An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors. Issue 1 (December 2015)
- Record Type:
- Journal Article
- Title:
- An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors. Issue 1 (December 2015)
- Main Title:
- An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors
- Authors:
- Broeckx, Bart
Coopman, Frank
Verhoeven, Geert
Bosmans, Tim
Gielen, Ingrid
Dingemanse, Walter
Saunders, Jimmy
Deforce, Dieter
Van Nieuwerburgh, Filip - Abstract:
- Abstract Background Identification of one or several disease causing variant(s) from the large collection of variants present in an individual is often achieved by the sequential use of heuristic filters. The recent development of whole exome sequencing enrichment designs for several non-model species created the need for a species-independent, fast and versatile analysis tool, capable of tackling a wide variety of standard and more complex inheritance models. With this aim, we developed "Mendelian", an R-package that can be used for heuristic variant filtering. Results The R-package Mendelian offers fast and convenient filters to analyze putative variants for both recessive and dominant models of inheritance, with variable degrees of penetrance and detectance. Analysis of trios is supported. Filtering against variant databases and annotation of variants is also included. This package is not species specific and supports parallel computation. We validated this package by reanalyzing data from a whole exome sequencing experiment on intellectual disability in humans. In a second example, we identified the mutations responsible for coat color in the dog. This is the first example of whole exome sequencing without prior mapping in the dog. Conclusion We developed an R-package that enables the identification of disease-causing variants from the long list of variants called in sequencing experiments. The software and a detailed manual are availableAbstract Background Identification of one or several disease causing variant(s) from the large collection of variants present in an individual is often achieved by the sequential use of heuristic filters. The recent development of whole exome sequencing enrichment designs for several non-model species created the need for a species-independent, fast and versatile analysis tool, capable of tackling a wide variety of standard and more complex inheritance models. With this aim, we developed "Mendelian", an R-package that can be used for heuristic variant filtering. Results The R-package Mendelian offers fast and convenient filters to analyze putative variants for both recessive and dominant models of inheritance, with variable degrees of penetrance and detectance. Analysis of trios is supported. Filtering against variant databases and annotation of variants is also included. This package is not species specific and supports parallel computation. We validated this package by reanalyzing data from a whole exome sequencing experiment on intellectual disability in humans. In a second example, we identified the mutations responsible for coat color in the dog. This is the first example of whole exome sequencing without prior mapping in the dog. Conclusion We developed an R-package that enables the identification of disease-causing variants from the long list of variants called in sequencing experiments. The software and a detailed manual are available athttps://github.com/BartBroeckx/Mendelian . … (more)
- Is Part Of:
- BMC bioinformatics. Volume 16:Issue 1(2015)
- Journal:
- BMC bioinformatics
- Issue:
- Volume 16:Issue 1(2015)
- Issue Display:
- Volume 16, Issue 1 (2015)
- Year:
- 2015
- Volume:
- 16
- Issue:
- 1
- Issue Sort Value:
- 2015-0016-0001-0000
- Page Start:
- 1
- Page End:
- 7
- Publication Date:
- 2015-12
- Subjects:
- Dominant -- Heuristic -- Recessive -- Sequence analysis -- Variant filtering
Bioinformatics -- Periodicals
Computational biology -- Periodicals
570.285 - Journal URLs:
- http://www.biomedcentral.com/bmcbioinformatics/ ↗
http://www.pubmedcentral.nih.gov/tocrender.fcgi?journal=13 ↗
http://link.springer.com/ ↗ - DOI:
- 10.1186/s12859-015-0822-7 ↗
- Languages:
- English
- ISSNs:
- 1471-2105
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - BLDSS-3PM
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