Sentence examples for ranking of transcripts from inspiring English sources
Although the choice of these hyper-parameter values is arbitrary to some extent, if the model is robust this choice should not affect the ranking of transcripts according to the PPs.
These results therefore indicate that the ranking of transcripts according to the PP of the parental effect, obtained by our model, is robust to the choice of hyper-parameter empirical values.
AUC ranking of transcripts revealed that the top 5% of genes are enriched for nucleosome components (P = 7.15 × 10−5), chromatin assembly and disassembly genes (P = 0.001), helicases (P = 0.007), and ATPases (P = 0.008).
The X-axis indicates ranks of transcripts from the top and Y-axis is the measure of relative transcript levels (WT/DKO) in log2 scale.
The ranked lists of transcripts were used to test for GO enrichment towards the top of the list, using GOrilla [ 20, 21].
The ranked sets of transcripts were subjected to gene set enrichment analysis using likelihood scores based on a pre-ranked list and SpaMo identified TF-pair target genes as datasets [ 18, 19].
As a result, we obtain ranks of the transcripts according to how strongly associated they are with the different pathways given their metabolite coresponse patterns.
In this view, representation is not given as a normalized percentage but as ranks of individual transcripts by category and may be compared directly between exosomal and parental cell samples.
An alternative approach to define reference genes is the use of various statistical tests that essentially rank the variability of transcripts abundances for sets of genes that are analysed [ 1].
The 2927 selected genes were ranked by level of transcripts, producing a profile similar to the one obtained with CWGs at 5-days; 1161 genes (39.7%) above background level, 1295 (44.2%) with a low transcript level, 238 (8.1%) with a moderate level, and 235 (8.0%) with a high level.
This was used for ranking the expressed set of transcripts on the microarray based on the similarity of the gene expression profiles represented in the form of likelihood scores.
