Unknown

Dataset Information

0

Multi-platform assessment of transcriptional profiling technologies utilizing a precise probe mapping methodology.


ABSTRACT: The arrival of RNA-seq as a high-throughput method competitive to the established microarray technologies has necessarily driven a need for comparative evaluation. To date, cross-platform comparisons of these technologies have been relatively few in number of platforms analyzed and were typically gene name annotation oriented. Here, we present a more extensive and yet precise assessment to elucidate differences and similarities in performance of numerous aspects including dynamic range, fidelity of raw signal and fold-change with sample titration, and concordance with qRT-PCR (TaqMan). To ensure that these results were not confounded by incompatible comparisons, we introduce the concept of probe mapping directed "transcript pattern". A transcript pattern identifies probe(set)s across platforms that target a common set of transcripts for a specific gene. Thus, three levels of data were examined: entire data sets, data derived from a subset of 15,442 RefSeq genes common across platforms, and data derived from the transcript pattern defined subset of 7,034 RefSeq genes.In general, there were substantial core similarities between all 6 platforms evaluated; but, to varying degrees, the two RNA-seq protocols outperformed three of the four microarray platforms in most categories. Notably, a fourth microarray platform, Agilent with a modified protocol, was comparable, or marginally superior, to the RNA-seq protocols within these same assessments, especially in regards to fold-change evaluation. Furthermore, these 3 platforms (Agilent and two RNA-seq methods) demonstrated over 80% fold-change concordance with the gold standard qRT-PCR (TaqMan).This study suggests that microarrays can perform on nearly equal footing with RNA-seq, in certain key features, specifically when the dynamic range is comparable. Furthermore, the concept of a transcript pattern has been introduced that may minimize potential confounding factors of multi-platform comparison and may be useful for similar evaluations.

SUBMITTER: Yu J 

PROVIDER: S-EPMC4575490 | biostudies-literature | 2015 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications


<h4>Background</h4>The arrival of RNA-seq as a high-throughput method competitive to the established microarray technologies has necessarily driven a need for comparative evaluation. To date, cross-platform comparisons of these technologies have been relatively few in number of platforms analyzed and were typically gene name annotation oriented. Here, we present a more extensive and yet precise assessment to elucidate differences and similarities in performance of numerous aspects including dyna  ...[more]

Similar Datasets

2015-09-28 | GSE66649 | GEO
2015-09-28 | GSE66648 | GEO
2015-09-28 | GSE66626 | GEO
2015-09-28 | GSE66614 | GEO
2015-09-28 | GSE66592 | GEO
2015-09-28 | GSE66590 | GEO
2015-09-28 | GSE66628 | GEO
| S-EPMC6877524 | biostudies-literature
| S-EPMC4737954 | biostudies-literature
| S-EPMC10750099 | biostudies-literature