Sentence examples for both probeset and transcript from inspiring English sources

For Gene1.0 and HTA2.0, Affymetrix Expression Console (v1.3) was used to generate default raw data at both probeset and transcript cluster levels, and the raw data were RMA background corrected, median polish summarized and quantile normalized.

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.

Clinical outcome was also integrated with gene expression data such that Kaplan-Maier plot may be dynamically generated for each probeset and transcript cluster.

Affymetrix Power Tool [ 35] (APT Release 1.8.5) were used to pre-process exon array data such as probe intensity normalization, probeset and transcript expression summarization, implementation of MiDAS algorithm [ 36] etc.

To facilitate exon array data access and visualization, we have developed a novel database and visualization system displaying both gene-level and exon-level expressions for array probesets and transcript clusters (http://pob.abcc.ncifcrf.gov/cgi-bin/JK).

To evaluate their potential impact on the previous gene expression data, we compared our new list of SNP-containing probesets and transcript clusters derived from the 1000 Genomes Project with the ∼350,000 affected probesets from the SNPinProbe database (dbSNP v129).

First, the detection p-value was used to remove probesets and transcript clusters with undetectable signals.

For data analysis, we used Affymetrix Power Tool (APT) to get signal intensities for probesets and transcript clusters.

All probesets and transcript clusters were analysed by FIRMA, as it is part of the default aroma.affymetrix workflow.

The probes, probesets and transcript clusters from these files annotated as targeting core human transcripts (i.e. non Affymetrix control probes) were combined, based on their annotated genomic coordinates, to create a mapping table with a three tier hierarchy where probes belong to probesets that in turn belong to transcript clusters (mapping table available on request).

It is worth noting that aroma.affymetrix enables the analysis at the three levels of annotation mentioned above, and also that it provides intensity estimates for probes, probesets and transcript clusters, allowing for a variety of options for the analysis.