De novo assembly and analysis of RNA-seq data

By Gordon Robertson, Jacqueline E. Schein, Readman Chiu, R. Corbett, M. Field, Shaun D. Jackman, K. Mungall, Sam Lee, H. M. Okada, Jenny Q. Qian and 19 more. Nature Methods, 2010

993 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/c63ce741ecccc27849662493ee5878e3a4c33d26

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Citations in the corpus

Phylogeny of the manta and devilrays (Chondrichthyes: mobulidae), with an updated taxonomic arrangement for the family (2018, methodology): “Assembled contigs were filtered, extended and merged using Trans-ABySS v.1.4.4 (Robertson et al., 2010).”
Comprehensive and Integrative Genomic Characterization of Hepatocellular Carcinoma (2017, neutral): “4.8 Robertson et al., 2010 PMID: 20935650 Gene fusion analysis Tophat-v2.”
An Extensive Evaluation of Read Trimming Effects on Illumina NGS Data Analysis (2013, background): “However, the read correction approach cannot be applied wherever sequence abundance is intrinsically not uniform, such as in transcriptomics (RNA-Seq) [20], metagenomics [21] or heterogeneous cancer DNA samples [22].”
rnaSPAdes: a de novo transcriptome assembler and its application to RNA-Seq data (2018, neutral): “To address these constraints, de novo transcriptome assemblers [7–11] have emerged as a viable complement to the reference-based tools.”
A Comparative Study of Techniques for Differential Expression Analysis on RNA-Seq Data (2014, background): “Compared to microarray techniques, RNA-Seq can be performed without prior knowledge of reference sequences and enables a wide range of applications including transcriptome de novo assembly [1-4], abundance estimation [5-9], and detection of alternative splicing events [10-12], all of which have revo”
Comprehensive Molecular Characterization of Muscle-Invasive Bladder Cancer. (2017, positive): “We performed de novo assembly (Robertson et al., 2010) with ABySS v1.”
A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae (2012, methodology): “We first address the impact of different aligners in detecting DGE: Gsnap (33), Stampy (34) and TopHat (35) and successively evaluate the impact of using five different statistical methods: (i) baySeq (31), (ii) Cuffdiff (23), (iii) DESeq (30), (iv) edgeR (25) and (v) NOISeq (32).”
TopHat-Fusion: an algorithm for discovery of novel fusion transcripts (2011, methodology): “A different strategy is used by Trans-ABySS [16], a de novo transcript assembler, which first uses ABySS [17] to assemble RNA-seq reads into full-length transcripts.”
Genetic alterations activating kinase and cytokine receptor signaling in high-risk acute lymphoblastic leukemia (2012, methodology): “We used multiple complementary analysis pipelines, including deFuse (McPherson et al., 2011), Mosaik (Marth, 2010), CREST (Wang et al., 2011), CONSERTING (Zhang et al., 2012), and Trans-ABySS (Robertson et al., 2010) to identify rearrangements, structural variations, and sequence mutations.”
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome (2011, methodology): “Second, using transcript-level alignments easily allows for analyses of samples from species without sequenced genomes but with a decently characterized transcriptome (perhaps via RNA-Seq transcriptome assembly [11,12]).”
De novo transcript sequence reconstruction from RNA-Seq: reference generation and analysis with Trinity (2013, methodology): “Available de novo RNA-seq assembly software include, among others, Oases 7 , SOAPdenovo-trans and TransABySS 6 .”