Sentence examples for between transcript clusters and from inspiring English sources

Many of the transcript clusters correspond to non-coding RNAs (lincRNAs, snoRNAs, miRNAs) while others have a many-to-one relationship between transcript clusters and genes.

Though the independent data covered only a small part of the transcript clusters outside annotated genes and promoters, the good correspondence between transcript clusters and data from RNA-Seq, miRNA and lincRNA lead us to conclude that the transcript clusters did represent transcript-related regulatory elements.

Fig. 2 shows the pairwise signal pattern between transcript clusters from the two arrays.

In addition to distinguishing between transcript clusters within toxin families, our approach was sensitive enough to distinguish between alleles within clusters (Table 3).

Because no sig-mer is shared between transcript clusters, the problem reduces to quantifying transcript abundances using sig-mer counts within each cluster, which can be solved much more efficiently and can be easily parallelized.

We found 4,677 and 5,125 significant associations between expression quantitative nucleotides (eQTNs) and transcript clusters in the CEU and the YRI samples, respectively.

For example, xmapcore [ 54] provides annotation data and cross-mappings between genetic features such as transcript clusters or exons and Affymetrix probesets.

We found an increased overlap between these noncoding RNA transcripts and our transcript clusters compared to enhancer clusters and overlaps expected by chance (Table 2).

To map between gene-level estimates from the sequencing data to exon array data, we use the mapping between RefSeq transcripts and exon array transcript clusters.

Then (iii) we ranked the probesets according to their absolute mean difference: as the scores are comparable across transcript clusters, larger average differences between the normal and cancer samples will point at exons more differentially spliced between the two conditions.

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.