Code Monkey home page Code Monkey logo

excelerate-scrnaseq's Introduction

logo

Single cell RNA-seq data analysis with R

This international hands-on course covers several aspects of single cell RNA-seq data analysis, ranging from clustering and differential gene expression analysis to trajectories, cell type identification and spatial transcriptomics. The course is kindly sponsored by the ELIXIR EXCELERATE project.

Date

27.05.2019 - 29.05.2019

Location

The course is organised in the training room Dogmi at CSC. When you come to the main entrance, turn right to the reception and follow the signs to the course. The street address is Keilaranta 14, Espoo, Finland. You can reach us easily by public transport, please find more details here.

Course computing environment

The software and data required for the exercises have been installed on the classroom computers, and they are also available in CSC's cPouta cloud as a virtual machine image. Please read the instructions and how to install the environment on your own computer after the course with Conda.

Programme

Monday 27.5.2019

  • Introduction and experimental design (Åsa Björklund, Jules Gilet)
  • QC, data preprocessing (Åsa Björklund)
  • Normalisation and batch effect correction (Heli Pessa, Bishwa Ghimire)
  • Data integration (CCA, MNN, dataset alignment) (Ahmed Mahfouz)

Tuesday 28.5.2019

  • Dimensionality reduction (PCA, tSNE and UMAP) (Paulo Czarnewski)
  • Clustering (Ahmed Mahfouz)
  • Differential gene expression analysis (Ståle Nygård)

Wednesday 29.5.2019

  • Cell type identification (Philip Lijnzaad)
  • Trajectories/Pseudo-time (Paulo Czarnewski)
  • Spatial transcriptomics (Jeongbin Park and Lars Borm)

Prerequisities

In order to participate in this course you should have prior experience in using R.

Learning objectives

After this course you will be able to:

  • use a range of bioinformatics tools to analyze single cell RNA-seq data
  • discuss a variety of aspects of single cell RNA-seq data analysis
  • understand the advantages and limitations of single cell RNA-seq data analysis

Lecturers

  • Åsa Björklund (NBIS, ELIXIR-SE, Sweden)
  • Paulo Czarnewski (NBIS, ELIXIR-SE, Sweden)
  • Ahmed Mahfouz (LUMC, Netherlands)
  • Ståle Nygård (UIO, Norway)
  • Jeongbin Park (Charité-Universitätsmedizin Berlin & de.NBI, Germany)
  • Lars Borm (Karolinska Institutet, Sweden)
  • Jules Gilet (Institut Curie, France)
  • Heli Pessa (University of Helsinki, Finland)
  • Bishwa Ghimire (FIMM, Finland)
  • Philip Lijnzaad (Princess Maxima Center for Pediatric Oncology, Netherlands)

Additional information

excelerate-scrnaseq's People

Contributors

ahmedmahfouz avatar asabjorklund avatar benfeitas avatar ekorpela avatar hpessa avatar jonandernovella avatar juugii avatar olgadet avatar plijnzaad avatar staaln avatar

Watchers

 avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.