This method is ideal to analyze a large number of transcripts in a given tissue, and it allows the quantitative cataloguing and comparison of expressed genes under various physiological and pathological states [ 13- 15].
In practice, when setting up preamplification for samples of unknown target concentrations, one may initially analyze a few selected, ubiquitously expressed transcripts, such as GAPDH or ACTB, by regular qPCR and based on these data design the preamplification protocol.
They could show that cross-platform comparability is improved when the transcriptome is analyzed by a transcript-specific approach and a minimum probe set size of four is used.
We developed a method to analyze transcripts in A and P cells in single wing imaginal discs from third instar larvae.
Of the four researchers who were involved in qualitative data analysis, each one analyzed and coded a set of transcripts as the 'first' coder and then analyzed a second set of transcripts as a 'second' coder.
For each transcript analyzed, a standard curve with predetermined concentrations and serial diluted respective PCR amplification products from 0.1 ng to 0.000 01 ng was constructed.
Schulz and coworkers analyzed a set of retina transcripts from a mixed population of different datasets and suggested that about 13,000 transcripts might describe 90% of the adult retinome [ 14].
A single coder analyzed all transcripts, with > 25% of transcripts coded by a second coder to ensure quality control and consistency.
We analyzed a set of cellular transcripts known to be involved in the stress response under these various conditions of infection.
Two members of the research team double-analyzed a subset of the transcripts; disagreements and insights were discussed and alternative interpretations were incorporated in the analysis.
In this work, by constructing and analyzing a dataset of toxin transcripts from the venom gland of the scorpion Boi, we were able to follow the evolutionary path leading to scorpion toxin diversification.
