Integrating diverse genomic data using gene sets

By Svitlana Tyekucheva, Luigi Marchionni, Rachel Karchin, Giovanni Parmigiani. Genome Biology, 2011

9,843 citations recorded by the source corpus.

We introduce and evaluate data analysis methods to interpret simultaneous measurement of multiple genomic features made on the same biological samples. Our tools use gene sets to provide an interpretable common scale for diverse genomic information. We show we can detect genetic effects, although they may act through different mechanisms in different samples, and show we can discover and validate important disease-related gene sets that would not be discovered by analyzing each data type individually.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/01361610a72c846d095698a7e24c879c4bc316fa

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In Molecular Biology

Citations in the corpus

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ANOVA-Like Differential Expression (ALDEx) Analysis for Mixed Population RNA-Seq (2013, methodology): “Comparison of ALDEx to existing methods We initially compared the ability of ALDEx, DESeq[23], edgeR [38] and CuffDiff[39] to identify differentially expressed transcripts in the B. cereus dataset.”
Cross-talk between PRMT1-mediated methylation and ubiquitylation on RBM15 controls RNA splicing (2015, methodology): “For each 686 peak, we used DESeq (Anders and Huber, 2010) to test if there was significant difference in read counts 687 within the peak region between RBM15 samples and control samples after correcting for library size 688”
RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis (2018, methodology): “Initial implementations focused on two-group comparisons [120,135] and were later extended to the generalized linear model (GLM) framework, an extension of classical linear models to non-Gaussian responses [136].”
SeqGL Identifies Context-Dependent Binding Signals in Genome-Wide Regulatory Element Maps (2015, methodology): “DESeq [49] was used to identify the cell-type specific and common peaks.”
Altering the intestinal microbiota during a critical developmental window has lasting metabolic consequences (2014, methodology): “Differential expression analysis was performed with the Bioconductor package DESeq (Anders and Huber, 2010).”
A long noncoding RNA induced by TLRs mediates both activation and repression of immune response genes (2013, methodology): “Subsequent data analysis was performed in R and differential gene expression specific analyses were conducted with the DESeq R package (31).”