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PrediXcan specifications


Unique identifier OMICS_08952
Name PrediXcan
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Perl, Python, R
Computer skills Advanced
Stability Stable
Maintained Yes


No version available



  • person_outline Hae Kyung Im

Publication for PrediXcan

PrediXcan citations


Exploring the phenotypic consequences of tissue specific gene expression variation inferred from GWAS summary statistics

Nat Commun
PMCID: 5940825
PMID: 29739930
DOI: 10.1038/s41467-018-03621-1

[…] t risk for cardiovascular disease. This gene is most actively regulated in liver (close to 50% of the expression level of this gene is determined by the genetic component) with the most significant S-PrediXcan association in liver (p-value ≈ 0, Z = −28.8), consistent with our prior knowledge of lipid metabolism. In this example, tissue specific results suggest a causal role of SORT1 in liver.Howev […]


Integrative genomics identifies new genes associated with severe COPD and emphysema

PMCID: 5863845
PMID: 29566699
DOI: 10.1186/s12931-018-0744-9

[…] ence datasets to predict gene expression given a set of genotypes, and subsequently identify gene expression differences for a given phenotype. This approach has been implemented in software called S-PrediXcan and TWAS [–]. Aggregating information from variant level to infer gene-level associations increases the power to discover more genes at loci not previously implicated by GWAS and gives mecha […]


Using regulatory genomics data to interpret the function of disease variants and prioritise genes from expression studies

PMCID: 5850119
PMID: 29568492
DOI: 10.5256/f1000research.14748.r30355

[…] or cell types . Here, we will simply match GWAS SNPs and eQTLs according to their genomic locations, which is a rather crude way to integrate these two types of data. More robust alternatives such as PrediXcan , TWAS and SMR exist and should be adopted if possible. One downside of these methods is that they require subject-level or complete summary data, making them less practical in some circum […]


Another Round of “Clue” to Uncover the Mystery of Complex Traits

PMCID: 5852557
PMID: 29370075
DOI: 10.3390/genes9020061

[…] e expression influences disease risk (hence the crime in investigation). Various methods to test the effects of gene expression on diseases exist, such as Summary based Mendelian Randomization (SMR), PrediXcan, MetaXcan, and CAVIAR (Causal Variant Identification in Associated Regions) [,,,]. Gene expression data have also been utilized in multi-omics integrative approaches. For example, LaCriox et […]


Gene based association study for lipid traits in diverse cohorts implicates BACE1 and SIDT2 regulation in triglyceride levels

PMCID: 5793713
PMID: 29404214
DOI: 10.7717/peerj.4314

[…] cholesterol (CHOL), HDL, TRIG, or LDL levels, and they conducted further gene set enrichment analysis with MAGENTA (). However, gene-level association studies that integrate transcriptome data, like PrediXcan and TWAS, were not performed (; ). Summary statistics from GLGC were used as a replication and base set in our analyses of the Yoruba and Cebu cohorts.Both the Cebu and Yoruba cohorts have b […]


Genome wide association and expression quantitative trait loci studies identify multiple susceptibility loci for thyroid cancer

Nat Commun
PMCID: 5511346
PMID: 28703219
DOI: 10.1038/ncomms15966
call_split See protocol

[…] ct of the associated genotypes on expression in various tissues using the public eQTL database (GTEx and Whole blood eQTL). We conducted the imputation of gene expression in 470 DTC samples using the PrediXcan package ( The normal thyroid eQTL database (GTEx V6p, 278 thyroid samples) was used as a reference. In patients with PTC from the […]


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PrediXcan institution(s)
Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL; Division of Genetic Medicine, Vanderbilt University, Nashville, TN; Department of Biomedical Informatics, Vanderbilt University, Nashville, TN; Section of Hematology/Oncology, Department of Medicine, University of Chicago, Chicago, IL; Department of Human Genetics, University of Chicago, Chicago, IL; Department of Statistics, University of Chicago, Chicago, IL

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