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 logoAnthony Bretaudeau avatar Anthony BretaudeauWilliam Durand avatar William DurandMateusz Kuzak avatar Mateusz Kuzakorcid logoGraeme Tyson avatar Graeme TysonXi Liu avatar Xi Liuorcid logoArmin Dadras avatar Armin DadrasAnne Siegel avatar Anne Siegelorcid logoErwan Corre avatar Erwan Correorcid logoMarisa Loach avatar Marisa LoachGildas Le Corguillé avatar Gildas Le Corguilléorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoMo Heydarian avatar Mo Heydarianorcid logoAnne Fouilloux avatar Anne Fouillouxorcid logoFlorian Heyl avatar Florian HeylXavier Garnier avatar Xavier Garnierorcid logoLucille Delisle avatar Lucille DelisleMatt Ritchie avatar Matt RitchieJames Taylor avatar James TaylorCasper de Visser avatar Casper de Visserorcid logoBjörn Grüning avatar Björn GrüningNiall Beard avatar Niall Beardorcid logoCristóbal Gallardo avatar Cristóbal GallardoMatthias Bernt avatar Matthias BerntSimon Bray avatar Simon BrayEkaterina Polkh avatar Ekaterina Polkhorcid logoHelena Rasche avatar Helena RascheIGC Bioinformatics Unit avatar IGC Bioinformatics UnitThorben Stehling avatar Thorben Stehlingorcid logoAmirhossein Naghsh Nilchi avatar Amirhossein Naghsh Nilchiorcid logoPavankumar Videm avatar Pavankumar VidemCharity Law avatar Charity Laworcid logoMorgan Howells avatar Morgan Howellsorcid logoMateo Boudet avatar Mateo Boudetorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosCharlotte Adang avatar Charlotte AdangPablo Moreno avatar Pablo Morenoorcid logoLinelle Abueg avatar Linelle AbuegAnton Nekrutenko avatar Anton Nekrutenkoorcid logoSofoklis Keisaris avatar Sofoklis Keisarisorcid logoClemens Blank avatar Clemens Blankorcid logoIacopo Cristoferi avatar Iacopo CristoferiSanjay Kumar Srikakulam avatar Sanjay Kumar SrikakulamPeter-Bram 't Hoen avatar Peter-Bram 't Hoenorcid logoJulia Jakiela avatar Julia Jakielaorcid logoMarek Ostaszewski avatar Marek Ostaszewskiorcid logoMyrthe van Baardwijk avatar Myrthe van BaardwijkMarius van den Beek avatar Marius van den Beekorcid logoBérénice Batut avatar Bérénice BatutOlivier Dameron avatar Olivier Dameronorcid logoTeresa Müller avatar Teresa MüllerBelinda Phipson avatar Belinda PhipsonJovana Maksimovic avatar Jovana Maksimovicorcid logoSaskia Hiltemann avatar Saskia HiltemannHarriet Dashnow avatar Harriet DashnowMehmet Tekman avatar Mehmet Tekmanorcid logoWendi Bacon avatar Wendi Baconorcid logoMartin Čech avatar Martin Čechorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoToby Hodges avatar Toby HodgesCarlos Chee Mendonça avatar Carlos Chee MendonçaAnna Trigos avatar Anna Trigosorcid logoDiana Chiang Jurado avatar Diana Chiang Juradoorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-SolanoChao Zhang avatar Chao ZhangShian Su avatar Shian SuAndrea Bagnacani avatar Andrea Bagnacaniorcid logoClea Siguret avatar Clea SiguretMarkus Wolfien avatar Markus Wolfienorcid logoMallory Freeberg avatar Mallory FreebergDaniel Maticzka avatar Daniel Maticzkaorcid logoMatti Hoch avatar Matti Hochorcid logoMaria Doyle avatar Maria DoyleJosé Manuel Domínguez avatar José Manuel Domínguezorcid logoMira Kuntz avatar Mira Kuntzorcid logoAnika Erxleben avatar Anika Erxlebenorcid logoPeter van Heusden avatar Peter van Heusdenorcid logoNicola Soranzo avatar Nicola Soranzo

Funding

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

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de.NBI
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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)
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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.