Sentence examples for several transcript clusters from inspiring English sources
Several transcript clusters were highly induced in both the light and seedling leaves, including clusters III, V, VI, VII, XIII, XVI, and XVIII, with cluster XVI containing the most highly induced transcripts.
Several transcripts (10 clusters, 22 clones) were similar to hypothetical secreted peptides from other scorpions.
We, in fact, observed overexpression of several transcripts belonging to clusters B and C and downregulation of a gene data set present in cluster D. The functional correlates of these changes have been discussed above.
Next, transcript clusters are analysed with several statistical models to detect differential expression or splicing, and the transcripts of interest are annotated and visualized at the end.
Some transcript clusters present unspecific annotation and have several possible associated gene names.
This analysis confirmed the specific over transcription of several genes in the Imida-R strain and identified nine main transcript clusters based on their expression profile across strains.
To reduce the false positive rate in the splicing variant identification, several filtering steps were applied to the signals of both probesets and transcript clusters.
To confirm the microarray results, we chose several transcripts from category D, cluster 8 (C5 and LBP) and cluster 1 (SERPINA 3 and C4A), and measured their expressions with real-time PCR using the same RNA samples used for microarray studies.
Affymetrix Human Transcriptome Arrays (HTA 2.0) probed 30,682 annotated transcript clusters, of which 24,371 coding and 5,389 non-coding transcript clusters were deemed expressed in maternal whole blood.
For microarrays, transcript clusters were considered expressed if at least one probeset targeting the same transcript cluster had a detection p-value < 0.05 in at least 5 of the 32 samples.
Mapping of transcript clusters to UniGene identifiers Transcript cluster IDs were assigned to their corresponding UniGene clusters using transcript_annot file [80].
