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Across all SCN inoculated samples, transcript counts underwent normalization and variance estimation using the DESeq R package.
In unpublished studies of the same NBEC samples, transcript abundance values for several DNA repair genes were correlated with these antioxidant genes.
To compare gene expression abundance in different samples, transcript count information for sequences corresponding to each unigene was calculated and normalized to the reads per kilobase of exon model per million mapped reads (RPKM) values [ 48].
To test whether gadph behaves as a housekeeping gene in the analyzed samples, transcript levels of gadph and dap were measured by qPCR in each cDNA sample and the ratios of control transcript to the endogenous transcript gadph were calculated.
To investigate the expression level of each unigene in different samples, transcript abundance estimates were obtained by running RNA-seq by Expectation-Maximization analysis separately for each sample, which uses an iterative process to fractionally assign reads to each transcript based on the probabilities of the reads being derived from each transcript [ 62].
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As with the mouse samples, transcripts were added continually with more reads.
Instead of using molecular hybridization to 'capture' transcript molecules of interest, RNA-Seq samples transcripts present in the starting material by direct sequencing.
Compared with milk cell samples, transcripts for eight of the lactose synthesis genes were more abundant (p < 0.05) in milk fat and the other six were not different.
Initial high-throughput RNA sequencing (RNA-Seq) experiments have revealed a complex and dynamic transcriptome, but because it samples transcripts in proportion to their abundances, assessing the extent and nature of low-level transcription using this technique has been difficult.
The number of copies of each sample transcript was then determined with the aid of the LightCycler software.
Each sample transcript was assayed in triplicate and copy numbers were indicated for each transcript.
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