http://www-huber.embl.de/HTSeqHTSeq: Analysing high-throughput sequencing data with Python¶HTSeq is a Python package that provides infrastructure to process datafrom high-throughput sequencing assays.
- Please see the chapter A tour through HTSeq first for an overview on the kind of analysisyou can do with HTSeq and the design of the package, and then look at the referencedocumentation.
- While the main purpose of HTSeq is to allow you to write your own analysis scripts,customized to your needs, there are also a couple of stand-alone scripts forcommon tasks that can be used without any Python knowledge. See the Scriptssection in the overview below for what is available.
Paper¶HTSeq is described in the following publication:
Simon Anders, Paul Theodor Pyl, Wolfgang Huber
HTSeq — A Python framework to work with high-throughput sequencing dataBioinformatics (2014), in print, online at
doi:10.1093/bioinformatics/btu638If you use HTSeq in research, please cite this paper in your publication.
Documentation overview¶Prequisites and installationDownload links and installation instructions can be found here
A tour through HTSeqThe Tour shows you how to get started. It explains how to install HTSeq, and thendemonstrates typical analysis steps with explicit examples. Read this first, andthen see the Reference for details.
A detailed use case: TSS plotsThis chapter explains typical usage patterns for HTSeq by explaining in detailthree different solutions to the same programming task.
Counting readsThis chapter explorer in detail the use case of counting the overlap of readswith annotation features and explains how to implement custom logic bywriting on’s own customized counting scriptsReference documentation
The various classes of
HTSeq are described here.
Reference overviewA brief overview over all classes.
Sequences and FASTA/FASTQ filesIn order to represent sequences and reads (i.e., sequences with base-call qualityinformation), the classes
Sequence and
SequenceWithQualities are used.The classes
FastaReader and
FastqReader allow to parse FASTA and FASTQfiles.
Genomic intervals and genomic arraysThe classes
GenomicInterval and
GenomicPosition represent intervals andpositions in a genome. The class
GenomicArray is an all-purpose containerwith easy access via a genomic interval or position, and
GenomicArrayOfSetsis a special case useful to deal with genomic features (such as genes, exons,etc.)
Read alignmentsTo process the output from short read aligners in various formats (e.g., SAM),the classes described here are used, to represent output files and alignments,i.e., reads with their alignment information.
FeaturesThe classes
GenomicFeature and
GFF_Reader help to deal with genomicannotation data.
Other parsersThis page describes classes to parse VCF, Wiggle and BED files.
Scripts
The following scripts can be used without any Python knowledge.
Quality Assessment with htseq-qaGiven a FASTQ or SAM file, this script produces a PDF file with plots depictingthe base calls and base-call qualities by position in the read. This is useful toassess the technical quality of a sequencing run.
Counting reads in features with htseq-countGiven a SAM file with alignments and a GFF file with genomic features, this scriptcounts how many reads map to each feature.[/list]
Author¶HTSeq is developed by
Simon Anders at
EMBL Heidelberg (
Genome BiologyUnit). Please do not hesitate to contact me (anders
at embl
dot de) if youhave any comments or questions.
License¶HTSeq is free software: you can redistribute it and/or modifyit under the terms of the GNU General Public License as published bythe Free Software Foundation, either version 3 of the License, or(at your option) any later version.
This program is distributed in the hope that it will be useful,but WITHOUT ANY WARRANTY; without even the implied warranty ofMERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.See theGNU General Public License for more details.
The full text of the GNU General Public License, version 3, can be foundhere:
http://www.gnu.org/licenses/gpl-3.0-standalone.htmlTable Of Contents[/list]
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