scholarly journals satuRn: Scalable analysis of differential transcript usage for bulk and single-cell RNA-sequencing applications

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 374
Author(s):  
Jeroen Gilis ◽  
Kristoffer Vitting-Seerup ◽  
Koen Van den Berge ◽  
Lieven Clement
Keyword(s):  
Rate Control ◽  
Single Gene ◽  
Experimental Designs ◽  
Rna Seq ◽  
Modelling Framework ◽  
Gene Dysregulation ◽  
False Discovery ◽  
Generalized Linear Modelling ◽  
Linear Modelling ◽  
Scalable Analysis

Alternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.

scholarly journals satuRn: Scalable Analysis of differential Transcript Usage for bulk and single-cell RNA-sequencing applications

2021 ◽  
Author(s):  
Jeroen Gilis ◽  
Kristoffer Vitting-Seerup ◽  
Koen Van den Berge ◽  
Lieven Clement
Keyword(s):  
Rate Control ◽  
Single Gene ◽  
Experimental Designs ◽  
Rna Seq ◽  
Modelling Framework ◽  
Gene Dysregulation ◽  
False Discovery ◽  
Generalized Linear Modelling ◽  
Linear Modelling ◽  
Scalable Analysis

AbstractAlternative splicing produces multiple functional transcripts from a single gene. Dysregulation of splicing is known to be associated with disease and as a hallmark of cancer. Existing tools for differential transcript usage (DTU) analysis either lack in performance, cannot account for complex experimental designs or do not scale to massive scRNA-seq data. We introduce satuRn, a fast and flexible quasi-binomial generalized linear modelling framework that is on par with the best performing DTU methods from the bulk RNA-seq realm, while providing good false discovery rate control, addressing complex experimental designs and scaling to scRNA-seq applications.

scholarly journals Searchlight: automated bulk RNA-seq exploration and visualisation using dynamically generated R scripts

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
John J. Cole ◽  
Bekir A. Faydaci ◽  
David McGuinness ◽  
Robin Shaw ◽  
Rose A. Maciewicz ◽  
...  
Keyword(s):  
Visual Analysis ◽  
Service Providers ◽  
Single Gene ◽  
Experimental Designs ◽  
Rna Seq ◽  
Analysis Study ◽  
Processing Pipeline ◽  
Shiny App ◽  
User Friendly ◽  
Downstream User

Abstract Background Once bulk RNA-seq data has been processed, i.e. aligned and then expression and differential tables generated, there remains the essential process where the biology is explored, visualized and interpreted. Without the use of a visualisation and interpretation pipeline this step can be time consuming and laborious, and is often completed using R. Though commercial visualisation and interpretation pipelines are comprehensive, freely available pipelines are currently more limited. Results Here we demonstrate Searchlight, a freely available bulk RNA-seq visualisation and interpretation pipeline. Searchlight provides: a comprehensive statistical and visual analysis, focusing on the global, pathway and single gene levels; compatibility with most differential experimental designs irrespective of organism or experimental complexity, via three workflows; reports; and support for downstream user modification of plots via user-friendly R-scripts and a Shiny app. We show that Searchlight offers greater automation than current best tools (VIPER and BioJupies). We demonstrate in a timed re-analysis study, that alongside a standard bulk RNA-seq processing pipeline, Searchlight can be used to complete bulk RNA-seq projects up to the point of manuscript quality figures, in under 3 h. Conclusions Compared to a manual R based analysis or current best freely available pipelines (VIPER and BioJupies), Searchlight can reduce the time and effort needed to complete bulk RNA-seq projects to manuscript level. Searchlight is suitable for bioinformaticians, service providers and bench scientists. https://github.com/Searchlight2/Searchlight2.

scholarly journals Polyester: simulating RNA-seq datasets with differential transcript expression

2014 ◽  
Author(s):  
Alyssa C Frazee ◽  
Andrew E Jaffe ◽  
Ben Langmead ◽  
Jeffrey Leek
Keyword(s):  
Differential Expression ◽  
Rate Control ◽  
Differential Expression Analysis ◽  
R Package ◽  
Experimental Designs ◽  
Rna Seq ◽  
Reasonable Approximation ◽  
Methods Development ◽  
Error Rate Control ◽  
Expression Status

