专题介绍：单细胞RNA-seq被评为2018年重大科研进展，但实际上这是老技术。2015年，商品化单细胞RNA测序流程已经建立，成果发表在Cell上。今年井喷式发文章，关注点那么高，是因为最近这项技术全面商品化了。

Alexander Predeus (apredeus), Hugo Tavares (tavareshugo), Simon Murray (simondmurray), Vladimir Kiselev (wikiselev), Tallulah Andrews (talandrews), Jennifer Westoby (Jenni_Westoby), Davis McCarthy (davisjmcc), Maren Büttner (marenbuettner), Jimmy Lee (THJimmyLee), Krzysztof Polanski, Sebastian Y. Müller, Elo Madissoon, Stephane Ballereau, Maria Do Nascimento Lopes Primo, Rocio Martinez Nunez and Martin Hemberg (m_hemberg) 名字虽然不熟悉，但是肯定都是seraut团队的大牛啦

2021-08-06 时间是很新的，时效性杠杠滴，这一套如果要学习单细胞硬着头也要吃透。

1 About the course 关于课程

Today it is possible to obtain genome-wide transcriptome data from single cells using high-

如今利用高产的scRNA-seq测序技术，从单个细胞中获得基因组中的转录组数据已经成为可能。

throughput sequencing (scRNA-seq). The main advantage of scRNA-seq is that the cellular

…………………………………………………………………. 这种技术的主要好处是，细胞的高分辨率（？resolution）和

resolution and the genome wide scope makes it possible to address issues that are intractable

整个基因组的大范围使得技术参与带来相互化学反应的问题得以解决，而其它的测序方法，比如

using other methods, e.g. bulk RNA-seq or single-cell RT-qPCR. However, to analyze scRNA-seq

bulk RNA-seq和single-cell RT-qPCR ，就无法解决这样的问题。然而，要分析scRNA-seq处理后得

data, novel methods are required and some of the underlying assumptions for the methods

到的数据必须有新的方法，在bulk RNA-seq的实验中，一些传统假设中的老方法不再有效。

developed for bulk RNA-seq experiments are no longer valid.

……………………………………………………………………………………………………………………………………………………………………………

In this course we will discuss some of the questions that can be addressed using scRNA-seq as

在这个课程中我们会讨论一些用scRNA-seq可以解决的问题，以及一些可利用的计算机数据处理方

well as the available computational and statistical methods available. The course is taught through

法。…………………………………………………………………………………………………………………… 这个课程是在剑桥大学生信

the University of Cambridge Bioinformatics training unit, but the material found on these pages is

培训中心讲授的，但这些网页上的材料是为了给对scRNA-seq的计算机数据分析感兴趣的人学习的

meant to be used for anyone interested in learning about computational analysis of scRNA-seq

机会。

data. The course is taught twice per year and the material here is updated prior to each event.

…………这个课一年教两次，这里的材料比每次的课更新得更快。

The number of computational tools is increasing rapidly and we are doing our best to keep up to

计算机工具的数量正在急剧增加，我们也在尽力不落伍，紧跟发展趋势。

date with what is available. One of the main constraints for this course is that we would like to use

………………………………………………我们这个课程主要的局限性之一就是我们喜欢用一些R中的工具，它们运

tools that are implemented in R and that run reasonably fast. Moreover, we will also confess to

行得很快。………………………………………………………………………………………. 此外，我们也承认我们有些倾向于使

being somewhat biased towards methods that have been developed either by us or by our friends

用我们的同事、朋友等自己人开发的东西。

and colleagues.

总结一句话，bulk rna-seq那么多，单细胞测序很香。

1.1 Registration 注册

Please follow this link and register for the “Analysis of single cell RNA-seq data” course: http://training.csx.cam.ac.uk/bioinformatics/search 貌似国内还是要乖乖的看教程学习就行吧

点击链接注册课程

1.2 GitHub 代码仓库地址

https://github.com/hemberg-lab/scRNA.seq.course

1.3 Course Docker image 贴心的创作了docker镜像，保证工作重复性

The course can be reproduced without any package installation by running the course docker image which contains all the required packages.

