t-Test at the Probe Level: An Alternative Method to Identify Statistically Significant Genes for Microarray Data
Marcelo Boareto; Nestor Caticha · 2014 · Microarrays
WASTE classifies this as Negative / Null Result Report · AI classification, approximate
The study found no significant effect — useful as a negative control or null benchmark for your own design.
Abstract (excerpt)
Microarray data analysis typically consists in identifying a list of differentially expressed genes (DEG), i.e., the genes that are differentially expressed between two experimental conditions. Variance shrinkage methods have been…
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Metadata source: Crossref · DOI 10.3390/microarrays3040340