How does Rnaseq data differ from microarray data?
The main difference between RNA-Seq and microarrays is that the former allows for full sequencing of the whole transcriptome while the latter only profiles predefined transcripts/genes through hybridization.
Where do you find gene expression data?
Gene expression data have been archived as microarray and RNA-seq datasets in two public databases, Gene Expression Omnibus (GEO) and ArrayExpress (AE). In 2018, the DNA DataBank of Japan started a similar repository called the Genomic Expression Archive (GEA).
What is the difference between RNA-Seq and Qpcr?
While qRT-PCR is useful for quantifying the expression of a few genes, it can only detect known sequences. In contrast, RNA sequencing (RNA-Seq) using NGS can detect both known and novel transcripts.
What is the difference between RNA-Seq and microarrays?
Data were compared to determine any potential added scientific (i.e., better biological or toxicological insight) value offered by RNA-Seq compared to microarrays. RNA-Seq identified more differentially expressed protein-coding genes and provided a wider quantitative range of expression level changes when compared to microarrays.
Are all data sets similar in gene expression patterns?
The correlations of correlations of the original data sets are considerably larger than those calculated for random correlation matrices. Thus, all data sets are more similar in their gene expression patterns than expected by chance. However, the observed similarities are not equally distributed across all pairs of data sets.
Which microarray platforms are used in the production of the data sets?
The four data sets were produced using three different microarray platforms: Agilent spotted oligonucleotide microarrays (here referred to as Rosetta1 [ 5] and Rosetta2 [ 20 ]), Affymetrix GeneChips (referred to as Geneatlas [ 8 ]), and cDNA microarrays (referred to as Stanford [ 21 ]).
Does differential expression differ between Rosetta 1 and Rosetta 2?
The differential expression found in the data sets by Rosetta1 and Rosetta2 were highly correlated whereas the Stanford data set showed more distinct results compared to the other data sets. Nevertheless, a prominent similarity in differential expression across all data sets exists.