Sentence examples for ease analyses from inspiring English sources
EASE analyses tested each list against all genes on the chip and overrepresentation describes a group of genes belonging to a certain GO category that appear more often in the given input list than expected to occur if the distribution were random.
To identify biological processes that were statistically enriched in our lists of DEGs, we conducted EASE analyses using the database for annotation visualization and integrated discovery (DAVID [ 55].
The EASE analyses in SS and myxoid/round-cell liposarcomas employed the top 4000 and 1000 genes (with 11% FDR) respectively.
To facilitate this process, we used data coding to ease analyses of larger data files and ensure the accuracy of our analysis.
When significant probes are organized according to molecular function ontology with a fold change threshold of two, ontological categories of differentially abundant transcripts emerge by EASE analyses (Tables 2 and 3).
We used EASE analyses, as implemented by DAVID (Dennis et al. 2003), to identify biological process, cellular component, and molecular function gene ontology terms that were statistically enriched in lists of DEGs.
We introduce the ratio (gamma = gamma_{2} /gamma_{1}) to ease the analyses, where competition is increased through increasing (gamma).
We also summed the three OCPs HCB, trans-nonachlor, and DDE for ease of analyses, with DDE representing the bulk.
Classification scores InfoKeep and Ease were analysed using ANOVA.
To test CRIS performance with the MIST system, we decided to train MIST with a set of 50 day-to-day events notes and, we trained it to de-identify First Names (FN) and Last Names (LNs) only for ease of analysing data and training the model as accurately as possible (in depth details of how MIST works is published in Aberdeen et al., 2010) [ 28].
EASE and Gene Set analyses were used to determine the statistical likelihood that a priori families of genes were over-represented and differentially expressed [49].
