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While new methods of transcript measurement are rapidly becoming available [37], [38], the usefulness of microarrays in the study of qualitative transcript biology still has not been fully explored.
Several methods of transcript analysis were employed across different tissues in barley and maize.
However, beyond alignment, no methods of transcript inference utilize the genome sequence, so this issue cannot affect performance at that level.
Correlation between the two methods of transcript quantitation are likely to improve as the sponge genome assembly and gene definitions are further refined.
Although RNA-Seq still could not replace the role of FL-cDNA in gene discovery, sophisticated methods of transcript reconstruction through RNA-Seq in the near future may help us to reconstruct more full-length transcripts.
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However, that earlier study used end-point PCR to quantify transcripts which is a less sensitive method of transcript quantification than real-time PCR.
A second limitation is that we limited our assembled transcript data to those produced by TCGA, namely using one transcript definition (UCSC) and one method of transcript assembly (RSEM), though different methods are known to produce different results (19).
Finally, pilot-scale projects were incorporated to generate preliminary data for several additional applications, including a comparison of methods for transcript profiling and analysis, examination of antisense and intron transcription, chromatin immunoprecipitation studies, expression of selected host genes, and polymorphism detection in highly variable genes.
Tag-Seq, and other sequencing-based methods of quantifying transcript expression, provides a powerful alternative to hybridization-based assays of gene expression, particularly for cross-species comparisons.
RNA-seq is replacing other methods of quantifying transcript expression, including microarray platforms [ 24], as it overcomes some of their limitations, such as detection of only those transcripts that are represented on microarrays, low dynamic range (limited upper and lower limits of detection), and thus provides more accurate quantification of differential transcript expression.
In comparison to the significantly differentially expressed gene list from microarray profiling of yeast using oligo-dT primers, tag sequencing confirmed 35% of the genes with gene expression levels consistent between the two methods of measuring transcript abundance, but left 57% of the genes without statistically significant confirmation (cf. Figures 2, 3, see Additional File 5).
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