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 logoMarisa Loach avatar Marisa Loachorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoPeter van Heusden avatar Peter van HeusdenDaniel Maticzka avatar Daniel MaticzkaIGC Bioinformatics Unit avatar IGC Bioinformatics UnitPeter-Bram 't Hoen avatar Peter-Bram 't HoenMateusz Kuzak avatar Mateusz Kuzakorcid logoMallory Freeberg avatar Mallory FreebergMatt Ritchie avatar Matt RitchieAndrea Bagnacani avatar Andrea BagnacaniAnton Nekrutenko avatar Anton NekrutenkoXavier Garnier avatar Xavier GarnierBelinda Phipson avatar Belinda Phipsonorcid logoLinelle Abueg avatar Linelle Abuegorcid logoMarek Ostaszewski avatar Marek Ostaszewskiorcid logoMatti Hoch avatar Matti Hochorcid logoToby Hodges avatar Toby Hodgesorcid logoSofoklis Keisaris avatar Sofoklis KeisarisCharlotte Adang avatar Charlotte Adangorcid logoMaria Doyle avatar Maria Doyleorcid logoSaskia Hiltemann avatar Saskia HiltemannXi Liu avatar Xi Liuorcid logoCristóbal Gallardo avatar Cristóbal GallardoJosé Manuel Domínguez avatar José Manuel Domínguezorcid logoAnthony Bretaudeau avatar Anthony BretaudeauThorben Stehling avatar Thorben StehlingPablo Moreno avatar Pablo Morenoorcid logoBérénice Batut avatar Bérénice BatutMehmet Tekman avatar Mehmet Tekmanorcid logoMo Heydarian avatar Mo HeydarianHarriet Dashnow avatar Harriet Dashnoworcid logoAmirhossein Naghsh Nilchi avatar Amirhossein Naghsh Nilchiorcid logoMateo Boudet avatar Mateo Boudetorcid logoMartin Čech avatar Martin ČechNiall Beard avatar Niall BeardMatthias Bernt avatar Matthias BerntCarlos Chee Mendonça avatar Carlos Chee Mendonçaorcid logoJulia Jakiela avatar Julia Jakielaorcid logoMyrthe van Baardwijk avatar Myrthe van Baardwijkorcid logoPavankumar Videm avatar Pavankumar Videmorcid logoHelena Rasche avatar Helena Rascheorcid logoDiana Chiang Jurado avatar Diana Chiang JuradoJames Taylor avatar James TaylorShian Su avatar Shian Suorcid logoIacopo Cristoferi avatar Iacopo Cristoferiorcid logoArmin Dadras avatar Armin Dadrasorcid logoAnika Erxleben avatar Anika ErxlebenEkaterina Polkh avatar Ekaterina Polkhorcid logoErwan Corre avatar Erwan Correorcid logoClea Siguret avatar Clea Siguretorcid logoWolfgang Maier avatar Wolfgang MaierWilliam Durand avatar William Durandorcid logoClemens Blank avatar Clemens Blankorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-Solanoorcid logoFotis E. Psomopoulos avatar Fotis E. Psomopoulosorcid logoLucille Delisle avatar Lucille Delisleorcid logoBjörn Grüning avatar Björn GrüningChao Zhang avatar Chao ZhangAnna Trigos avatar Anna Trigosorcid logoMira Kuntz avatar Mira Kuntzorcid logoTeresa Müller avatar Teresa MüllerCharity Law avatar Charity Laworcid logoMorgan Howells avatar Morgan Howellsorcid logoWendi Bacon avatar Wendi BaconAnne Siegel avatar Anne SiegelCasper de Visser avatar Casper de VisserSanjay Kumar Srikakulam avatar Sanjay Kumar Srikakulamorcid logoFlorian Heyl avatar Florian HeylMarius van den Beek avatar Marius van den BeekJovana Maksimovic avatar Jovana Maksimovicorcid logoGraeme Tyson avatar Graeme TysonGildas Le Corguillé avatar Gildas Le CorguilléSimon Bray avatar Simon BrayOlivier Dameron avatar Olivier DameronMarkus Wolfien avatar Markus Wolfienorcid logoAnne Fouilloux avatar Anne Fouillouxorcid 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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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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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)