It is important to know that this routine does not extract reads mapped to either strand from a non-stranded BAM/BED file if the $strand argument is given. It rather adjusts the sign of all mapped reads/features in a BAM/BED file and then creates bigWig files. See the split_bam routine for extracting reads mapped to either strand.

Stranded bigWigs can easily be visualized via TrackHubs in the UCSC Genome Browser. Internally, the conversion from BAM/BED to bigWig is accomplished via two third-party applications: genomeCoverageBed and bedGraphToBigWig. Intermediate bedGraph files are removed automatically once the bigWig files are ready.

sortbed($infile,$dest,$outfile,$rm_orig,$log)

Sorts BED file $infile with bedtools sortt. $dest and outfile name path and filename of the resulting sorted BED file. $rm_infile is either 1 or 0 and indicated whether the original $infile should be deleted. $log holds path and name of log file.

bed2bigBed($infile,$chromsizes,$dest,$log)

Creates an indexed bigBed file from a BED file. $infile is the BED file to be transformed, $chromsizes is the chromosome.sizes file and $dest contains the output path for results. $log is the name of a log file, or undef if no logging is reuqired. A '.bed', '.bed6' or '.bed12' suffix in $infile will be replace by '.bb' in the output. Else, the name of the output bigBed file will be the value of $infile plus '.bb' appended.

The conversion from BED to bigBed is done by a third-party utility (bedToBigBed), which is executed by IPC::Cmd.

computeTPM($featCount_sample,$rl)

Computes expression in Transcript per Million (TPM) [Wagner et.al. Theory Biosci. (2012)]. $featCount_sample is a reference to a Hash of Hashes data straucture where keys are feature names and values hold a hash that must at least contain length and raw read counts. Practically, $featCount_sample is represented by _one_ element of @featCount, which is populated from a multicov file by parse_multicov(). $rl is the read length of the sequencing run.

Returns the mean TPM of the processed sample, which is invariant among samples. (TPM models relative molar concentration and thus fulfills the invariant average criterion.)

parse_multicov($file)

Parse a bedtools multicov (multiBamCov) file, i.e. an extended BED6 file, into an Array of Hash of Hashes data structure (@featCount). $file is the input file. Returns the number of samples present in the multicov file, ie. the numner of columns extending the canonical BED6 columns in the input multicov file.

write_multicov($item,$dest_dir,$base_name)

Write @featCount data to a bedtools multicov (multiBamCov)-type file. $item specifies the type of information from @featCount HoH entries, e.g. TPM or RPKM. These values must have been computed and inserted into @featCount beforehand by e.g. computeTPM(). $dest_dir gives the absolute path and $base_name the basename (will be extended by $item.csv) of the output file.

DEPENDENCIES

Bio::Perl >= 1.00690001

BIO::DB::Sam >= 1.39

File::Basename

File::Temp

Path::Class

IPC::Cmd

Carp

Bio::ViennaNGS uses third-party tools for computing intersections of BED files: bedtools intersect from the BEDtools suite is used to compute overlaps and bedtools sort is used to sort BED output files. Make sure that those third-party utilities are available on your system, and that hey can be found and executed by the Perl interpreter. We recommend installing the latest version of BEDtools on your system.

SEE ALSO

Bio::ViennaNGS::AnnoC

Bio::ViennaNGS::UCSC

Bio::ViennaNGS::SpliceJunc

Bio::ViennaNGS::Fasta

Bio::ViennaNGS::FeatureChain

AUTHORS

Michael T. Wolfinger <michael@wolfinger.eu>

Jörg Fallmann <fall@tbi.univie.ac.at>

Florian Eggenhofer <florian.eggenhofer@tbi.univie.ac.at>

Fabian Amman <fabian@tbi.univie.ac.at<gt>

COPYRIGHT AND LICENSE

Copyright (C) 2014 Michael T. Wolfinger <michael@wolfinger.eu>

This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself, either Perl version 5.12.4 or, at your option, any later version of Perl 5 you may have available.

This software is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.