Comparative analysis of RNA-Seq alignment algorithms and the RNA-Seq unified mapper (RUM)

By Gregory R. Grant, Michael H. Farkas, Angel D. Pizarro, Nicholas F. Lahens, Jonathan Schug, Brian P. Brunk, Christian J. Stoeckert Jr., John B. Hogenesch, Eric A. Pierce. Bioinform., 2011

356 citations recorded by the source corpus.

Subfields: Molecular Biology

View Paper: https://www.semanticscholar.org/paper/b07ffcd7d9b297aecdde011e6a8d95fe4c1c2911

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In Molecular Biology

Citations in the corpus

RNA Sequencing and Analysis (2015, unknown): “The more commonly used RNA-Seq alignment tools include GSNAP (Wu and Nacu 2010), MapSplice (Wang et al. 2010a), RUM (Grant et al. 2011), STAR (Dobin et al. 2013), and TopHat (Trapnell et al. 2009) (Table 2).”
Complexity of the Alternative Splicing Landscape in Plants[C][W][OPEN] (2013, methodology): “The exon-first approach starts with aligning reads to the genome, and then the remaining unaligned reads are chopped and realigned (e.g., Tophat [Trapnell et al., 2009], MapSplice [Wang et al., 2010a], RNA-seq Unified Mapper [Grant et al., 2011], and SpliceMap [Auet al., 2010]).”
STAR: ultrafast universal RNA-seq aligner (2013, unknown): “Various sequence alignment algorithms have been recently developed to tackle these challenges (Au et al., 2010; De Bona, et al., 2008; Grant et al., 2011; Han et al., 2011; Trapnell et al., 2009; Wang et al., 2010; Wu and Nacu, 2010; Zhang et al., 2012).”
TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions (2013, methodology): “2 The number of read alignments from TopHat2, GSNAP, RUM, MapSplice, and STAR.”
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): “Recently, different aligners and algorithm for RNA-seq analysis were compared, based on their mapping quality and splice junctions (24).”
Detecting circular RNAs: bioinformatic and experimental challenges (2016, methodology): “Several tools for simulating data exist, with a common choice being BEERS 67 , which simulates human or mouse paired-end RNA-seq from the Illumina platform with varying levels of gene expression, splicing, sequencing error, single-nucleotide variants (SNVs) and indels.”
Repetitive DNA and next-generation sequencing: computational challenges and solutions (2011, methodology): “RNA‑seq aligners, such as TopHat 58 , MapSplice 59 , rnaSeqMap 60 , RUM 61 and SpliceMap 62 are capable of aligning a short read to two distinct locations.”