Literature DB >> 18179399

Prioritization of positional candidate genes using multiple web-based software tools.

Tobias A Thornblad1, Kate S Elliott, Jeremy Jowett, Peter M Visscher.   

Abstract

The prioritization of genes within a candidate genomic region is an important step in the identification of causal gene variants affecting complex traits. Surprisingly, there have been very few reports of bioinformatics tools to perform such prioritization. The purpose of this article is to investigate the performance of 3 positional candidate gene software tools available, PosMed, GeneSniffer and SUSPECTS. The comparison was made for 40, 20 and 10 Mb regions in the human genome centred around known susceptibility genes for the common diseases breast cancer, Crohn's disease, age-related macular degeneration and schizophrenia. The known susceptibility gene was not always ranked highly, or not ranked at all, by 1 or more of the software tools. There was a large variation between the 3 tools regarding which genes were prioritized, and their rank order. PosMed and GeneSniffer were most similar in their prioritization gene list, whereas SUSPECTS identified the same candidate genes only for the narrowest (10 Mb) regions. Combining 2 or all of the candidate gene finding tools was superior in terms of ranking positional candidates. It is possible to reduce the number of candidate genes from a starting set in a region of interest by combining a variety of candidate gene finding tools. Conversely, we recommend caution in relying solely on single positional candidate gene prioritization tools. Our results confirm the obvious, that is, that starting with a narrower positional region gives a higher likelihood that the true susceptibility gene is selected, and that it is ranked highly. A narrow confidence interval for the mapping of complex trait genes by linkage can be achieved by maximizing marker informativeness and by having large samples. Our results suggest that the best approach to classify a minimum set of candidate genes is to take those genes that are prioritized by multiple prioritization tools.

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Year:  2007        PMID: 18179399     DOI: 10.1375/twin.10.6.861

Source DB:  PubMed          Journal:  Twin Res Hum Genet        ISSN: 1832-4274            Impact factor:   1.587


  15 in total

Review 1.  Computational tools for prioritizing candidate genes: boosting disease gene discovery.

Authors:  Yves Moreau; Léon-Charles Tranchevent
Journal:  Nat Rev Genet       Date:  2012-07-03       Impact factor: 53.242

2.  Outcome of array CGH analysis for 255 subjects with intellectual disability and search for candidate genes using bioinformatics.

Authors:  Y Qiao; C Harvard; C Tyson; X Liu; C Fawcett; P Pavlidis; J J A Holden; M E S Lewis; E Rajcan-Separovic
Journal:  Hum Genet       Date:  2010-05-29       Impact factor: 4.132

3.  PosMed-plus: an intelligent search engine that inferentially integrates cross-species information resources for molecular breeding of plants.

Authors:  Yuko Makita; Norio Kobayashi; Yoshiki Mochizuki; Yuko Yoshida; Satomi Asano; Naohiko Heida; Mrinalini Deshpande; Rinki Bhatia; Akihiro Matsushima; Manabu Ishii; Shuji Kawaguchi; Kei Iida; Kosuke Hanada; Takashi Kuromori; Motoaki Seki; Kazuo Shinozaki; Tetsuro Toyoda
Journal:  Plant Cell Physiol       Date:  2009-06-15       Impact factor: 4.927

Review 4.  Using genome-wide expression profiling to define gene networks relevant to the study of complex traits: from RNA integrity to network topology.

Authors:  M A O'Brien; B N Costin; M F Miles
Journal:  Int Rev Neurobiol       Date:  2012       Impact factor: 3.230

5.  Identifying relationships among genomic disease regions: predicting genes at pathogenic SNP associations and rare deletions.

Authors:  Soumya Raychaudhuri; Robert M Plenge; Elizabeth J Rossin; Aylwin C Y Ng; Shaun M Purcell; Pamela Sklar; Edward M Scolnick; Ramnik J Xavier; David Altshuler; Mark J Daly
Journal:  PLoS Genet       Date:  2009-06-26       Impact factor: 5.917

6.  Disease gene characterization through large-scale co-expression analysis.

Authors:  Allen Day; Jun Dong; Vincent A Funari; Bret Harry; Samuel P Strom; Dan H Cohn; Stanley F Nelson
Journal:  PLoS One       Date:  2009-12-31       Impact factor: 3.240

7.  ToppGene Suite for gene list enrichment analysis and candidate gene prioritization.

Authors:  Jing Chen; Eric E Bardes; Bruce J Aronow; Anil G Jegga
Journal:  Nucleic Acids Res       Date:  2009-05-22       Impact factor: 16.971

8.  PosMed (Positional Medline): prioritizing genes with an artificial neural network comprising medical documents to accelerate positional cloning.

Authors:  Yuko Yoshida; Yuko Makita; Naohiko Heida; Satomi Asano; Akihiro Matsushima; Manabu Ishii; Yoshiki Mochizuki; Hiroshi Masuya; Shigeharu Wakana; Norio Kobayashi; Tetsuro Toyoda
Journal:  Nucleic Acids Res       Date:  2009-05-25       Impact factor: 16.971

9.  Genetic region characterization (Gene RECQuest) - software to assist in identification and selection of candidate genes from genomic regions.

Authors:  Rajani S Sadasivam; Gayathri Sundar; Laura K Vaughan; Murat M Tanik; Donna K Arnett
Journal:  BMC Res Notes       Date:  2009-09-30

10.  PosMed: Ranking genes and bioresources based on Semantic Web Association Study.

Authors:  Yuko Makita; Norio Kobayashi; Yuko Yoshida; Koji Doi; Yoshiki Mochizuki; Koro Nishikata; Akihiro Matsushima; Satoshi Takahashi; Manabu Ishii; Terue Takatsuki; Rinki Bhatia; Zolzaya Khadbaatar; Hajime Watabe; Hiroshi Masuya; Tetsuro Toyoda
Journal:  Nucleic Acids Res       Date:  2013-06-12       Impact factor: 16.971

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