Motivation: Statistical methods development for differential expression analysis of RNA sequencing (RNA-seq) requires software tools to assess accuracy and error rate control. Since true differential expression status is often unknown in experimental datasets, artificially-constructed datasets must be utilized, either by generating costly spike-in experiments or by simulating RNA-seq data. Results: Polyester is an R package designed to simulate RNA-seq data, beginning with an experimental design and ending with collections of RNA-seq reads. Its main advantage is the ability to simulate reads indicating isoform-level differential expression across biological replicates for a variety of experimental designs. Data generated by Polyester is a reasonable approximation to real RNA-seq data and standard differential expression workflows can recover differential expression set in the simulation by the user. Availability and Implementation: Polyester is freely available from Bioconductor (http://bioconductor.org/).

Wellbeing and Running Events in Qatar: The Ooredoo Doha Marathon

2021 ◽  
Author(s):  
Kevin Filo ◽  
Millicent Kennelly ◽  
Richard J. Buning ◽  
Rana Sobh
Keyword(s):  
Goal Setting ◽  
Qualitative Data ◽  
Online Questionnaire ◽  
Sport Event ◽  
Sense Of Direction ◽  
Generalized Linear Modelling ◽  
Linear Modelling ◽  
Personal Connections ◽  
Males And Females

Research into participatory sport event experiences and wellbeing outcomes has increased, however, much of this work explores Western contexts. The purpose of the current research is to examine the wellbeing outcomes related to sport event participation in Qatar, as well as how these outcomes differ across nationalities and by gender. An online questionnaire was administered to participants of the 2017 Ooredoo Doha Marathon (ODM) (N = 239). Inductive coding of responses to the open-ended items uncovered activation of relationships, meaning and accomplishment. The qualitative data revealed that event participation allowed participants to strengthen personal connections with others, fostered a sense of direction and allowed for goal setting among participants, and enabled participants to experience achievement. Meanwhile, generalized linear modelling revealed Qatari nationals and expats as well as males and females differentially reported wellbeing based on PERMA domains.

scholarly journals Grouped False-Discovery Rate for Removing the Gene-set-Level Bias of RNA-seq

2013 ◽  
Vol 9 ◽  
pp. EBO.S13099 ◽  
Author(s):  
Tae Young Yang ◽  
Seongmun Jeong
Keyword(s):  
False Discovery Rate ◽  
Rna Seq ◽  
Gene Set ◽  
False Discovery

scholarly journals Genetic effect in leaf and xylem transcriptome variations among Eucalyptus urophylla x grandis hybrids in field conditions

2018 ◽  
Vol 67 (1) ◽  
pp. 57-65
Author(s):  
Alexandre Vaillant ◽  
Astrid Honvault ◽  
Stéphanie Bocs ◽  
Maryline Summo ◽  
Garel Makouanzi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Variance Components ◽  
Genetic Effect ◽  
Field Conditions ◽  
Eucalyptus Urophylla ◽  
Rna Seq ◽  
Intermediate Phenotypes ◽  
False Discovery ◽  
Hybrid Clones ◽  
Selection Of

Abstract To assess the genetic and environmental components of gene-expression variation among trees we used RNA-seq technology and Eucalyptus urophylla x grandis hybrid clones tested in field conditions. Leaf and xylem transcriptomes of three 20 month old clones differing in terms of growth, repeated in two blocks, were investigated. Transcriptomes were very similar between ramets. The number of expressed genes was significantly (P<0.05) higher in leaf (25,665±634) than in xylem (23,637±1,241). A pairwise clone comparisons approach showed that 4.5 to 14 % of the genes were diffe­rentially expressed (false discovery rate [FDR]<0.05) in leaf and 7.1 to 16 % in xylem. An assessment of among clone variance components revealed significant results in leaf and xylem in 3431 (248) genes (at FDR<0.2) and 160 (3) (at FDR<0.05), respectively. These two complementary approa­ches displayed correlated results. A focus on the phenylpro­panoid, cellulose and xylan pathways revealed a large majo­rity of low expressed genes and a few highly expressed ones, with RPKM values ranging from nearly 0 to 600 in leaf and 10,000 in xylem. Out of the 115 genes of these pathways, 45 showed differential expression for at least one pair of geno­type, five of which displaying also clone variance compo­nents. These preliminary results are promising in evaluating whether gene expression can serve as possible ‘intermediate phenotypes’ that could improve the accuracy of selection of grossly observable traits.

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