RNA-seq transcript assembly evaluation
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Project description:To assess the performance of computational methods for exon identification, transcript reconstruction and expression level quantification from RNA-seq data, 24 protocol variants of 14 independent software programs (AUGUSTUS, Cufflinks, Exonerate, GSTRUCT, iReckon, mGene, mTim, NextGeneid, Oases, SLIDE, Transomics, Trembly, Tromer and Velvet) were evaluated against transcriptome data from human cells and two model organisms. The following supplementary data files are also available from ArrayExpress at http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1730/files/ : (1) Reference annotation used in the study, (2) Alignments used for reference annotation, (3) Predicted exons and transcript models submitted for evaluation and (4) NanoString nCounter probes and detection counts. Each file is described in greater detail in file http://www.ebi.ac.uk/arrayexpress/experiments/E-MTAB-1730/files/E-MTAB-1730_supplemental_files.xlsx .
2013-07-15 | E-MTAB-1730 | biostudies-arrayexpress
Project description:Accurate annotation of transcript isoforms is crucial to understand gene functions, but automated methods for reconstructing full-length transcripts from RNA sequencing (RNA-seq) data remain imprecise. We developed Bookend, a software package for transcript assembly that incorporates data from different RNA-seq techniques, with a focus on identifying and utilizing RNA 5′ and 3′ ends. Through end-guided assembly with Bookend we demonstrate that correct modeling of transcript start and end sites is essential for precise transcript assembly. Furthermore, we discovered that utilization of end-labeled reads present in full-length single-cell RNA-seq (scRNA-seq) datasets dramatically improves the precision of transcript assembly in single cells. Finally, we show that hybrid assembly across short-read, long-read, and end-capture RNA-seq datasets from Arabidopsis, as well as meta-assembly of RNA-seq from single mouse embryonic stem cells (mESCs) can produce end-to-end transcript annotations of comparable quality to reference annotations in these model organisms.
2022-01-08 | GSE189482 | GEO
Project description:RNA-seq read alignment evaluation
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Project description:RNA-Seq analysis carried out in three different backcrosses based on Iberian breed with Landrace, Pietrain and Duroc breeds
2017-10-31 | PRJEB23068 | EVA
Project description:New tools for improved long-read transcript assembly and coalescence with its short-read counterpart are required. Using our short- and long-read measurements from different cell lines with spiked-in standards, we systematically compared key parameters and biases in the read alignment and assembly of transcripts. We report a cDNA synthesis artifact in long-read datasets that impacts the identity and quantitation of assembled transcripts. We developed a computational pipeline to strand long-read cDNA libraries that markedly improves assembly of transcripts from long-reads. Incorporating stranded long-reads in a new hybrid assembly approach, we demonstrate its efficacy for improved characterization of challenging lncRNA transcripts. Our workflow can be applied to a wide range of transcriptomics datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.
2023-10-14 | GSE215357 | GEO
Project description:New tools for improved long-read transcript assembly and coalescence with its short-read counterpart are required. Using our short- and long-read measurements from different cell lines with spiked-in standards, we systematically compared key parameters and biases in the read alignment and assembly of transcripts. We report a cDNA synthesis artifact in long-read datasets that impacts the identity and quantitation of assembled transcripts. We developed a computational pipeline to strand long-read cDNA libraries that markedly improves assembly of transcripts from long-reads. Incorporating stranded long-reads in a new hybrid assembly approach, we demonstrate its efficacy for improved characterization of challenging lncRNA transcripts. Our workflow can be applied to a wide range of transcriptomics datasets for superior demarcation of transcript ends and refined isoform structure, which can enable better differential gene expression analyses and molecular manipulations of transcripts.
2023-10-14 | GSE215355 | GEO
Project description:RNA-Seq: assessment of transcript level analysis tools
| PRJNA302625 | ENA
Project description:We introduce an approach to transcript discovery coupled with a statistical model for RNA-Seq experiments that produces estimates of transcript abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation timeseries. We detected 13,689 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the timeseries revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development. Timeseries of C2C12 myoblast RNA-Seq
2010-04-14 | E-GEOD-20846 | biostudies-arrayexpress
Project description:Systematic evaluation of RNA-Seq preparation protocol performance
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Project description:Bulk RNA-Seq - Evaluation of single-Cell RNA Sequencing Platforms
| PRJNA597870 | ENA