Sentence examples for transcript and generated from inspiring English sources

To obtain a subset of variable genes, we calculated the coefficient of variation (CV) for each transcript and generated a set of 5095 "active genes" containing the transcripts with the highest (15% of the total) CV scores.

This confirmed a single ORF per transcript, and generated an NCBI.tbl file for submission.

At least two members of the research team read each interview transcript and generated a list of themes.

These probabilistic models provide estimates for the variance and credibility interval for each transcript and generate more accurate estimates of low levels of gene expression on benchmark datasets when compared with other stochastic models (Text S1).

The project team met to open code an initial transcript, and generate a draft coding frame.

In addition to filtering the transcriptome, Transvestigator also prepared the dataset for NCBI Transcriptome Shotgun Assembly (TSA) submission by ensuring the predicted ORF is in the positive strand, confirming presence of only a single ORF per transcript, and generating a properly formatted NCBI.tbl file for submission.

ELL and MS read and re-read the transcripts and generated initial codes.

Meanwhile, another investigator (ML) read all the transcripts and generated emergent and recurrent themes independently.

The two authors coded the transcripts and generated descriptive and analytical themes independently.

Two investigators independently analyzed the transcripts and generated codes to represent informants' statements.

At the start of the coding process, SCB and YA read the initial transcripts and generated preliminary codes.