Literature DB >> 26992202

Testing differentially expressed genes in dose-response studies and with ordinal phenotypes.

Elizabeth Sweeney, Ciprian Crainiceanu, Jan Gertheiss.   

Abstract

When testing for differentially expressed genes between more than two groups, the groups are often defined by dose levels in dose-response experiments or ordinal phenotypes, such as disease stages. We discuss the potential of a new approach that uses the levels' ordering without making any structural assumptions, such as monotonicity, by testing for zero variance components in a mixed models framework. Since the mixed effects model approach borrows strength across doses/levels, the test proposed can also be applied when the number of dose levels/phenotypes is large and/or the number of subjects per group is small. We illustrate the new test in simulation studies and on several publicly available datasets and compare it to alternative testing procedures. All tests considered are implemented in R and are publicly available. The new approach offers a very fast and powerful way to test for differentially expressed genes between ordered groups without making restrictive assumptions with respect to the true relationship between factor levels and response.

Mesh:

Year:  2016        PMID: 26992202     DOI: 10.1515/sagmb-2015-0091

Source DB:  PubMed          Journal:  Stat Appl Genet Mol Biol        ISSN: 1544-6115


  1 in total

1.  Statistical inference for ordinal predictors in generalized additive models with application to Bronchopulmonary Dysplasia.

Authors:  Jan Gertheiss; Fabian Scheipl; Tina Lauer; Harald Ehrhardt
Journal:  BMC Res Notes       Date:  2022-03-22
  1 in total

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