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Bioinformatics. 2014 Sep 1;30(17):2496-7. doi: 10.1093/bioinformatics/btu326. Epub 2014 May 10.

SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci.

Author information

1
Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.
2
Bioinformatics and Integrative Genomics, Harvard University, Cambridge, MA 02138, USA, Harvard-MIT Division of Health Sciences and Technology, Harvard Medical School, Boston MA 02215, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA and Program in Medical and Population Genetics, Broad Institute, Cambridge, MA 02142, USA.

Abstract

We created a fast, robust and general C+ + implementation of a single-nucleotide polymorphism (SNP) set enrichment algorithm to identify cell types, tissues and pathways affected by risk loci. It tests trait-associated genomic loci for enrichment of specificity to conditions (cell types, tissues and pathways). We use a non-parametric statistical approach to compute empirical P-values by comparison with null SNP sets. As a proof of concept, we present novel applications of our method to four sets of genome-wide significant SNPs associated with red blood cell count, multiple sclerosis, celiac disease and HDL cholesterol.

AVAILABILITY AND IMPLEMENTATION:

http://broadinstitute.org/mpg/snpsea.

SUPPLEMENTARY INFORMATION:

Supplementary data are available at Bioinformatics online.

PMID:
24813542
PMCID:
PMC4147889
DOI:
10.1093/bioinformatics/btu326
[Indexed for MEDLINE]
Free PMC Article

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