Stem cell transcriptome profiling via massive-scale mRNA sequencing

By N. Cloonan, A. Forrest, G. Kolle, B. Gardiner, G. Faulkner, Mellissa K Brown, Darrin F. Taylor, Anita L. Steptoe, Shivangi Wani, G. Bethel and 9 more. Nature Methods, 2008

1,130 citations recorded by the source corpus.

Subfields: Cancer Research, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/253fba2a2b4060c4adf47f625764182e67420334

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Citations in the corpus

Characterization of the single-cell transcriptional landscape by highly multiplex RNA-seq. (2011, positive): “RNA sequencing (RNA-seq) overcomes these problems by sequencing RNA directly (Ozsolak et al. 2009) or after reverse-transcription to cDNA (Cloonan et al. 2008; Mortazavi et al. 2008; Wang et al. 2008).”
Transcriptome analysis by strand-specific sequencing of complementary DNA (2009, methodology): “Two modifications of the ds cDNA synthesis have been suggested so far that allow one to preserve information about the direction of the transcripts (12,13).”
A statistical perspective on algorithmic leveraging (2013, methodology): “1 Linear model for bias correction in RNA-Seq data In order to illustrate how our methods perform on a real data set with nearly uniform leverage scores, we consider an RNA-Seq data set containing n = 51, 751 read counts from embryonic mouse stem cells [15].”
voom: precision weights unlock linear model analysis tools for RNA-seq read counts (2014, methodology): “One common approach to summarize RNA-seq data is to count the number of sequence reads mapping to each gene or genomic feature of interest [11, 12, 13, 14].”
Statistical Design and Analysis of RNA Sequencing Data (2010, methodology): “At present, there are three widely accepted commercially available NGS devices [Illumina’s Genome Analyzer, Applied Biosystems’ (Foster City, CA) SOLiD, and the 454 Genome Sequencer FLX] for RNA-Seq (C loonan et al .”
DIANA-TarBase v8: a decade-long collection of experimentally supported miRNA–gene interactions (2017, background): “conditions and link to the actual publication are presented (6).”
Real-Time DNA Sequencing from Single Polymerase Molecules (2009, methodology): “Next-generation DNA sequencing methods have changed whole-genome sequencing projects into routine procedures (reviewed in Mardis, 2008) and have been adapted to other areas, such as transcriptome sequencing and epigenetics (Cloonan et al., 2008; Cokus et al., 2008; Fullwood et al., 2009; Maher et al”
Applications of next-generation sequencing to the study of biological invasions (2015, background): “Several programs are available to map RNA reads to a reference (Cloonan et al., 2008; Li et al., 2008; Mortazavi et al., 2008; Langmead et al., 2009) and consideration of the available reference (genome or transcriptome), and mapping program(s) used, is important.”