Project description:Bacteriophage Immunoprecipitation Sequencing (PhIP-Seq) datasets of three eHHV-6B-positive SLE patients (three technical replicates), six eHHV-6B-negative SLE patients (three technical replicates), and a negative control lacking sera or plasma (12 technical replicates; Illumina NextSeq) and sequencing data of HHV-6 peptide phage library (two technical replicates; Illumina NextSeq).

| EGAS00001007955 | EGA

eHHV-6B-positive Japanese WGS Data Access Committee

Project description:Data Access Committee EGAC00001003498

| EGAC00001003498 | EGA

SEER Remote Access Pilot Test Data (2018)

Project description:SEER Remote Access Pilot Test Data (2018)

| PRJNA625584 | ENA

SEER Remote Access Pilot Test Data (2018)

Project description:SEER Remote Access Pilot Test Data (2018)

| PRJNA625583 | ENA

SCA3_RNA-Seq Data Access Committee

Project description:Data Access Committee EGAC00001002840

| EGAC00001002840 | 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

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