RSeQC: quality control of RNA-seq experiments

By Liguo Wang, Shengqin Wang. Bioinform., 2012

2,467 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/98a77917a7fff289c8dae7ea1c4b8f9aea692ccc

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In Molecular Biology

Citations in the corpus

Dido3-dependent SFPQ recruitment maintains efficiency in mammalian alternative splicing (2019, methodology): “The fragcount script from the RSeQC package (45) was used to determine expression levels.”
Zc3h13 regulates nuclear RNA m6A methylation and mouse embryonic stem cell self-renewal (2018, neutral): “…(Trapnell et al., 2010) http://cole-trapnell-lab.github.io/cufflinks Signalplot This paper N/A Rseqc (Wang et al., 2012) http://rseqc.sourceforge.net/ exomePeak (Meng et al., 2014)…”
Coactivator condensation at super-enhancers links phase separation and gene control (2018, methodology): “Per-transcript expression was quantified as RPKMs using RPKM_count from the RSeQC package (76).”
Using SPAdes De Novo Assembler (2020, methodology): “For more details see the RSeQC manual at http://rseqc.sourceforge.net/ #infer-experiment-py.”
A survey of best practices for RNA-seq data analysis (2016, methodology): “Tools for quality control in mapping include Picard [16], RSeQC [17] and Qualimap [18].”
MAP-RSeq: Mayo Analysis Pipeline for RNA sequencing (2014, methodology): “The workflow uses the RSeQC software [21] to estimate distance between paired-end reads, evaluate sequencing depth for alternate splicing events, determine rate of duplicate reads, and calculate coverage of reads across genes as shown in the example report file (Figure 2).”
Transcriptomic characteristics of bronchoalveolar lavage fluid and peripheral blood mononuclear cells in COVID-19 patients (2020, background): “0) [23], and visualized in UCSC genome browser [24] with custom track hub.”