forked from hemberg-lab/scRNA.seq.course
-
Notifications
You must be signed in to change notification settings - Fork 0
/
index.Rmd
44 lines (29 loc) · 2.59 KB
/
index.Rmd
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
---
title: "Analysis of single cell RNA-seq data"
author: "Vladimir Kiselev, Tallulah Andrews, Davis McCarthy and Martin Hemberg"
date: "`r Sys.Date()`"
knit: "bookdown::render_book"
documentclass: book
bibliography: [book.bib]
biblio-style: apalike
link-citations: yes
always_allow_html: yes
---
# About the course
Recent technological advances have made it possible to obtain genome-wide transcriptome data from single cells using high-throughput sequencing (scRNA-seq). The main advantage of scRNA-seq is that the cellular resolution and the genome wide scope makes it possible to address issues that are intractable using other methods, e.g. bulk RNA-seq or single-cell RT-qPCR. However, to analyze scRNA-seq data, novel methods are required and some of the underlying assumptions for the methods developed for bulk RNA-seq experiments are no longer valid.
In this course we will be surveying the existing problems as well as the available computational and statistical frameworks available for the analysis of scRNA-seq. The course is taught through the University of Cambridge <a href="http://training.csx.cam.ac.uk/bioinformatics/" target="blank">Bioinformatics training unit</a>, but the material found on these pages is meant to be used for anyone interested in learning about computational analysis of scRNA-seq data.
## Video
<iframe width="560" height="315" src="https://www.youtube.com/embed/IrlNcJwPClQ?list=PLEyKDyF1qdObdFBc3JncwXAnMUHlcd0ap" frameborder="0" allowfullscreen></iframe>
## Registration
Please follow this link and register for the __"Analysis of single cell RNA-seq data"__ course:
<a href="http://training.csx.cam.ac.uk/bioinformatics/search" target="blank">http://training.csx.cam.ac.uk/bioinformatics/search</a>
## GitHub
<a href="https://github.com/hemberg-lab/scRNA.seq.course" target="blank">https://github.com/hemberg-lab/scRNA.seq.course</a>
## License
<b>GPL-3</b>
## Prerequisites
The course is intended for those who have basic familiarity with Unix and the R scripting language.
We will also assume that you are familiar with mapping and analysing bulk RNA-seq data as well as with the commonly available computational tools.
We recommend attending the [Introduction to RNA-seq and ChIP-seq data analysis](http://training.csx.cam.ac.uk/bioinformatics/search) or the [Analysis of high-throughput sequencing data with Bioconductor](http://training.csx.cam.ac.uk/bioinformatics/search) before attending this course.
## Contact
If you have any __comments__, __questions__ or __suggestions__ about the material, please contact <a href="mailto:[email protected]">Vladimir Kiselev</a>.