transcriptomics

Tutorials covering transcriptomics

Material

You can view the tutorial materials in different languages by clicking the dropdown icon next to the slides () and tutorial () buttons below.

Proteomics

Lesson Slides Hands-on Recordings Input dataset Workflows
Multiomics data analysis using MultiGSEA
multi-omics transcriptomics proteomics metabolomics

Single Cell

Lesson Slides Hands-on Recordings Input dataset Workflows
Bulk RNA Deconvolution with MuSiC
transcriptomics deconvolution
Pseudobulk Analysis with Decoupler and EdgeR
transcriptomics pseudobulk
Comparing inferred cell compositions using MuSiC deconvolution
transcriptomics deconvolution
Evaluating Reference Data for Bulk RNA Deconvolution
transcriptomics deconvolution
Bulk matrix to ESet | Creating the bulk RNA-seq dataset for deconvolution
transcriptomics data management deconvolution

Transcriptomics

Lesson Slides Hands-on Recordings Input dataset Workflows
1: RNA-Seq reads to counts
collections mouse QC
2: RNA-seq counts to genes
limma-voom mouse QC
3: RNA-seq genes to pathways
mouse
CLIP-Seq data analysis from pre-processing to motif detection
Differential abundance testing of small RNAs
GO Enrichment Analysis
Genome-wide alternative splicing analysis
alternative splicing isoform switching
Introduction to Transcriptomics
Network analysis with Heinz
metatranscriptomics network analysis
RNA Seq Counts to Viz in R
interactive-tools
RNA-RNA interactome data analysis
RNA-Seq analysis with AskOmics Interactive Tool
RNA-seq Alignment with STAR
Small Non-coding RNA Clustering using BlockClust
Visualization of RNA-Seq results with CummeRbund
Visualization of RNA-Seq results with Volcano Plot
Visualization of RNA-Seq results with Volcano Plot in R
interactive-tools
Visualization of RNA-Seq results with heatmap2
Whole transcriptome analysis of Arabidopsis thaliana
miRNA plants stress tolerance
Pathway analysis with the MINERVA Platform
bulk rna-seq viz cyoa
Reference-based RNA-Seq data analysis
bulk rna-seq collections drosophila QC cyoa deutsch español italiano
De novo transcriptome reconstruction with RNA-Seq

Contributors

This material was contributed to by:

orcid logoPavankumar Videm avatar Pavankumar Videmorcid logoMartin Čech avatar Martin Čechorcid logoMorgan Howells avatar Morgan Howellsorcid logoWendi Bacon avatar Wendi Baconorcid logoSofoklis Keisaris avatar Sofoklis Keisarisorcid logoClemens Blank avatar Clemens BlankBelinda Phipson avatar Belinda PhipsonMarius van den Beek avatar Marius van den BeekAnton Nekrutenko avatar Anton Nekrutenkoorcid logoAmirhossein Naghsh Nilchi avatar Amirhossein Naghsh NilchiMateusz Kuzak avatar Mateusz KuzakAnna Trigos avatar Anna TrigosJosé Manuel Domínguez avatar José Manuel DomínguezCasper de Visser avatar Casper de VisserAnne Siegel avatar Anne Siegelorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoMatti Hoch avatar Matti Hochorcid logoMarisa Loach avatar Marisa Loachorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosMatthias Bernt avatar Matthias Berntorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoAnthony Bretaudeau avatar Anthony BretaudeauThorben Stehling avatar Thorben Stehlingorcid logoIacopo Cristoferi avatar Iacopo Cristoferiorcid logoFlorian Heyl avatar Florian Heylorcid logoAnika Erxleben avatar Anika ErxlebenMarkus Wolfien avatar Markus Wolfienorcid logoGraeme Tyson avatar Graeme Tysonorcid logoHelena Rasche avatar Helena RascheXavier Garnier avatar Xavier GarnierJovana Maksimovic avatar Jovana MaksimovicGildas Le Corguillé avatar Gildas Le Corguilléorcid logoNicola Soranzo avatar Nicola SoranzoDaniel Maticzka avatar Daniel MaticzkaCharlotte Adang avatar Charlotte AdangChao Zhang avatar Chao ZhangEkaterina Polkh avatar Ekaterina Polkhorcid logoLinelle Abueg avatar Linelle AbuegCharity Law avatar Charity Laworcid logoMateo Boudet avatar Mateo Boudetorcid logoMallory Freeberg avatar Mallory FreebergPeter-Bram 't Hoen avatar Peter-Bram 't HoenNiall Beard avatar Niall Beardorcid logoMo Heydarian avatar Mo Heydarianorcid logoJulia Jakiela avatar Julia JakielaHarriet Dashnow avatar Harriet DashnowMatt Ritchie avatar Matt Ritchieorcid logoCristóbal Gallardo avatar Cristóbal GallardoIGC Bioinformatics Unit avatar IGC Bioinformatics Unitorcid logoLucille Delisle avatar Lucille Delisleorcid logoToby Hodges avatar Toby HodgesOlivier Dameron avatar Olivier Dameronorcid logoClea Siguret avatar Clea Siguretorcid logoMyrthe van Baardwijk avatar Myrthe van Baardwijkorcid logoErwan Corre avatar Erwan CorreSanjay Kumar Srikakulam avatar Sanjay Kumar SrikakulamShian Su avatar Shian SuPablo Moreno avatar Pablo Morenoorcid logoPeter van Heusden avatar Peter van HeusdenWilliam Durand avatar William DurandSimon Bray avatar Simon Brayorcid logoMarek Ostaszewski avatar Marek Ostaszewskiorcid logoBjörn Grüning avatar Björn Grüningorcid logoBérénice Batut avatar Bérénice BatutAndrea Bagnacani avatar Andrea Bagnacaniorcid logoMira Kuntz avatar Mira KuntzJames Taylor avatar James TaylorMehmet Tekman avatar Mehmet Tekmanorcid logoArmin Dadras avatar Armin Dadrasorcid logoSaskia Hiltemann avatar Saskia HiltemannXi Liu avatar Xi Liuorcid logoAnne Fouilloux avatar Anne Fouillouxorcid logoDiana Chiang Jurado avatar Diana Chiang JuradoCarlos Chee Mendonça avatar Carlos Chee Mendonçaorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-Solanoorcid logoMaria Doyle avatar Maria Doyleorcid logoTeresa Müller avatar Teresa Müller

Funding

These individuals or organisations provided funding support for the development of this resource

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DASH UK
This Fellowship was funded through the ELIXIR-UK DaSH project as part of the UKRI Innovation Scholars: Data Science Training in Health and Bioscience call (DaSH). (MR/V038966/1). The project aims to embed Research Data Management (RDM) know-how into UK universities and institutes by producing and delivering training in FAIR data stewardship using ELIXIR-UK knowledge and resources.
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The University of Melbourne
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de.NBI
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Australian BioCommons
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Melbourne Bioinformatics
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Gallantries
This project (2020-1-NL01-KA203-064717) is funded with the support of the Erasmus+ programme of the European Union. Their funding has supported a large number of tutorials within the GTN across a wide array of topics.
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BeYond-COVID
BY-COVID is an EC funded project that tackles the data challenges that can hinder effective pandemic response. This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement № 101046203 (BY-COVID)