PredictDB Data Repository

Here you can find transcriptome and other traits prediction weights for the PrediXcan family of methods: S-PrediXcan, MultiXcan, S-MultiXcan, and BrainXcan.

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Prediction weights and covariance files

The prediction weigths are saved in SQLite format, *.db, which can be easily queried using sqlit, R, python, etc. See example in R here. The summary statistics based methods need covariances (LD reference) between predictor SNPs and are saved in gzipped text files *.txt.gz. S-PrediXcan is meant to use the single-tissue LD reference files (“covariances”) appropriate to each model. S-MultiXcan uses single-tissue prediction models and a cross-tissue LD reference.

The Search option in the menu may be the fastest way to find the right models or answers to your questions. If you still have more questions, join our mailing list and post your questions there. You can also navigate through the menu options.

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Please join our Google Group for general discussion, notification of future changes to our tools, feature requests, etc.

Disclaimer

The models are provided “as is”, with the hope that they may be of use, without warranty of any kind, express or implied, including but not limited to the warranties of merchantability, fitness for a particular purpose and noninfringement. in no event shall the authors or copyright holders be liable for any claim, damages or other liability, whether in an action of contract, tort or otherwise, arising from, out of or in connection with the models or the use or other dealings in the models.

References

  1. PrediXcan: Gamazon ER†, Wheeler HE†, Shah KP†, Mozaffari SV, Aquino-Michaels K, Carroll RJ, Eyler AE, Denny JC, Nicolae DL, Cox NJ, Im HK. (2015) A gene-based association method for mapping traits using reference transcriptome data. Nat Genet. doi:10.1038/ng.3367 url
  2. S-PrediXcan: Barbeira, Alvaro N., Scott P. Dickinson, Rodrigo Bonazzola, Jiamao Zheng, Heather E. Wheeler, Jason M. Torres, Eric S. Torstenson, Kaanan P. Shah, Tzintzuni Garcia, Todd L. Edwards, Eli A. Stahl, Laura M. Huckins, Dan L. Nicolae, Nancy J. Cox, and Hae Kyung Im. 2018. “Exploring the Phenotypic Consequences of Tissue Specific Gene Expression Variation Inferred from GWAS Summary Statistics.” Nature Communications 9 (1). Nature Publishing Group: 1–20.
  3. Genetic Architecture of Expression traits: Heather E Wheeler, Kaanan P Shah, Jonathon Brenner, Tzintzuni Garcia, Keston Aquino-Michaels, GTEx Consortium, Nancy J Cox, Dan L Nicolae, Hae Kyung Im. (2016) Survey of the Heritability and Sparsity of Gene Expression Traits Across Human Tissues. url
  4. MultiXcan: Barbeira, Alvaro N., Milton Pividori, Jiamao Zheng, Heather E. Wheeler, Dan L. Nicolae, and Hae Kyung Im. 2019. “Integrating Predicted Transcriptome from Multiple Tissues Improves Association Detection.” PLoS Genetics 15 (1). Public Library of Science: e1007889–20.
  5. GTEx V8 models: Barbeira, Alvaro N., Rodrigo Bonazzola, Eric R. Gamazon, Yanyu Liang, Yoson Park, …, and Hae Kyung Im. 2021. “Exploiting the GTEx Resources to Decipher the Mechanisms at GWAS Loci.” Genome Biology 22 (1): 49.
  6. GTEx Consortium Main Paper: 2020. “The GTEx Consortium Atlas of Genetic Regulatory Effects across Human Tissues.” Science 369 (6509): 1318–30.
  7. Fine-mapping-based prediction more reliable: Barbeira, Alvaro N., Owen J. Melia, Yanyu Liang, Rodrigo Bonazzola, Gao Wang, Heather E. Wheeler, François Aguet, Kristin G. Ardlie, Xiaoquan Wen, and Hae K. Im. 2020. “Fine-Mapping and QTL Tissue-Sharing Information Improves the Reliability of Causal Gene Identification.” Genetic Epidemiology n/a (n/a). John Wiley & Sons, Ltd. doi:10.1002/gepi.22346.

License

This work is licensed under the Creative Commons Attribution-ShareAlike 4.0 International License.

FAQ

Error for region (...) LinAlgError('SVD did not converge')

2021-07-23 PredictDB Team
𝕆ne step of the summary imputation, the computation of snp covariance matrix inverse, is performed via singular value decomposition (SVD). Numerical solutions to the SVD algorithm are not guaranteed to converge, and fail on some regions. When this happens, unmeasured zscores will not be present in … Read more →
FAQ

Error No intersection between model names in MetaXcan Results and Prediction Models

2021-07-23 Festus
𝕋his error happen when the strings captured from the metaxcan results and models don’t coincide A good example is when the metaxcan results' captured names looked like Aorta while the models' captured names looked like Artery_Aorta, this will result into this error […] … Read more →

BrainXcan Brain Feature Prediction Models

2021-07-22 Yanyu Liang
𝕊-BrainXcan takes GWAS as input and return the association between GWAS phenotype and a list of brain image-derived phenotypes. BrainXcan manuscript link. Software documentation (Quick start) link. BrainXcan database link. Analysis scripts link. […] The software is built upon both Python and … Read more →
FAQ

Why are there fewer available genes/introns in the prediction models than in the GTEx dataset?

2021-07-21 PredictDB Team
𝕋he prediction model databases only contain models that pass a stringent criteria (each family of models has its own criteria, e.g. MASHR models require at least one snp with high posterior probability of being an eQTL). Our model training algorithms are complex and conservative. Sometimes, a good … Read more →
FAQ

AttributeError 'NoneType' object has no attribute 'groups'

2021-07-21 Festus
𝕋his error happens when using the Multixcan tool, it usually happens when the tool cant find files in the Metaxcan folder you provided. Thus halting the process of meta analyzing the results. The most probable cause of this error are; […] –metaxcan_filter … Read more →
FAQ

Can I predict genes on chromosome X or Y?

2021-07-21 PredictDB Team
ℕot at the moment. Sex chromosome genes need to be handled differently than those on the autosomes, and do not fit into our existing analysis pipeline. Read more →
FAQ

Error low % of SNPs used

2021-07-21 Festus
𝕋here are different reasons where you could get a low % of SNPs in the model used with your individual level data or summary stats file. Some of the issues include; […] Little overlap between the model SNPs and genotype/summary stats SNPs […] Incomplete/malformed models .db file … Read more →

GTEx v8 models on eQTL and sQTL

2021-07-21 PredictDB Team
𝕎e have produced different families of prediction models for sQTL and eQTL, using several prediction strategies, on GTEx v8 release data. We recommend MASHR-based models below. Elastic Net-based are a safe, robust alternative with decreased power. […] Expression and splicing prediction models … Read more →
FAQ

How can I build my own prediction model?

2021-07-21 PredictDB Team
𝔽or elastic net models, you can find a tutorial here(https://github.com/hakyimlab/PredictDB-Tutorial) The newer GTEx v8 models were generaed with code available here. The documentation is still a work in progress, don’t hesitate to use the PrediXcan/MetaXcan Google Group to ask for support. Read more →
FAQ

How do I query the prediction model db?

2021-07-21 PredictDB Team
𝕋he .db files are simple sqlite files. You can programmatically query them via python, R, perl, etc (using appropriate libraries). Find example queries in this link(https://github.com/hakyimlab/PrediXcan/blob/master/Software/query-db.Rmd) Read more →