Sentence examples for and significant analysis of from inspiring English sources

Class comparison and significant analysis of microarrays (SAMs) were performed to identify differentially expressed miRNAs.

T-test and Significant Analysis of Microarray analyses (SAM) [ 29] were carried out to identify dysregulated mRNAs.

Filter methods include correlation-based feature selection (CFS) [ 244], t-test [ 243, 245], information gain [ 243, 245], mutual information [ 246], entropy-based methods [ 247], Euclidian distance [ 245], signal to noise ratio [ 245], and significant analysis of microarrays [ 248].

After Between-array normalization and signal filtration (IsGeneDetected, WellAboveNeg) performed by RMA algorithm [ 28], the data was analyzed by T-test and Significant Analysis of Microarray analyses SAM) [ 29] to identify differentially expressed miRNAs.

Using Student's  t-test and Significant Analysis of Microarray analyses (SAM) [ 29] (FDR < 0.05 from student's t-test and q-value < 0.05 from SAM), 32 miRNAs were found to be significantly differentially expressed between CRC tissues and their corresponding adjacent normal tissues, including 16 up-regulated and 16 down-regulated which were shown in Additional file 1: Table S2.

A one-way ANOVA and SAM (Significant Analysis of Microarrays) procedures were applied to look for time-, strand-, and CM-R/CM-S-specific variation in gene expression in the full data set.

We used analysis of variance (ANOVA), t-score analysis and SAM (Significant Analysis of Microarray) of the J-Express program package for identification of differentially expressed genes.

Statistical analyses were performed with TIGR Microarray Data Analysis System (TM4) including MIDAS Microarray Data Analysis Systemm; Quackenbush, 2002) for normalisation and SAM (significant analysis of microarrays; Tusher et al, 2001) for identification of genes with significant differential regulation.

Statistical analyses were performed using TM4 Microarray software suite including MIDAS (Microarray Data Analysis System) for normalization (47) and SAM (Significant Analysis of Microarrays) for the determination of genes showing significant differential regulation (48).

By means of the trial results obtained on real-world data, the structure has been shown to regularize highly available feature selection and prediction methods, such as Significant Analysis of Microarray (SAM), Information gain (IG) and the Lasso-type prediction model.

To define differentially expressed transcripts between wide type and heat shock conditions, SAM (significant analysis of microarray, siggenes package from BioConductor) was employed to compute the q value.