Format

Send to

Choose Destination
See comment in PubMed Commons below
Bioinformatics. 2011 Aug 1;27(15):2112-8. doi: 10.1093/bioinformatics/btr324. Epub 2011 Jun 23.

Enriching targeted sequencing experiments for rare disease alleles.

Author information

1
Vanderbilt Epidemiology Center, Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN 37203, USA.

Abstract

MOTIVATION:

Next-generation targeted resequencing of genome-wide association study (GWAS)-associated genomic regions is a common approach for follow-up of indirect association of common alleles. However, it is prohibitively expensive to sequence all the samples from a well-powered GWAS study with sufficient depth of coverage to accurately call rare genotypes. As a result, many studies may use next-generation sequencing for single nucleotide polymorphism (SNP) discovery in a smaller number of samples, with the intent to genotype candidate SNPs with rare alleles captured by resequencing. This approach is reasonable, but may be inefficient for rare alleles if samples are not carefully selected for the resequencing experiment.

RESULTS:

We have developed a probability-based approach, SampleSeq, to select samples for a targeted resequencing experiment that increases the yield of rare disease alleles substantially over random sampling of cases or controls or sampling based on genotypes at associated SNPs from GWAS data. This technique allows for smaller sample sizes for resequencing experiments, or allows the capture of rarer risk alleles. When following up multiple regions, SampleSeq selects subjects with an even representation of all the regions. SampleSeq also can be used to calculate the sample size needed for the resequencing to increase the chance of successful capture of rare alleles of desired frequencies.

SOFTWARE:

http://biostat.mc.vanderbilt.edu/SampleSeq

PMID:
21700677
PMCID:
PMC3137214
DOI:
10.1093/bioinformatics/btr324
[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

0 comments
How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for Silverchair Information Systems Icon for PubMed Central
    Loading ...
    Support Center