> For the complete documentation index, see [llms.txt](https://lu-lab.gitbook.io/training/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://lu-lab.gitbook.io/training/part-i-basic-skills/introduction-of-part-i.md).

# Introduction of PART I

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**写在前面的话**

今天，数据不是太少而是太大，信息不是匮乏而是繁杂，现代人的重要的能力是“挖掘”和“鉴别”。对生物信息学的工作而言，最重要的、最有用的基本工具和技能一直是，我相信也会始终是：

1. google
2. wikipedia

## **Aim**

**These basic data skills give you freedom.**

> * Running bioinformatics software isn’t all that difficult, doesn’t take much skill, and it doesn’t embody any of the significant challenges of bioinformatics.…**These data skills give you freedom**…
> * I believe these two qualities — **reproducibility** and **robustness.**
> * So what is a reproducible bioinformatics project? At the very least, it’s **sharing your project’s code and data**.  
> * In wet lab biology, when experiments fail, it can be very apparent, but this is not always true in computing. Electrophoresis gels that look like Rorschach blots rather than tidy bands clearly indicate something went wrong. Unfortunately, **without prior expectations**, it can be quite difficult to distinguish good results from bad results.
> * The easy way to ensure everything is working properly is to **adopt a cautious attitude** , and **check everything between computational steps**.
> * You will **almost certainly have to rerun an analysis more than once**.
> * **Write Code for Humans, Write Data for Computers**
> * **Use Existing Libraries Whenever Possible**
> * **Treat Data as Read-Only**
> * **Document Everything** (-- Too geeky?) Just as a well-organized laboratory makes a scientist’s life easier, a well-organized and well-documented project makes a bioinformatician’s life easier.
>
> \-- <\<Bioinformatics Data Skills>>

## Step 1

### 学习内容：

1. **Setup** - How to do  jobs efficiently and reproducibly&#x20;
2. **Linux** - How to work with command lines

### 预习内容：

1. 练习一个Editor (e.g. VIM，Atom) &#x20;
2. 阅读《鸟哥的Linux私房菜-基础学习篇》如下章节

> 第5章\
> 5.3.1 man page
>
> 第6章
>
> ```
>  6.1用户与用户组
>
>  6.2  LINUX文件权限概念
>
>  6.3  LINUX目录配置
> ```
>
> 第7章Linux文件与目录管理
>
> ```
> 7.1目录与路径
>
> 7.2文件与目录管理
>
> 7.3文件内容查阅
>
> 7.5命令与文件的查询
>
> 7.6权限与命令间的关系
> ```
>
> 第8章
>
> ```
> 8.2文件系统的简单操作
> ```
>
> 第9章
>
> ```
> 9.1压缩文件的用途与技术
>
> 9.2 Linux系统常见的压缩命令
>
> 9.3打包命令：tar
> ```
>
> > 第10章vim程序编辑器 （*或者其他编辑器文档*）
>
> 第11章 认识与学习bash
>
> 第25章 LINUX备份策略
>
> ```
> 25.2.2完整备份的差异备份
>
> 25.3鸟哥的备份策略
>
> 25.4灾难恢复的考虑
>
> 25.5重点回顾
> ```

## Step 2

### 学习内容：

1. **Bash (and Github)** - How to set up multiple job as a pipeline
2. **R** - How to make professional and beautiful plots

### 预习内容：

1. 阅读和练习《鸟哥的Linux私房菜-基础学习篇》如下章节:

> 第11章 认识与学习bash\
> 第12章 正则表达式与文件格式化处理\
> 第13章 学习shell script

2.阅读和练习[Quick R](https://www.statmethods.net/) 如下章节 :

> Learning R\
> R Interface\
> Data Input\
> Statistics\
> `Descriptive Statistics`

## Step 3

### 学习内容：

1. **Perl/Python** - How to program for bioinformatics

### 预习内容：

1. 《Beginning Perl for Bioinformatics》
2. [Learning Python the Hard Way](https://www.gitbook.com/book/flyouting/learn-python-the-hard-way-cn/details) 中文版

### 相关书籍下载：

* 《[Bioinformatics Data Skills](https://www.jianguoyun.com/p/Dd9aSb4Q0NLuBRjJ9UY)》
* 《[鸟哥的Linux私房菜-基础学习篇](https://www.jianguoyun.com/p/Dd9aSb4Q0NLuBRjJ9UY)》
* 《Beginning Perl for Bioinformatics》
* [Learning Python the Hard Way](https://www.gitbook.com/book/flyouting/learn-python-the-hard-way-cn/details) 中文版
* [Quick R](https://www.statmethods.net/)

### [Quick Reference Cards](https://github.com/lulab/training/tree/master/assets/training_book/refcards)