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Data from: Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose

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Readme

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  • 5.8 KB
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  • Plain text
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Phenotype data

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  • 415 KB
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  • ZIP Format
Description

Contains unprocessed and processed phenotype data. Covariates specific to each trait contain the same prefix in the raw phenotype file. For example, bmi_w_tail_age and bmi_w_tail_technician are age and technician initials for the trait bmi_w_tail. Residuals (processed phenotype data) used for GWAS were produced using the following approach: Each trait within each research site was quantile normalized separately for males and females, this approach is similar to using sex as a covariate. Other relevant covariates (including age and dissector) were identified for each trait, and covariate effects were regressed out if they were significant and explained more than 2% of the variance. (Please note that each technician is specific to each center. Phenotyping center information is in column “center”). Residuals were then quantile normalized again, after which the data for each sex and site was pooled prior to further analysis. Trait_ontology.xlsx contains phenotype descriptions and InterLex IDs.

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LD pruned genotype data

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  • 438 MB
File Format
  • ZIP Format
Description

LD pruned genotype data in PLINK binary and BIMBAM file formats. Command used to LD-prune the genotype data in PLINK v1.90 : --indep-pairwise 50 5 0.95. The 50 is the number of variants to look at in a window, the 5 is the number of variants to shift the windows side way each step, and the 0.95 is the r2 threshold for trimming SNPs.

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Unpruned genotype data in Oxford file format

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  • 7.95 GB
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  • ZIP Format
Description

Genotype data in the form of genotype probabilities.

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Genetic Relatedness Matrix (GRM)

File Size
  • 32.7 MB
File Format
  • ZIP Format
Description

gcta v1.26.0 was used to produce the GRM using the following command: gcta --bfile genotype --autosome-num 20 --autosome --thread-num 1 --make-grm-bin --out obesity_published_grm

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GWAS summary files

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  • 44.5 MB
File Format
  • ZIP Format
Description

Summary files for the GWAS results for all phenotypes. gemma_commands.sh contains the commands used to run the GWAS analysis in GEMMA v0.97

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Cite This Work

Chitre, Apurva S.; Polesskaya, Oksana; Holl, Katie; Gao, Jianjun; Cheng, Riyan; Bimschleger, Hannah; Garcia Martinez, Angel; George, Anthony; Gileta, Alexander F.; Han, Wenyan; Horvath, Aidan; Hughson, Alesa; Ishiwari, Keita; King, Christopher P.; Lamparelli, Alexander; Versaggi, Cassandra L.; Martin, Connor; St. Pierre, Celine L.; Tripi, Jordan A.; Wang, Tengfei; Chen, Hao; Flagel, Shelly B.; Meyer, Paul; Richards, Jerry; Robinson, Terry E.; Palmer, Abraham A.; Solberg Woods, Leah C. (2022). Data from: Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose. In The Center for GWAS in Outbred Rats Database (C-GORD). UC San Diego Library Digital Collections. https://doi.org/10.6075/J0Q240F0

Description

The data in this object comes from the publication titled “Genome-Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose”, authored by Chitre et al. The majority of the object is dedicated to the phenotypic and genetic data presented throughout the publication. However, this object also contains additional information beyond what is presented, including (1) a genetic relatedness matrix generated from LD pruned set of genotypes, (2) Summary files for the GWAS results for all phenotypes, (3) Trait descriptions. Details on how these files were generated can all be found in the Methods section of the associated publication.

Creation Date
  • 2014 to 2020
Date Issued
  • 2022
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Technical Details

All relevant tools and software used to generate the data in this object are noted below and in the Methods section of the associated publication.
GWAS: GEMMA v0.97
Converting genotype probabilities into dosages: QCTOOL v2
Converting genotype probabilities into Hard-Called Genotypes: PLINK v2.0
LD pruning of the genotype data : PLINK v1.90
Command used to LD-prune the genotype data in PLINK v1.90 : --indep-pairwise 50 5 0.95
The 50 is the number of variants to look at in a window, the 5 is the number of variants to shift the windows side way each step, and the 0.95 is the r2 threshold for trimming SNPs.

