RSeQC: quality control of RNA-seq experiments

Wang, Liguo; Wang, Shengqin; Li, Wei

doi:10.1093/bioinformatics/bts356

Cited by 2,217 publications

(1,606 citation statements)

References 7 publications

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“…The data set was analyzed using standard quality check (QC) procedures (DeLuca et al 2012;Wang et al 2012) and new approaches (I Mohorianu, A Bretman, DT Smith, EK Fowler, T Dalmay, T Chapman, in prep.). We assessed (i) read number and complexity (i.e., ratio of nonredundant to redundant reads), (ii) nucleotide composition and strand bias, (iii) genome matching and annotation matching reads (e.g., mRNAs, t/rRNAs, miRNAs, UTRs, introns, intergenic regions), and (iv) correlation and Jaccard similarity indices on the original versus normalized data.…”

Section: Bioinformatics Analysismentioning

confidence: 99%

Genomic responses to the socio-sexual environment in male Drosophila melanogaster exposed to conspecific rivals

Mohorianu

Bretman

Smith

et al. 2017

RNA

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Socio-sexual environments have profound effects on fitness. Local sex ratios can alter the threat of sexual competition, to which males respond via plasticity in reproductive behaviors and ejaculate composition. In Drosophila melanogaster, males detect the presence of conspecific, same-sex mating rivals prior to mating using multiple, redundant sensory cues. Males that respond to rivals gain significant fitness benefits by altering mating duration and ejaculate composition. Here we investigated the underlying genome-wide changes involved. We used RNA-seq to analyze male transcriptomic responses 2, 26, and 50 h after exposure to rivals, a time period that was previously identified as encompassing the major facets of male responses to rivals. The results showed a strong early activation of multiple sensory genes in the head-thorax (HT), prior to the expression of any phenotypic differences. This gene expression response was reduced by 26 h, at the time of maximum phenotypic change, and shut off by 50 h. In the abdomen (A), fewer genes changed in expression and gene expression responses appeared to increase over time. The results also suggested that different sets of functionally equivalent genes might be activated in different replicates. This could represent a mechanism by which robustness is conferred upon highly plastic traits. Overall, our study reveals that mRNA-seq can identify subtle genomic signatures characteristic of flexible behavioral phenotypes.

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Section: Bioinformatics Analysismentioning

confidence: 99%

Genomic responses to the socio-sexual environment in male Drosophila melanogaster exposed to conspecific rivals

Mohorianu

Bretman

Smith

et al. 2017

RNA

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“…The number of reads per transcript was measured using RSeQC (54). Whole transcriptome gene expression was calculated by normalizing the read counts per transcript by the kilobases of the transcript per million mapped reads that has at least 10 times coverage denoted as adjusted RPKM (55).…”

Section: (Illumina)mentioning

confidence: 99%

Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing

Lee

López-Díaz

Khan

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

171

150

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The acute cellular response to stress generates a subpopulation of reversibly stress-tolerant cells under conditions that are lethal to the majority of the population. Stress tolerance is attributed to heterogeneity of gene expression within the population to ensure survival of a minority. We performed whole transcriptome sequencing analyses of metastatic human breast cancer cells subjected to the chemotherapeutic agent paclitaxel at the single-cell and population levels. Here we show that specific transcriptional programs are enacted within untreated, stressed, and drugtolerant cell groups while generating high heterogeneity between single cells within and between groups. We further demonstrate that drug-tolerant cells contain specific RNA variants residing in genes involved in microtubule organization and stabilization, as well as cell adhesion and cell surface signaling. In addition, the gene expression profile of drug-tolerant cells is similar to that of untreated cells within a few doublings. Thus, single-cell analyses reveal the dynamics of the stress response in terms of cell-specific RNA variants driving heterogeneity, the survival of a minority population through generation of specific RNA variants, and the efficient reconversion of stress-tolerant cells back to normalcy.

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“…Reads were mapped to the human genome using Bowtie1 (default), Bowtie1 (best strata), Bowtie2 (vsl), BWA (df), and MicroRazers (sl18.se.pa). Mismatch profiles were generated by RSeqQC (Wang et al 2012). …”

Section: Effect Of Aligner Accuracy On Expression Quantification Andmentioning

confidence: 99%

Evaluation of microRNA alignment techniques

Ziemann

Kaspi²,

El‐Osta³

2016

RNA

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Genomic alignment of small RNA (smRNA) sequences such as microRNAs poses considerable challenges due to their short length (∼21 nucleotides [nt]) as well as the large size and complexity of plant and animal genomes. While several tools have been developed for high-throughput mapping of longer mRNA-seq reads (>30 nt), there are few that are specifically designed for mapping of smRNA reads including microRNAs. The accuracy of these mappers has not been systematically determined in the case of smRNA-seq. In addition, it is unknown whether these aligners accurately map smRNA reads containing sequence errors and polymorphisms. By using simulated read sets, we determine the alignment sensitivity and accuracy of 16 short-read mappers and quantify their robustness to mismatches, indels, and nontemplated nucleotide additions. These were explored in the context of a plant genome (Oryza sativa, ∼500 Mbp) and a mammalian genome (Homo sapiens, ∼3.1 Gbp). Analysis of simulated and real smRNA-seq data demonstrates that mapper selection impacts differential expression results and interpretation. These results will inform on best practice for smRNA mapping and enable more accurate smRNA detection and quantification of expression and RNA editing.

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RSeQC: quality control of RNA-seq experiments

Abstract: RSeQC is written in Python and C. Source code and a comprehensive user's manual are freely available at: http://code.google.com/p/rseqc/.

Cited by 2,217 publications

References 7 publications

Genomic responses to the socio-sexual environment in male Drosophila melanogaster exposed to conspecific rivals

Genomic responses to the socio-sexual environment in male Drosophila melanogaster exposed to conspecific rivals

Single-cell analyses of transcriptional heterogeneity during drug tolerance transition in cancer cells by RNA sequencing

Evaluation of microRNA alignment techniques

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