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An integrative computational approach for prioritization of genomic variants

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An integrative computational approach for prioritization of genomic variants. / Dubchak, Inna; Balasubramanian, Sandhya; Wang, Sheng; Cem, Meydan; Meyden, Cem; Sulakhe, Dinanath; Poliakov, Alexander; Börnigen, Daniela; Xie, Bingqing; Taylor, Andrew; Ma, Jianzhu; Paciorkowski, Alex R; Mirzaa, Ghayda M; Dave, Paul; Agam, Gady; Xu, Jinbo; Al-Gazali, Lihadh; Mason, Christopher E; Ross, M Elizabeth; Maltsev, Natalia; Gilliam, T Conrad.

In: PLOS ONE, Vol. 9, No. 12, 2014, p. e114903.

Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review

Harvard

Dubchak, I, Balasubramanian, S, Wang, S, Cem, M, Meyden, C, Sulakhe, D, Poliakov, A, Börnigen, D, Xie, B, Taylor, A, Ma, J, Paciorkowski, AR, Mirzaa, GM, Dave, P, Agam, G, Xu, J, Al-Gazali, L, Mason, CE, Ross, ME, Maltsev, N & Gilliam, TC 2014, 'An integrative computational approach for prioritization of genomic variants', PLOS ONE, vol. 9, no. 12, pp. e114903. https://doi.org/10.1371/journal.pone.0114903

APA

Dubchak, I., Balasubramanian, S., Wang, S., Cem, M., Meyden, C., Sulakhe, D., Poliakov, A., Börnigen, D., Xie, B., Taylor, A., Ma, J., Paciorkowski, A. R., Mirzaa, G. M., Dave, P., Agam, G., Xu, J., Al-Gazali, L., Mason, C. E., Ross, M. E., ... Gilliam, T. C. (2014). An integrative computational approach for prioritization of genomic variants. PLOS ONE, 9(12), e114903. https://doi.org/10.1371/journal.pone.0114903

Vancouver

Dubchak I, Balasubramanian S, Wang S, Cem M, Meyden C, Sulakhe D et al. An integrative computational approach for prioritization of genomic variants. PLOS ONE. 2014;9(12):e114903. https://doi.org/10.1371/journal.pone.0114903

Bibtex

@article{6032d1301d0a41faaf0e4cc165dff2f0,
title = "An integrative computational approach for prioritization of genomic variants",
abstract = "An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.",
keywords = "Child, Female, Folic Acid, Genomics, Humans, Models, Molecular, Mutation, Pregnancy, Protein Conformation, Reduced Folate Carrier Protein, Software, Spinal Dysraphism, Journal Article, Research Support, N.I.H., Extramural, Research Support, Non-U.S. Gov't, Research Support, U.S. Gov't, Non-P.H.S.",
author = "Inna Dubchak and Sandhya Balasubramanian and Sheng Wang and Meydan Cem and Cem Meyden and Dinanath Sulakhe and Alexander Poliakov and Daniela B{\"o}rnigen and Bingqing Xie and Andrew Taylor and Jianzhu Ma and Paciorkowski, {Alex R} and Mirzaa, {Ghayda M} and Paul Dave and Gady Agam and Jinbo Xu and Lihadh Al-Gazali and Mason, {Christopher E} and Ross, {M Elizabeth} and Natalia Maltsev and Gilliam, {T Conrad}",
year = "2014",
doi = "10.1371/journal.pone.0114903",
language = "English",
volume = "9",
pages = "e114903",
journal = "PLOS ONE",
issn = "1932-6203",
publisher = "Public Library of Science",
number = "12",

}

RIS

TY - JOUR

T1 - An integrative computational approach for prioritization of genomic variants

AU - Dubchak, Inna

AU - Balasubramanian, Sandhya

AU - Wang, Sheng

AU - Cem, Meydan

AU - Meyden, Cem

AU - Sulakhe, Dinanath

AU - Poliakov, Alexander

AU - Börnigen, Daniela

AU - Xie, Bingqing

AU - Taylor, Andrew

AU - Ma, Jianzhu

AU - Paciorkowski, Alex R

AU - Mirzaa, Ghayda M

AU - Dave, Paul

AU - Agam, Gady

AU - Xu, Jinbo

AU - Al-Gazali, Lihadh

AU - Mason, Christopher E

AU - Ross, M Elizabeth

AU - Maltsev, Natalia

AU - Gilliam, T Conrad

PY - 2014

Y1 - 2014

N2 - An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

AB - An essential step in the discovery of molecular mechanisms contributing to disease phenotypes and efficient experimental planning is the development of weighted hypotheses that estimate the functional effects of sequence variants discovered by high-throughput genomics. With the increasing specialization of the bioinformatics resources, creating analytical workflows that seamlessly integrate data and bioinformatics tools developed by multiple groups becomes inevitable. Here we present a case study of a use of the distributed analytical environment integrating four complementary specialized resources, namely the Lynx platform, VISTA RViewer, the Developmental Brain Disorders Database (DBDB), and the RaptorX server, for the identification of high-confidence candidate genes contributing to pathogenesis of spina bifida. The analysis resulted in prediction and validation of deleterious mutations in the SLC19A placental transporter in mothers of the affected children that causes narrowing of the outlet channel and therefore leads to the reduced folate permeation rate. The described approach also enabled correct identification of several genes, previously shown to contribute to pathogenesis of spina bifida, and suggestion of additional genes for experimental validations. The study demonstrates that the seamless integration of bioinformatics resources enables fast and efficient prioritization and characterization of genomic factors and molecular networks contributing to the phenotypes of interest.

KW - Child

KW - Female

KW - Folic Acid

KW - Genomics

KW - Humans

KW - Models, Molecular

KW - Mutation

KW - Pregnancy

KW - Protein Conformation

KW - Reduced Folate Carrier Protein

KW - Software

KW - Spinal Dysraphism

KW - Journal Article

KW - Research Support, N.I.H., Extramural

KW - Research Support, Non-U.S. Gov't

KW - Research Support, U.S. Gov't, Non-P.H.S.

U2 - 10.1371/journal.pone.0114903

DO - 10.1371/journal.pone.0114903

M3 - SCORING: Journal article

C2 - 25506935

VL - 9

SP - e114903

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 12

ER -