Funding

This work was supported by the National Institute on Drug Abuse (P50 DA037844) and the National Institute of Diabetes and Digestive and Kidney Diseases (R01 DK106386).

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Language
  • English
Identifier

Bimschleger, Hannah: https://orcid.org/0000-0001-6578-7201

Chen, Hao: https://orcid.org/0000-0002-2680-6921

Cheng, Riyan: https://orcid.org/0000-0002-8670-795X

Chitre, Apurva S.: https://orcid.org/0000-0003-1709-9214

Flagel, Shelly B.: https://orcid.org/0000-0002-7309-9908

George, Anthony: https://orcid.org/0000-0002-3700-5003

Gileta, Alexander F.: https://orcid.org/0000-0002-7793-8043

Han, Wenyan: https://orcid.org/0000-0003-0886-1430

Ishiwari, Keita: https://orcid.org/0000-0002-6190-2249

King, Christopher P.: https://orcid.org/0000-0002-6641-237X

Lamparelli, Alexander: https://orcid.org/0000-0003-1908-9562

Meyer, Paul: https://orcid.org/0000-0001-5665-2292

Palmer, Abraham A.: https://orcid.org/0000-0003-3634-0747

Polesskaya, Oksana: https://orcid.org/0000-0003-3024-114X

Robinson, Terry E.: https://orcid.org/0000-0001-7861-3737

Solberg Woods, Leah C.: https://orcid.org/0000-0002-7943-798X

St. Pierre, Celine L.: https://orcid.org/0000-0001-5465-6601

Wang, Tengfei: https://orcid.org/0000-0003-3527-3394

Related Resources

    Primary associated publication

    • Chitre, A. S., Polesskaya, O., Holl, K., Gao, J., Cheng, R., Bimschleger, H., Garcia Martinez, A., George, T., Gileta, A. F., Han, W., Horvath, A., Hughson, A., Ishiwari, K., King, C. P., Lamparelli, A., Versaggi, C. L., Martin, C., St. Pierre, C. L., Tripi, J. A., … Solberg Woods, L. C. (2020). Genome‐Wide Association Study in 3,173 Outbred Rats Identifies Multiple Loci for Body Weight, Adiposity, and Fasting Glucose. Obesity, 28(10), 1964–1973. https://doi.org/10.1002/oby.22927

    Source data

    Newer version

    • Wright, Sarah N.; Leger, Brittany S.; Rosenthal, Sara B.; Liu, Sophie; Jia, Tongqiu; Chitre, Apurva S.; Polesskaya, Oksana; Holl, Katie; Gao, Jianjun; Cheng, Riyan; Martinez, Angel G.; George, Anthony; Gileta, Alexander F.; Han, Wenyan; Netzley, Alesa H.; King, Christopher P.; Lamparelli, Alexander; Martin, Connor; St. Pierre, Celine L.; Wang, Tengfei; Bimschleger, Hannah; Richards, Jerry; Ishiwari, Keita; Chen, Hao; Flagel, Shelly B.; Meyer, Paul; Robinson, Terry E.; Solberg Woods, Leah C.; Kreisberg, Jason F.; Ideker, Trey; Palmer, Abraham A. (2023). Data from: Genome-wide association studies of human and rat BMI converge on synapse, epigenome, and hormone signaling networks. In The Center for GWAS in Outbred Rats Database (C-GORD). UC San Diego Library Digital Collections. https://doi.org/10.6075/J0NV9JFT

    Other resource

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Creative Commons Attribution 4.0 International Public License

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Research Data Curation Program, UC San Diego, La Jolla, 92093-0175 (https://lib.ucsd.edu/rdcp)

Last Modified

2024-07-11