title: SNPsea: an algorithm to identify cell types, tissues and pathways affected by risk loci.
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.
  
  
  METHODS
  http://broadinstitute.org/mpg/snpsea.
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: 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.
authors.forename: Kamil
authors.initials: K
authors.lastname: Slowikowski
authors.affiliation: 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.
authors.forename: Xinli
authors.initials: X
authors.lastname: Hu
authors.affiliation: 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.
authors.forename: Soumya
authors.initials: S
authors.lastname: Raychaudhuri
mesh_terms: D000465:Algorithms; D041905:Erythroid Cells / Q000378:metabolism; D056426:Genetic Loci; D023281:Genomics; D006801:Humans; D015810:Linkage Disequilibrium; D020641:Polymorphism, Single Nucleotide; D012306:Risk