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:

Charlotte Adang avatar Charlotte AdangMatt Ritchie avatar Matt Ritchieorcid logoHans-Rudolf Hotz avatar Hans-Rudolf Hotzorcid logoMorgan Howells avatar Morgan HowellsIGC Bioinformatics Unit avatar IGC Bioinformatics UnitChao Zhang avatar Chao ZhangAnne Siegel avatar Anne SiegelJames Taylor avatar James TaylorMateusz Kuzak avatar Mateusz KuzakXi Liu avatar Xi Liuorcid logoNicola Soranzo avatar Nicola SoranzoMarkus Wolfien avatar Markus WolfienBelinda Phipson avatar Belinda Phipsonorcid logoDiana Chiang Jurado avatar Diana Chiang JuradoPeter-Bram 't Hoen avatar Peter-Bram 't HoenShian Su avatar Shian Suorcid logoMatti Hoch avatar Matti Hochorcid logoLucille Delisle avatar Lucille Delisleorcid logoArmin Dadras avatar Armin Dadrasorcid logoHelena Rasche avatar Helena RascheNiall Beard avatar Niall BeardAndrea Bagnacani avatar Andrea BagnacaniCharity Law avatar Charity LawJosé Manuel Domínguez avatar José Manuel Domínguezorcid logoTeresa Müller avatar Teresa MüllerOlivier Dameron avatar Olivier Dameronorcid logoErwan Corre avatar Erwan Correorcid logoAnika Erxleben avatar Anika ErxlebenWilliam Durand avatar William Durandorcid logoMateo Boudet avatar Mateo BoudetSimon Bray avatar Simon Brayorcid logoGraeme Tyson avatar Graeme TysonAnton Nekrutenko avatar Anton Nekrutenkoorcid logoSofoklis Keisaris avatar Sofoklis Keisarisorcid logoAnne Fouilloux avatar Anne Fouillouxorcid logoAnthony Bretaudeau avatar Anthony BretaudeauXavier Garnier avatar Xavier Garnierorcid logoMaria Doyle avatar Maria DoyleDaniel Maticzka avatar Daniel Maticzkaorcid logoFlorian Heyl avatar Florian Heylorcid logoSaskia Hiltemann avatar Saskia HiltemannCarlos Chee Mendonça avatar Carlos Chee MendonçaJovana Maksimovic avatar Jovana Maksimovicorcid logoMo Heydarian avatar Mo HeydarianSanjay Kumar Srikakulam avatar Sanjay Kumar SrikakulamMarius van den Beek avatar Marius van den BeekPablo Moreno avatar Pablo Morenoorcid logoBjörn Grüning avatar Björn GrüningMehmet Tekman avatar Mehmet Tekmanorcid logoMartin Čech avatar Martin ČechAnna Trigos avatar Anna Trigosorcid logoClea Siguret avatar Clea SiguretHarriet Dashnow avatar Harriet Dashnoworcid logoJulia Jakiela avatar Julia Jakielaorcid logoMallory Freeberg avatar Mallory Freebergorcid logoIacopo Cristoferi avatar Iacopo Cristoferiorcid logoCristóbal Gallardo avatar Cristóbal Gallardoorcid logoWolfgang Maier avatar Wolfgang Maierorcid logoMarisa Loach avatar Marisa Loachorcid logoLinelle Abueg avatar Linelle Abuegorcid logoAmirhossein Naghsh Nilchi avatar Amirhossein Naghsh NilchiGildas Le Corguillé avatar Gildas Le Corguilléorcid logoFotis E. Psomopoulos avatar Fotis E. PsomopoulosMatthias Bernt avatar Matthias Berntorcid logoBérénice Batut avatar Bérénice Batutorcid logoMarek Ostaszewski avatar Marek Ostaszewskiorcid logoPeter van Heusden avatar Peter van Heusdenorcid logoWendi Bacon avatar Wendi BaconCasper de Visser avatar Casper de Visserorcid logoClemens Blank avatar Clemens BlankThorben Stehling avatar Thorben StehlingEkaterina Polkh avatar Ekaterina Polkhorcid logoBeatriz Serrano-Solano avatar Beatriz Serrano-Solanoorcid logoToby Hodges avatar Toby Hodgesorcid logoMyrthe van Baardwijk avatar Myrthe van Baardwijkorcid logoPavankumar Videm avatar Pavankumar Videmorcid logoMira Kuntz avatar Mira Kuntz

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
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.
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
de.NBI