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:

Casper de Visser avatar Casper de Visserorcid logoClea Siguret avatar Clea Siguretorcid logoMatti Hoch avatar Matti Hochorcid logoMarek Ostaszewski avatar Marek Ostaszewskiorcid logoFlorian Heyl avatar Florian Heylorcid logoFotis E. Psomopoulos avatar Fotis E. Psomopoulosorcid logoPavankumar Videm avatar Pavankumar Videmorcid logoMaria Doyle avatar Maria Doyleorcid logoGraeme Tyson avatar Graeme TysonDaniel Maticzka avatar Daniel Maticzkaorcid logoArmin Dadras avatar Armin DadrasSimon Bray avatar Simon BrayAnna Trigos avatar Anna Trigosorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-SolanoMateusz Kuzak avatar Mateusz Kuzakorcid logoHans-Rudolf Hotz avatar Hans-Rudolf HotzJames Taylor avatar James TaylorCharity Law avatar Charity Laworcid logoBérénice Batut avatar Bérénice BatutXi Liu avatar Xi Liuorcid logoHelena Rasche avatar Helena Rascheorcid logoAnne Fouilloux avatar Anne Fouillouxorcid logoAmirhossein Naghsh Nilchi avatar Amirhossein Naghsh Nilchiorcid logoClemens Blank avatar Clemens Blankorcid logoSofoklis Keisaris avatar Sofoklis KeisarisNiall Beard avatar Niall Beardorcid logoIacopo Cristoferi avatar Iacopo Cristoferiorcid logoSaskia Hiltemann avatar Saskia Hiltemannorcid logoLinelle Abueg avatar Linelle AbuegPeter-Bram 't Hoen avatar Peter-Bram 't HoenAnton Nekrutenko avatar Anton NekrutenkoHarriet Dashnow avatar Harriet DashnowAndrea Bagnacani avatar Andrea Bagnacaniorcid logoTristan Reynolds avatar Tristan Reynoldsorcid logoJulia Jakiela avatar Julia Jakielaorcid logoDiana Chiang Jurado avatar Diana Chiang Juradoorcid logoAnthony Bretaudeau avatar Anthony BretaudeauGildas Le Corguillé avatar Gildas Le CorguilléOlivier Dameron avatar Olivier DameronIGC Bioinformatics Unit avatar IGC Bioinformatics UnitShian Su avatar Shian Suorcid logoMateo Boudet avatar Mateo BoudetAnne Siegel avatar Anne SiegelEkaterina Polkh avatar Ekaterina Polkhorcid logoPeter van Heusden avatar Peter van Heusdenorcid logoAnika Erxleben avatar Anika Erxlebenorcid logoMorgan Howells avatar Morgan Howellsorcid logoMo Heydarian avatar Mo Heydarianorcid logoMyrthe van Baardwijk avatar Myrthe van BaardwijkMarkus Wolfien avatar Markus Wolfienorcid logoMira Kuntz avatar Mira KuntzMehmet Tekman avatar Mehmet TekmanBelinda Phipson avatar Belinda Phipsonorcid logoBjörn Grüning avatar Björn Grüningorcid logoNicola Soranzo avatar Nicola Soranzoorcid logoCristóbal Gallardo avatar Cristóbal Gallardoorcid logoMarisa Loach avatar Marisa LoachPablo Moreno avatar Pablo MorenoThorben Stehling avatar Thorben Stehlingorcid logoToby Hodges avatar Toby HodgesCarlos Chee Mendonça avatar Carlos Chee Mendonçaorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoWendi Bacon avatar Wendi BaconXavier Garnier avatar Xavier Garnierorcid logoMarius van den Beek avatar Marius van den BeekMatt Ritchie avatar Matt RitchieChao Zhang avatar Chao Zhangorcid logoErwan Corre avatar Erwan CorreCharlotte Adang avatar Charlotte AdangJosé Manuel Domínguez avatar José Manuel Domínguezorcid logoMartin Čech avatar Martin Čechorcid logoMallory Freeberg avatar Mallory FreebergWilliam Durand avatar William DurandSanjay Kumar Srikakulam avatar Sanjay Kumar Srikakulamorcid logoLucille Delisle avatar Lucille Delisleorcid logoMatthias Bernt avatar Matthias Berntorcid logoTeresa Müller avatar Teresa MüllerJovana Maksimovic avatar Jovana Maksimovic

Funding

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

Logo
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.
Logo
de.NBI
Logo
Australian BioCommons
Logo
Melbourne Bioinformatics
Logo
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)
Logo
The University of Melbourne
Logo
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.