RNA-Seq: assessment of transcript level analysis tools
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PROVIDER: PRJNA302625 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:This study uses spiked-in transcript in order to compares various bioinformatics approaches and tools to assemble, quantify abundance and detect differentially expressed transcripts using RNA-Seq data. Mouse total RNA seq was extracted from embryonic stem cells (ES) before (designated as day 0) and four days after the addition of retinoic acid. 48 spikes were made in vitro from plasmid constructs and added to the total RNA in different concentrations (each mix has a set of different spike concentrations, see paper's method). We found that detection of differential expression at the gene level is acceptable, yet on the transcript-isofom level all tools tested were lacking accuracy and precision.
2016-04-26 | GSE71802 | GEO
Project description:This study uses spiked-in transcript in order to compare various bioinformatics approaches and tools to assemble, quantify abundance and detect differentially expressed transcripts using RNA-Seq data. Mouse total RNA seq was extracted from embryonic stem cells (ES) before (designated as day 0) and four days after the addition of retinoic acid. 48 spikes were made in vitro from plasmid constructs and added to the total RNA in different concentrations (each mix has a set of different spike concentrations, see paper's method). We found that detection of differential expression at the gene level is acceptable, yet on the transcript-isofom level all tools tested were lacking accuracy and precision. This set of microarrays was performed for the purpose of selecting unexpressed loci, to which spikes can be added
2016-04-26 | GSE75138 | GEO
Project description:This SuperSeries is composed of the SubSeries listed below.
2016-04-26 | GSE75139 | GEO
Project description:Benchmarking of available tools for the estimation of isoform-level transcript abundances from RNA-seq data
| PRJNA269376 | ENA
Project description:RNA-Seq: assessment of transcript level analysis tools [seq]
| PRJNA292105 | ENA
Project description:RNA-Seq: assessment of transcript level analysis tools [array]
| PRJNA302627 | ENA
Project description:High-throughput sequencing of cDNA (RNA-seq) is used extensively to characterize the transcriptome of cells. Many transcriptomics studies aim at comparing either abundance levels or the transcriptome composition between given conditions, and as a first step, the sequencing reads must be used as the basis for abundance quantification of transcriptomic features of interest, such as genes or transcripts. Several different quantification approaches have been proposed, ranging from simple counting of reads overlapping given genomic regions to more complex estimation of underlying transcript abundances. In this paper, we show that gene-level abundance estimates and statistical inference offer advantages over transcript-level analyses, in terms of both performance and interpretability. We also illustrate that while the presence of differential isoform usage can lead to inflated false discovery rates in differential expression analyses on simple count matrices, and incorporation of transcript-level abundance estimates improves the performance in simulated data, the difference is relatively minor in several real data sets. Finally, we provide an R package (tximport) to help users integrate transcript-level abundance estimates from common quantification pipelines into count-based statistical inference engines.
2015-12-10 | E-MTAB-4119 | biostudies-arrayexpress
Project description:State-of-the-art algorithms for m6A detection and quantification via nanopore direct RNA sequencing have been continuously developed, little is known about their capacities and limitations, which makes a comprehensive assessment in urgent need. Therefore, we performed comprehensive benchmarking of 10 computational tools relying on current-based and base-calling “errors” strategies for m6A detection by nanopore sequencing.
2023-03-01 | GSE195618 | GEO
Project description:Transcript expression level in control and Setd1a-knockdown mouse explant retina
| PRJNA646500 | ENA
Project description:Microarray comparisons of transcript level in wild-type Arabidopsis and eif3h mutant plants. Goal: To detect any change in transcript level between WT and eif3h mutant. BACKGROUND: The eukaryotic translation initiation factor eIF3 has multiple roles during the initiation of translation of cytoplasmic mRNAs. However, the contributions of individual subunits of eIF3 to the translation of specific mRNAs remain poorly understood. RESULTS: Working with stable reporter transgenes in Arabidopsis thaliana it was demonstrated that the h subunit of eIF3 contributes to the efficient translation initiation of mRNAs harboring upstream open reading frames (uORFs) in their 5’ leader sequence. uORFs, which can function as devices for translational regulation, are present in over 30% of Arabidopsis mRNAs, and are enriched among mRNAs for transcriptional regulators and protein modifying enzymes. Microarray comparisons of polysome loading in wild-type and eif3h mutant plants revealed that eIF3h generally helps to maintain efficient polysome loading of mRNAs harboring multiple uORFs. Independently, eIF3h also boosted polysome loading of mRNAs with long coding sequences. Moreover, the lesion in eIF3h revealed a concerted upregulation of translation for specific functional subgroups of mRNAs, including ribosomal proteins and proteins involved in photosynthesis. CONCLUSIONS: The intact eIF3h protein contributes to efficient translation initiation on 5’ leader sequences harboring multiple uORFs, although mRNA features independent of uORFs were also implicated. Moreover, our data suggest that regulons of translational control can be revealed by mutations in generic translation initiation factors. Keywords: mutant, total RNA
2007-05-01 | GSE6025 | GEO