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bioc
coMethDMR:Accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies
coMethDMR identifies genomic regions associated with continuous phenotypes by optimally leverages covariations among CpGs within predefined genomic regions. Instead of testing all CpGs within a genomic region, coMethDMR carries out an additional step that selects co-methylated sub-regions first without using any outcome information. Next, coMethDMR tests association between methylation within the sub-region and continuous phenotype using a random coefficient mixed effects model, which models both variations between CpG sites within the region and differential methylation simultaneously.
Maintained by Fernanda Veitzman. Last updated 5 months ago.
dnamethylationepigeneticsmethylationarraydifferentialmethylationgenomewideassociation
7 stars 6.47 score 42 scriptsbioc
rnaEditr:Statistical analysis of RNA editing sites and hyper-editing regions
RNAeditr analyzes site-specific RNA editing events, as well as hyper-editing regions. The editing frequencies can be tested against binary, continuous or survival outcomes. Multiple covariate variables as well as interaction effects can also be incorporated in the statistical models.
Maintained by Lanyu Zhang. Last updated 5 months ago.
genetargetepigeneticsdimensionreductionfeatureextractionregressionsurvivalrnaseq
3 stars 4.48 score 9 scripts