Resources for Researchers

Accessing COGA Data

(1) Apply for data directly from NIAAA.
Available data include:

Genetic linkage data (microsatellite markers) on the densely affected COGA families, including pedigree plots

GWAS data

DNA samples

Phenotypic data on all family members

Electroencephalography (EEG) data

Note that the subject IDs for these datasets are different than the IDs used by COGA investigators. Additionally, the wealth of data collected by COGA across the years can be challenging for investigators to navigate. For that reason, some investigators choose Option (2).
(2) Collaborate directly with COGA investigators. 
The advantage of this approach is that COGA collaborators can help navigate the extensive phenotypic and genotypic datasets, and provide access to new data that may not be publicly available. If you are interested in working with COGA on a project, start by identifying a COGA researcher with interests that map on to the project you would like to pursue. After ensuring your proposed project does not overlap with on-going or planned COGA analyses, that individual can help you navigate the collaboration process, which will involve writing an abstract of the proposed work, presenting your work on a COGA call, and inviting other COGA collaborators with relevant expertise to be involved.
(3) Access data through dbGaP
Six sets of GWAS data, along with limited phenotypic data, are available through NCBI (National Center for Biotechnology Information). For all datasets the subject ID is randomized and different than the ID used by COGA investigators.  Each of these datasets contains unique individuals, genotyped at different stages in the project, with the exception of 2-127 samples genotyped on at least two different arrays, to assess quality. See Lai et al (2019) for more detail.  The links to the datasets can be found here:

CIDR: Collaborative Study on the Genetics of Alcoholism Case Control Study [phs000125.v1.p1]. GWAS data on cases (primarily probands) and controls drawn from the families.

Study of Addiction: Genetics and Environment (SAGE) [phs000092.v1.p1]. GWAS data on a subset of the COGA case-control individuals plus individuals from studies of cocaine and nicotine dependence.

Families with highest density of alcohol dependence and/or extreme event-related oscillation data [phs000763.v1.p1]. GWAS data on 119 extended families of European descent are available here, along with extensive documentation.

Study on the Genetics of Alcoholism (COGA): African American Family GWAS [phs000976.v1.p1]. GWAS data on all available COGA families of African descent are available.

COGA: Smokescreen GWAS [phs001208.v2.p1]. GWAS data on all remaining COGA DNA samples, primarily of other racial background, were genotyped on the Smoke Screen array.

Exome array data [phs001208.v2.p1}. A subsample of COGA families and individuals were genotyped on the Affymetrix Exon Array.

 

Access to Biomaterials

Rutgers University stores, maintains, and distributes biomaterials consisting of lymphoblastoid cell lines and DNA from participating subjects.

The table is a list of all iPSC available through the NIAAA/COGA Sharing Repository from Sampled, Inc., our repository contractor.

COGA iPSC Inventory at Sampled

COGA iPSC lines available through the NIAAA/COGA Sharing Repository.  Use the Clone Inventory Code in the request.  The Cell ID, Sex, and Group match cell line identifiers in publications denoted in the Study column (Popova: https://doi.org/10.1038/s41380-022-01818-x; Li: https://doi.org/10.1101/2024.02.19.581066).  Matcode Source indicates the cell type used for reprogramming: CPL: cryopreserved lymphocytes; ERYB: erythroblasts; LCL: lymphocyte cell line.  In most cases, multiple, reprogrammed iPSC were prepared and frozen but generally only the A clone was used in published studies.

Researchers may gain access to biomaterials by completing an application as described:

https://www.niaaa.nih.gov/major-initiatives/collaborative-studies-genetics-alcoholism-coga-study#Access

 

COGA Instruments

COGA developed the Semi-Structured Assessment for the Genetics of Alcoholism (SSAGA) interview, which we make freely available for researchers.  The SSAGA is available in both adult and child forms.  Different versions of the SSAGA have been administered across the different phases of data collection.  To obtain the most recent version of the SSAGA, along with associated diagnostic algorithms, please contact Dr. Victor Hesselbrock.

 

Data Entry in Blaise

SSAGA-IV Entry Program – Instructions for downloading Blaise

Installation:

Users must obtain a Blaise license to download the dep.exe file. Once this is done, please email Sue Winkeler at winkeler@wustl.edu to obtain a password.

After downloading the Blaise executable file, dep.exe, unzip it to a folder of your choice. Note: If all files are unzipped to the same directory along with the dep.exe file, the specification pathnames will be simplified.

To Test:

Click on dep.exe in your folder. A window will open up. You will be prompted to enter the name of the data model. Paste or type the pathname for the test section chosen (e.g. tstDR.bdb) in the window.

On the first screen of the entry program, you will be prompted to enter the ID.

You may stop at this time during the data entry process and save the entered data. You may go back and change any previously entered responses. The program will enforce any changes to skip-out patterns associated with the changed responses.

Comments:

Some age checks are missing. This is intentional. These were omitted at the suggestion of the Assessment Committee.

CSSAGA-IV Entry Program

CSSAGA_f1

Electronic Data Entry using ASPECT with the SSAGA form heading

INFOTECHSoft Website