| Name : R-eGST
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| Version : 1.0.0
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp153.4.7
| Date : 2024-06-14 11:43:27
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| Group : Development/Libraries/Other
| Source RPM : R-eGST-1.0.0-lp153.4.7.src.rpm
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| Size : 0.21 MB
| |
| Packager : (none)
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| Summary : Leveraging eQTLs to Identify Individual-Level Tissue of Interest for a Complex Trait
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Description :
Genetic predisposition for complex traits is often manifested through
multiple tissues of interest at different time points in the
development. As an example, the genetic predisposition for obesity
could be manifested through inherited variants that control metabolism
through regulation of genes expressed in the brain and/or through the
control of fat storage in the adipose tissue by dysregulation of genes
expressed in adipose tissue. We present a method eGST (eQTL-based
genetic subtyper) that integrates tissue-specific eQTLs with GWAS data
for a complex trait to probabilistically assign a tissue of interest to
the phenotype of each individual in the study. eGST estimates the
posterior probability that an individual\'s phenotype can be assigned to
a tissue based on individual-level genotype data of tissue-specific
eQTLs and marginal phenotype data in a genome-wide association study
(GWAS) cohort. Under a Bayesian framework of mixture model, eGST
employs a maximum a posteriori (MAP) expectation-maximization (EM)
algorithm to estimate the tissue-specific posterior probability across
individuals. Methodology is available from: A Majumdar, C
Giambartolomei, N Cai, MK Freund, T Haldar, T Schwarz, J Flint, B
Pasaniuc (2019) < doi:10.1101/674226>.
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RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/openSUSE_Leap_15.3/x86_64 |