这个课可以用docker，就不用安装那么多包了

1.3.1 Run the image 运行启动镜像

Make sure Docker is installed on your system. If not, please follow these instructions. To run the

需要确保你的系统里装了Docker，如果没装要遵循这些指示。还要更新。

course docker image (use the latest version of the course instead of v5.14):

docker run -p 8888:8888 -e PASSWORD="jupyter" quay.io/cellgeni/scrna-seq-course:v5.14 

Then follow the instructions provided, e.g.:

To access the notebook, open this file in a browser:
    file:///home/jovyan/.local/share/jupyter/runtime/nbserver-6-open.html
Or copy and paste one of these URLs:
    http://(a9ee1aad5398 or 127.0.0.1):8888/?token=22debff49d9aae3c50e6b0b5241b47eefb1b8f883fcb7e6d

A Jupyter session will be open in a web browser (we recommend Chrome).

1.3.1.1 Windows users windows用户

On Windows operating system the IP address of the container can be different

Windows操作系统的IP地址和……不同，要找到IP运行以下内容：

from 127.0.0.1 (localhost). To find the IP address please run:

docker-machine ip default

1.3.2 Download data/other files 下载其他文件

Please click on New -> Terminal. In the new terminal window please run:

./poststart.sh

If you want to download data files outside of Docker image you can still use the same poststart.sh script but you will need to install AWS CLI on your computer.

Alternatively, you can browse and download the files in you web-browser by visiting this link.

如果你想要在Docker镜像之外下载数据文件也行，不过你需要在电脑上装AWS CLI，点链接。

或者你可以浏览这个蓝色链接下载。

1.3.3 RStudio 不用多说，R用户必备

Now go back to Jupyter browser tab and change word tree in the url to rstudio. RStudio server will open with all of the course files, software and the data folder available.

要准备好RStudio

1.4 Manual installation 手动安装

If you are not using a docker image of the course, then to be able to run all code chunks of the course you need to clone or download the course GitHub repository and start an R session in the course_files folder. You will also need to install all required packages manually.

Alternatively, you can just install packages listed in a chapter of interest.

如果你没有用课程的docker镜像，你可以运行你所需要的课程里的所有一块块代码，或者在蓝字处下载，打开R的course_files文件夹手动下载你所需要的所有包。

1.5 License 许可保留，转载应该是不违规的，哈哈哈

All of the course material is licensed under GPL-3. Anyone is welcome to go through the material in order to learn about analysis of scRNA-seq data. If you plan to use the material for your own teaching, we would appreciate if you tell us about it in addition to providing a suitable citation.

所有的课程材料得到了GPL-3的认可，欢迎所有人来阅读这些材料，学习scRNA-seq数据分析的有关内容。如果你打算拿这些东西来当作你自己的教学资料，在合适地说明引用来源之后如果您能和我们说一声，我们将非常感激。

1.6 Prerequisites 要求，还是有门槛的要有linux和R基础

The course is intended for those who have basic familiarity with Unix and the R scripting language.

这个课程的受众群体要有一定的Unix和R语言基础

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.

我们也假定你会具有绘图能力、大量RNA-seq序列的分析能力以及会用一些常用的计算机工具。

We recommend attending the Introduction to RNA-seq and ChIP-seq data analysis or the Analysis of high-throughput sequencing data with Bioconductor before attending this course.

在参与这个课之前我们推荐一些这两个课程链接的学习。

1.7 Contact 联系，没试过，不知道大佬们有没有时间理我

If you have any comments, questions or suggestions about the material, please contact Alexander Predeus, Hugo Tavares, or Vladimir Kiselev. 如果有问题也可以加微信：cll7658加入我们的单细胞交流群，目标是500人呐，啧啧啧～～～～～～