Bio::ViennaNGS - A Perl distribution for Next-Generation Sequencing (NGS) data analysis


Bio::ViennaNGS is a distribution of Perl modules and utilities for building efficient Next-Generation Sequencing (NGS) analysis pipelines. It covers various aspects of NGS data analysis, including (but not limited to) conversion of sequence annotation, evaluation of mapped data, expression quantification and visualization.

The main Bio::ViennaNGS module is shipped with a complementary set of (sub)modules:

Bio::ViennaNGS::AnnoC: A Moose interface for storage and conversion of sequence annotation data.
Bio::ViennaNGS::Bam: Routines for high-level manipulation of BAM files.
Bio::ViennaNGS::Bed: A Moose interface for manipulation of genomic interval data in BED format.
Bio::ViennaNGS::BedGraphEntry: A Moose interface for storing genomic cvoerage and interval data in bedGraph format.
Bio::ViennaNGS::Expression: An object oriented interface for read-count based gene expression analysis.
Bio::ViennaNGS::ExtFeature: A Moose wrapper for extended BED6 entries.
Bio::ViennaNGS::Fasta: Routines for accessing genomic sequences implemented through a Moose interface to Bio::DB::Fasta.
Bio::ViennaNGS::Feature: A Moose based BED6 wrapper.
Bio::ViennaNGS::FeatureChain: Yet another Moose class for chaining gene annotation features.
Bio::ViennaNGS::FeatureInterval: A Moose interface for handling elementary genomic intervals, corresponding to BED3.
Bio::ViennaNGS::FeatureIntervalN: A Moose interface for handling named genomic intervals.
Bio::ViennaNGS::FeatureIO: A Moose interface for efficient input/output handling of genomic annotation formats.
Bio::ViennaNGS::FeatureLine: An abstract Moose class for combining several Bio::ViennaNGS::FeatureChain objects.
Bio::ViennaNGS::MinimalFeature: A Moose interface for handling elementary gene annotation, corresponding to BED4.
Bio::ViennaNGS::Peak: A Moose interface for identification and characterization of peaks/enriched regions in RNA-seq data.
Bio::ViennaNGS::SpliceJunc: A collection of routines for alternative splicing analysis.
Bio::ViennaNGS::Subtypes: Moose subtypes for internal usage.
Bio::ViennaNGS::Tutorial: A comprehensive tutorial of the Bio::ViennaNGS core routines with real-world NGS data.
Bio::ViennaNGS::UCSC: Routines for visualization of genomics data with the UCSC genome browser.
Bio::ViennaNGS::Util: A collection of wrapper routines for commonly used third-party NGS utilities, code for normalization of gene expression values based on read count data and a set of utility functions.


Bio::ViennaNGS comes with a collection of command line utilities for accomplishing routine tasks often required in NGS data processing. These utilities serve as reference implementation of the routines implemented throughout the modules and can readily be used for atomic tasks in NGS data processing: The UCSC genome browser offers the possibility to visualize any organism (including organisms that are not included in the standard UCSC browser bundle) through hso called 'Assembly Hubs'. This script constructs Assembly Hubs from genomic sequence and annotation data. Split (paired-end and single-end) BAM alignment files by strand and compute statistics. Optionally create BED output, as well as normalized bedGraph and bigWig files for coverage visualization in genome browsers (see dependencies on third-patry tools below). Produce bigWig coverage profiles from (aligned) BAM files, explicitly considering strandedness. The most natural use case of this tool is to create strand-aware coverage profiles in bigWig format for genome browser visualization. Extract unique and multi mapping reads from BAM alignment files and create a separate BAM file for both uniqe (.uniq.) and multi (.mult.) mappers. Convert BED files to (strand specific) bedGraph files, allowing additional annotation and automatic generation of bedGraph files which can easily be converted to big-type files for easy UCSC visualization. Provide nucleotide and amino acid sequences for BED6 intervals. A simple BED6 -> BED12 converter. Extract indivudual (whole) sequences from a multi Fasta file. Extract subsequences from (multi) Fasta files. Convert RefSeq GFF3 annotation files to BED12 format. Individual BED12 files are created for each feature type (CDS/tRNA/rRNA/etc.). Tested with RefSeq bacterial GFF3 annotation. Count k-mers of predefined length in FastQ and Fasta files Compute simple statistics from MEME XML output and return a list of found motifs with the number of sequences containing those motifs as well as nice ggplot graphs. Create a new genome database to a locally installed instance of the UCSC genome browser in order to add a novel organism for visualization. Based on this Genomewiki article. Compute normalized expression data in RPKM and TPM from (raw) read counts in bedtools multicov format. TPM reference: Wagner et al, Theory Biosci. 131(4), pp 281-85 (2012). Find and characterize peaks/enriched regions of certain size and coverage in RNA-seq data. Convert splice junctions from mapped RNA-seq data in segemehl BED6 splice junction format to BED12 for easy visualization in genome Browsers. Identify and characterize splice junctions from RNA-seq data by intersecting them with annotated splice junctions. Analogous to, construct a Track Hub for an organism listed in the UCSC Genome Browser. Trim sequence and quality string fields in a Fastq file by user defined length.


The Bio::ViennaNGS modules and classes depend on a set of Perl modules, some of which are part of the Perl core distribution, most notably Bio::Perl >= 1.00690001 and Bio::DB::Sam >= 1.37.

In addition, Bio::ViennaNGS depends on third-party tools and libraries which are required for specific filtering and file format conversion tasks as well as for building internally used Perl modules:

bedGraphToBigWig, fetchChromSizes, faToTwoBit from the UCSC Genome Browser applications
samtools <=v0.1.19 for building Bio::DB::Sam.

Please ensure that all third-party utilities are available on your system, and that hey can be found and executed by the Perl interpreter.


Source code for this distribution is available from the ViennaNGS Github repository.

A pre-compiled binary distribution for Linux and MacOS is available from Bioconda, e.g. via conda install perl-bio-viennangs.


If the Bio::ViennaNGS suite is useful for your work or if you use any component of the distribution in a custom pipeline, please cite the following publication:

 "ViennaNGS - A toolbox for building efficient next-generation
 sequencing analysis pipelines"
 Michael T. Wolfinger, Joerg Fallmann, Florian Eggenhofer and Fabian
 Amman; F1000Research (2015), 4:50

doi: 10.12688/f1000research.6157.2)


The Bio::ViennaNGS suite is actively developed and tested on different flavours of Linux and Mac OS X. We have taken care of writing platform-independent code that should run out of the box on most UNIX-based systems, however we do not have access to machines running Microsoft Windows. As such, we have not tested and will not test Windows compatibility.




Michael T. Wolfinger <>
Joerg Fallmann <>
Florian Eggenhofer <>
Fabian Amman <<gt>


Copyright (C) 2014-2018 Michael T. Wolfinger <>

This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself, either Perl version 5.10.0 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.