Project description:250k Sty, 250k Nsp, 250k Hind and 250k Xba Affymetrix SNP arrays for 50 leukemia remission samples used as controls for copy number analysis for GSE9109 and GSE9112. Keywords: Acute leukemia, BCR-ABL1, chronic myeloid leukemia, copy number analysis, loss-of-heterozygosity, genomics *** Due to privacy concerns, the primary SNP array data is no longer available with unrestricted access. Individuals wishing to obtain this data for research purposes may request access using the Web links below. ***

2009-09-02 | GSE9111 | GEO

Lipodystrophy study Data Access Committee

Project description:Data Access Committee EGAC00001000997

| EGAC00001000997 | EGA

MBL2 study data access committee

Project description:Data Access Committee EGAC00001002678

| EGAC00001002678 | EGA

Study EGAS00001005054 Data Access Committee

Project description:Data Access Committee EGAC00001002066

| EGAC00001002066 | EGA

A mechanism for controlled access to GWAS data: experience of the GAIN Data Access Committee.

Project description:The Genetic Association Information Network (GAIN) Data Access Committee was established in June 2007 to provide prompt and fair access to data from six genome-wide association studies through the database of Genotypes and Phenotypes (dbGaP). Of 945 project requests received through 2011, 749 (79%) have been approved; median receipt-to-approval time decreased from 14 days in 2007 to 8 days in 2011. Over half (54%) of the proposed research uses were for GAIN-specific phenotypes; other uses were for method development (26%) and adding controls to other studies (17%). Eight data-management incidents, defined as compromises of any of the data-use conditions, occurred among nine approved users; most were procedural violations, and none violated participant confidentiality. Over 5 years of experience with GAIN data access has demonstrated substantial use of GAIN data by investigators from academic, nonprofit, and for-profit institutions with relatively few and contained policy violations. The availability of GAIN data has allowed for advances in both the understanding of the genetic underpinnings of mental-health disorders, diabetes, and psoriasis and the development and refinement of statistical methods for identifying genetic and environmental factors related to complex common diseases.

| S-EPMC3617375 | biostudies-literature

SI-NET study data access committee

Project description:Data Access Committee EGAC00001001995

| EGAC00001001995 | EGA