Results 11 to 20 of about 567,059 (348)
SCRABBLE: single-cell RNA-seq imputation constrained by bulk RNA-seq data [PDF]
Genome Biology, 2019 Single-cell RNA-seq data contain a large proportion of zeros for expressed genes. Such dropout events present a fundamental challenge for various types of data analyses. Here, we describe the SCRABBLE algorithm to address this problem. SCRABBLE leverages
Tao Peng, Qin Zhu, Penghang Yin, Kai Tan
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RNA-seq: technical variability and sampling [PDF]
BMC Genomics, 2011 RNA-seq is revolutionizing the way we study transcriptomes. mRNA can be surveyed without prior knowledge of gene transcripts. Alternative splicing of transcript isoforms and the identification of previously unknown exons are being reported. Initial reports of differences in exon usage, and splicing between samples as well as quantitative differences ...
Lauren M. McIntyre +6 more
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RNA-Seq: revelation of the messengers [PDF]
Trends in Plant Science, 2013 Next-generation RNA-sequencing (RNA-Seq) is rapidly outcompeting microarrays as the technology of choice for whole-transcriptome studies. However, the bioinformatics skills required for RNA-Seq data analysis often pose a significant hurdle for many biologists.
Van Verk +6 more
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Bioinformatics, 2011 Abstract Summary: RNA-Seq is an exciting methodology that leverages the power of high-throughput sequencing to measure RNA transcript counts at an unprecedented accuracy. However, the data generated from this process are extremely large and biologist-friendly tools with which to analyze it are sorely lacking. MultiExperiment Viewer (MeV)
Daniel Schlauch +3 more
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RNA-Seq Assembly – Are We There Yet? [PDF]
Frontiers in Plant Science, 2012 Transcriptomic sequence resources represent invaluable assets for research, in particular for non-model species without a sequenced genome. To date, the Next Generation Sequencing technologies 454/Roche and Illumina have been used to generate transcriptome sequence databases by mRNA-Seq for more than fifty different plant species.
Schliesky, Simon +3 more
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Statistical Modeling of RNA-Seq Data [PDF]
Statistical Science, 2011 Recently, ultra high-throughput sequencing of RNA (RNA-Seq) has been developed as an approach for analysis of gene expression. By obtaining tens or even hundreds of millions of reads of transcribed sequences, an RNA-Seq experiment can offer a comprehensive survey of the population of genes (transcripts) in any sample of interest.
Julia Salzman, Hui Jiang, Wing Hung Wong
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A map of bat virus receptors derived from single-cell multiomics
Scientific Data, 2022 Measurement(s) RNA-seq gene expression profiling assay • ATAC-Seq Technology Type(s) RNA-seq of coding RNA from single cells • Single cell ATAC-seq (cell index) Sample Characteristic - Organism Rhinolophus ...
Tianhang Lv +18 more
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Frontiers in Plant Science, 2022 RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences ...
Min Tu +4 more
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Journal of Lipid Research, 2023 Small noncoding RNAs (sncRNAs) play diverse roles in numerous biological processes. While the widely used RNA sequencing (RNA-Seq) method has advanced sncRNA discovery, RNA modifications can interfere with the complementary DNA library construction ...
Rebecca Hernandez +8 more
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Discover hidden splicing variations by mapping personal transcriptomes to personal genomes. [PDF]
, 2015 RNA-seq has become a popular technology for studying genetic variation of pre-mRNA alternative splicing. Commonly used RNA-seq aligners rely on the consensus splice site dinucleotide motifs to map reads across splice junctions.
Bahrami-Samani, Emad +4 more
core +6 more sources