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An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors

Bart Broeckx (UGent) , Frank Coopman (UGent) , Geert Verhoeven (UGent) , Tim Bosmans (UGent) , Ingrid Gielen (UGent) , Walter Dingemanse (UGent) , Jimmy Saunders (UGent) , Dieter Deforce (UGent) and Filip Van Nieuwerburgh (UGent)
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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 available at https://github.com/BartBroeckx/Mendelian.
Keywords
Heuristic, Dominant, Recessive, Sequence analysis, Variant filtering, EXOME, MC1R, DOGS

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Chicago
Broeckx, Bart, Frank Coopman, Geert Verhoeven, Tim Bosmans, Ingrid Gielen, Walter Dingemanse, Jimmy Saunders, Dieter Deforce, and Filip Van Nieuwerburgh. 2015. “An Heuristic Filtering Tool to Identify Phenotype-associated Genetic Variants Applied to Human Intellectual Disability and Canine Coat Colors.” Bmc Bioinformatics 16.
APA
Broeckx, B., Coopman, F., Verhoeven, G., Bosmans, T., Gielen, I., Dingemanse, W., Saunders, J., et al. (2015). An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors. BMC BIOINFORMATICS, 16.
Vancouver
1.
Broeckx B, Coopman F, Verhoeven G, Bosmans T, Gielen I, Dingemanse W, et al. An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors. BMC BIOINFORMATICS. 2015;16.
MLA
Broeckx, Bart, Frank Coopman, Geert Verhoeven, et al. “An Heuristic Filtering Tool to Identify Phenotype-associated Genetic Variants Applied to Human Intellectual Disability and Canine Coat Colors.” BMC BIOINFORMATICS 16 (2015): n. pag. Print.
@article{7020951,
  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 {\textacutedbl}Mendelian{\textacutedbl}, 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 at https://github.com/BartBroeckx/Mendelian.},
  articleno    = {391},
  author       = {Broeckx, Bart and Coopman, Frank and Verhoeven, Geert and Bosmans, Tim and Gielen, Ingrid and Dingemanse, Walter and Saunders, Jimmy and Deforce, Dieter and Van Nieuwerburgh, Filip},
  issn         = {1471-2105},
  journal      = {BMC BIOINFORMATICS},
  language     = {eng},
  pages        = {7},
  title        = {An heuristic filtering tool to identify phenotype-associated genetic variants applied to human intellectual disability and canine coat colors},
  url          = {http://dx.doi.org/10.1186/s12859-015-0822-7},
  volume       = {16},
  year         = {2015},
}

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