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FILTUS: a desktop GUI for fast and efficient detection of disease-causing variants, including a novel autozygosity detector
- Source :
- Bioinformatics
- Publication Year :
- 2016
- Publisher :
- Oxford University Press (OUP), 2016.
-
Abstract
- Summary: FILTUS is a stand-alone tool for working with annotated variant files, e.g. when searching for variants causing Mendelian disease. Very flexible in terms of input file formats, FILTUS offers efficient filtering and a range of downstream utilities, including statistical analysis of gene sharing patterns, detection of de novo mutations in trios, quality control plots and autozygosity mapping. The autozygosity mapping is based on a hidden Markov model and enables accurate detection of autozygous regions directly from exome-scale variant files. Availability and implementation: FILTUS is written in Python and runs on Windows, Mac and Linux. Binaries and source code are freely available at http://folk.uio.no/magnusv/filtus.html and on GitHub: https://github.com/magnusdv/filtus. Automatic installation is available via PyPI (e.g. pip install filtus). Contact: magnusdv@medisin.uio.no Supplementary information: Supplementary data are available at Bioinformatics online.
- Subjects :
- 0301 basic medicine
Statistics and Probability
Source code
Downstream (software development)
Zygote
Computer science
media_common.quotation_subject
030105 genetics & heredity
Mendelian disease
computer.software_genre
Biochemistry
03 medical and health sciences
Humans
Exome
Molecular Biology
Gene
De novo mutations
computer.programming_language
media_common
Detector
Python (programming language)
File format
Applications Notes
Computer Science Applications
Computational Mathematics
030104 developmental biology
Computational Theory and Mathematics
Programming Languages
Data mining
Data and Text Mining
computer
Software
Subjects
Details
- ISSN :
- 13674811 and 13674803
- Volume :
- 32
- Database :
- OpenAIRE
- Journal :
- Bioinformatics
- Accession number :
- edsair.doi.dedup.....8cbaa53caa40be18511165235fe5f1c7
- Full Text :
- https://doi.org/10.1093/bioinformatics/btw046