RNA-Seq: a revolutionary tool for transcriptomics
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TLDR
The RNA-Seq approach to transcriptome profiling that uses deep-sequencing technologies provides a far more precise measurement of levels of transcripts and their isoforms than other methods.Abstract:
RNA-Seq is a recently developed approach to transcriptome profiling that uses deep-sequencing technologies. Studies using this method have already altered our view of the extent and complexity of eukaryotic transcriptomes. RNA-Seq also provides a far more precise measurement of levels of transcripts and their isoforms than other methods. This article describes the RNA-Seq approach, the challenges associated with its application, and the advances made so far in characterizing several eukaryote transcriptomes.read more
Citations
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Journal ArticleDOI
Transcriptomics technologies
TL;DR: The first attempts to study the whole transcriptome began in the early 1990s, and technological advances since the late 1990s have made transcriptomics a widespread discipline as mentioned in this paper, which has enabled the study of how gene expression changes in different organisms and has been instrumental in the understanding of human disease.
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An accurate and robust imputation method scImpute for single-cell RNA-seq data.
Wei Vivian Li,Jingyi Jessica Li +1 more
TL;DR: Evaluation based on both simulated and real human and mouse scRNA-seq data suggests that scImpute is an effective tool to recover transcriptome dynamics masked by dropouts, and scImputes to identify likely dropouts and enhance the clustering of cell subpopulations, improve the accuracy of differential expression analysis, and aid the study of gene expression dynamics.
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Translating RNA sequencing into clinical diagnostics: opportunities and challenges
TL;DR: It is the diversity of RNA species detected through RNA-seq that holds new promise for the multi-faceted clinical applicability of RNA-based measures, including the potential of extracellular RNAs as non-invasive diagnostic indicators of disease.
Journal ArticleDOI
RNA-Seq analysis to capture the transcriptome landscape of a single cell
Fuchou Tang,Catalin Barbacioru,Ellen Nordman,Bin Li,Nanlan Xu,Vladimir I. Bashkirov,Kaiqin Lao,M. Azim Surani +7 more
TL;DR: This protocol can generate deep-sequencing libraries for 16 single-cell samples within 6 d and can capture up to 75% more genes expressed in early embryos compared with cDNA microarray techniques.
Journal ArticleDOI
PLEK: a tool for predicting long non-coding RNAs and messenger RNAs based on an improved k-mer scheme
TL;DR: PLEK is an efficient alignment-free computational tool to distinguish lncRNAs from mRNAs in RNA-seq transcriptomes of species lacking reference genomes and is especially suitable for PacBio or 454 sequencing data and large-scale transcriptome data.
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