Single - cell
differential gene expression analysis revealed a spectrum of known transcripts, including several linked to cytotoxic and costimulatory function that are expressed at higher levels in the TEMRA (effector memory T cells expressing CD45RA) subset, which is highly enriched for CD4 - CTLs, compared with CD4 + T cells in the central memory (TCM) and effector memory (TEM) subsets.
Not exact matches
The second tool, SuperExactTest, establishes the very first theoretical framework for assessing the statistical significance of multi-set intersections and enables users to compare very large sets of data, such as
gene sets produced from genome - wide association studies (GWAS) and
differential expression analysis.
Gene Set Enrichment
Analysis (GSEA) is a microarray data - mining technique used to determine whether there is coordinated
differential expression or «enrichment» in a set of functionally related
genes when comparing control and experimental samples [35].
As mRNA isolation is simple and since DNA microarrays are a proven genomics reagent for monitoring
differential gene expression, a genome - wide
expression analysis may be the fastest and most efficient method for identifying additional candidate effectors of colony queen number.
Significant
gene sets with
differential expression in adipose tissue of diabetic compared with nondiabetic co-twins (GSEA
analysis with q < 0.05)
The
differential expression analysis between males and females for all
genes in each tissue is provided in Dataset S3.
We therefore focused our
analysis of
differential gene expression on those
genes that have at least a 25 % probability of being within the highly - expressed distribution: 17,698
genes in the VNO and 17,983 in the OM (see Materials and methods for details).
For a typical RNA - Seq project: mapping to the transcriptome including QA,
expression quantification,
differential expression analysis,
gene ontology and (un --RRB- supervised classification.
We show further support for the method's efficacy by exploiting allele - specific
gene expression levels, and
differential expression analyses.