Credibility analysis of putative disease-causing genes using bioinformatics

TY - JOUR

T1 - Credibility analysis of putative disease-causing genes using bioinformatics

AU - Abel, Olubunmi

AU - Powell, John F

AU - Andersen, Peter M

AU - Al-Chalabi, Ammar

PY - 2013

Y1 - 2013

N2 - Genetic studies are challenging in many complex diseases, particularly those with limited diagnostic certainty, low prevalence or of old age. The result is that genes may be reported as disease-causing with varying levels of evidence, and in some cases, the data may be so limited as to be indistinguishable from chance findings. When there are large numbers of such genes, an objective method for ranking the evidence is useful. Using the neurodegenerative and complex disease amyotrophic lateral sclerosis (ALS) as a model, and the disease-specific database ALSoD, the objective is to develop a method using publicly available data to generate a credibility score for putative disease-causing genes.

AB - Genetic studies are challenging in many complex diseases, particularly those with limited diagnostic certainty, low prevalence or of old age. The result is that genes may be reported as disease-causing with varying levels of evidence, and in some cases, the data may be so limited as to be indistinguishable from chance findings. When there are large numbers of such genes, an objective method for ranking the evidence is useful. Using the neurodegenerative and complex disease amyotrophic lateral sclerosis (ALS) as a model, and the disease-specific database ALSoD, the objective is to develop a method using publicly available data to generate a credibility score for putative disease-causing genes.

KW - Acknowledged-BRC

KW - Acknowledged-BRC-13/14

U2 - 10.1371/journal.pone.0064899

DO - 10.1371/journal.pone.0064899

M3 - Article

C2 - 23755159

SN - 1932-6203

VL - 8

SP - e64899

JO - PLoS ONE

JF - PLoS ONE

IS - 6

ER -