Sentence examples for modules we selected from inspiring English sources

Based on more complex TF modules, we selected a small set of factors for experimental validation.

To investigate the biological functions of the WGCNA modules, we selected the highly connected "hub genes" within each module.

From these modules we selected 2 modules from which the co-expression of the genes was observed in more than 5 samples (to increase the robustness of the analysis).

For the Blue and Yellow modules, we selected gene lists of 500 genes with module membership p-values smaller than 10-22 and corresponding local false discovery rates (q-values) smaller than 10-5.

However, for the OI module we selected a commercial filter (Edmund Optics TechSpec Fluorescence Bandpass, Barrington, NJ, USA) with a center wavelength of 692 nm and wider bandwidth of ~40 nm to match the dye's emission peak and to detect a larger part of the emission spectrum.

For each type of module, we selected genes which were identified as being highly used (i.e. one gene involved in multiple gene modules) as representative of the whole set (Methods).

During the interviewer-administered module, we selected as many as four of the most recent of those partners (if four or more had been reported) plus the enrollment partner, if one existed, into a subsample for extensive characterization.

For Gene Ontology enrichment of genes in each module, we selected GOTERM_BP_FAT, GOTERM_CC_FAT and GOTERM_MF_FAT as the gene set categories.

To detect LOH regions, we first counted the number of SNVs in 100-kb sequence blocks by VCFtools SNPdensity module, and then we selected those blocks where the number of homozygous SNVs was at least 10-times greater than the number of heterozygous SNVs and the number of homozygous SNVs was more than 50.

On the basis of those selection criteria we selected five modules for functional annotation: the Blue Module (275 genes), the Brown Module (62 genes), the Lightyellow Module (21 genes), the Black Module (105 genes) and the Greenyellow Module (41 genes).

We selected modules detected by SA algorithm for similarity analysis and functional classification.