Pathway-based analysis of genomic variation data

Nir Atias; Sorin Istrail; Roded Sharan

doi:10.1016/j.gde.2013.09.002

Pathway-based analysis of genomic variation data

Nir Atias, Sorin Istrail, Roded Sharan

School of Computer Science

Tel Aviv University

Research output: Contribution to journal › Review article › peer-review

Abstract

A holy grail of genetics is to decipher the mapping from genotype to phenotype. Recent advances in sequencing technologies allow the efficient genotyping of thousands of individuals carrying a particular phenotype in an effort to reveal its genetic determinants. However, the interpretation of these data entails tackling significant statistical and computational problems that stem from the complexity of human phenotypes and the huge genotypic search space. Recently, an alternative pathway-level analysis has been employed to combat these problems. In this review we discuss these developments, describe the challenges involved and outline possible solutions and future directions for improvement.

Original language	English
Pages (from-to)	622-626
Number of pages	5
Journal	Current Opinion in Genetics and Development
Volume	23
Issue number	6
DOIs	https://doi.org/10.1016/j.gde.2013.09.002
State	Published - Dec 2013

All Science Journal Classification (ASJC) codes

Genetics
Developmental Biology

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10.1016/j.gde.2013.09.002

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title = "Pathway-based analysis of genomic variation data",

abstract = "A holy grail of genetics is to decipher the mapping from genotype to phenotype. Recent advances in sequencing technologies allow the efficient genotyping of thousands of individuals carrying a particular phenotype in an effort to reveal its genetic determinants. However, the interpretation of these data entails tackling significant statistical and computational problems that stem from the complexity of human phenotypes and the huge genotypic search space. Recently, an alternative pathway-level analysis has been employed to combat these problems. In this review we discuss these developments, describe the challenges involved and outline possible solutions and future directions for improvement.",

author = "Nir Atias and Sorin Istrail and Roded Sharan",

note = "Funding Information: NA was supported in part by a fellowship from the Edmond J. Safra Center for Bioinformatics at Tel Aviv University . SI was supported by an NSF grant 1321000 . RS was supported by an I-CORE Program of the Planning and Budgeting Committee and The Israel Science Foundation (grant no. 757/12 ).",

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AU - Sharan, Roded

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N2 - A holy grail of genetics is to decipher the mapping from genotype to phenotype. Recent advances in sequencing technologies allow the efficient genotyping of thousands of individuals carrying a particular phenotype in an effort to reveal its genetic determinants. However, the interpretation of these data entails tackling significant statistical and computational problems that stem from the complexity of human phenotypes and the huge genotypic search space. Recently, an alternative pathway-level analysis has been employed to combat these problems. In this review we discuss these developments, describe the challenges involved and outline possible solutions and future directions for improvement.

AB - A holy grail of genetics is to decipher the mapping from genotype to phenotype. Recent advances in sequencing technologies allow the efficient genotyping of thousands of individuals carrying a particular phenotype in an effort to reveal its genetic determinants. However, the interpretation of these data entails tackling significant statistical and computational problems that stem from the complexity of human phenotypes and the huge genotypic search space. Recently, an alternative pathway-level analysis has been employed to combat these problems. In this review we discuss these developments, describe the challenges involved and outline possible solutions and future directions for improvement.

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DO - 10.1016/j.gde.2013.09.002

M3 - مقالة مرجعية

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JO - Current Opinion in Genetics and Development

JF - Current Opinion in Genetics and Development

IS - 6

ER -

Pathway-based analysis of genomic variation data

Abstract

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