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MicrobiomeStatPlot-Microbiome data analysis and visualization

MicrobiomeStatPlot-微生物组数据分析与可视化

0.Introduction (项目简介)

The development of high-throughput sequencing has greatly promoted the development of the microbiome/metagenomics field. The data analysis and interpretation of the microbiome requires multidisciplinary knowledge such as microbiology, bioinformatics, statistics, Shell and R language, metagenomics, etc. There is still a lack of systematic learning materials both in China and around the world. The purpose of establishing the "Metagenome" Public WeChat Account is to break the barriers to the analysis and interpretation of microbiome data and promote the development of this field. At present, with three years of accumulation, hundreds of tutorials on data analysis, visualization and scientific research experience in this field have been published. However, this field is developing rapidly, many tutorials need to be updated, and the knowledge and research fields of team members are limited. A wider range of peers need to join in to create an introductory encyclopedia of metagenomics. Now we are comprehensively soliciting authors and reviewers of the chapter "Microbiome Data Analysis and Visualization Practice" from the global Chinese community.

高通量测序的发展极大地推动了微生物组/宏基因组领域的发展。微生物组的数据分析和解读需要微生物学、生物信息学、统计学、Shell和R语言、宏基因组学等多学科的知识，无论是中国还是世界范围内仍缺少系统的学习教材。宏基因组公众号成立的目的是打破微生物组数据分析解读的壁垒，推动本领域的发展。目前经常三年的积累，已发布数百篇本领域相关数据分析、可视化和科研经验的教程。但本领域发展迅速，很多教程需要更新，而且团队成员的知识和研究领域有限，需要更广泛的同行加入，打造宏基因组学入门百科全书，现向全球华人圈全面征集《微生物组数据分析与可视化实战》章节编写的创作者和审稿人。

You are the founder, join us now and contribute your wisdom!

创始人就是你，赶快加入贡献你的智慧吧！

Creator requirements (创作者要求)

  • Professional colleagues in this field, including but not limited to microbiology, bioinformatics, microbiome, or researchers who use culturomics, amplicon, metagenomics, macrotranscriptomics, macrovirome, macroproteomics, macrometabolomics, macroepigenetics and other technologies to study humans, animals, plants, and the environment (without restrictions on grade and title);
  • 本领域的专业同行，专业包括且不限于微生物学、生物信息学、微生物组学，或应用培养组学、扩增子、宏基因组、宏转录组、宏病毒组、宏蛋白组、宏代谢组、宏表观组等技术研究人类、动植物、环境的相关研究人员(年级和职称不限)；
  • Those who have the ability to collect and organize professional knowledge, and have experience in recording electronic notes and publishing articles are preferred;
  • 有专业知识搜集和整理的能力，有记录电子笔记、发表文章经历者的优先；
  • Claim the chapters in the directory below, follow the reference template (the first few sample chapters will be released within a week), use Youdao Cloud Notes markdown format or Rmarkdown (free training after joining) to write a logically rigorous, reader-friendly, and repeatable tutorial;
  • 认领下方目录中章节，按照参考模板(一周内陆续发布前几节样章)，采用有道云笔记markdown格式或Rmarkdown(加入后有免费培训)编写逻辑严谨、考虑读者感受、可重复性强的教程；
  • Carefully revise the reasonable suggestions made by the Metagenome Editorial Department;
  • 对宏基因组编辑部提出的合理意见进行认真修改；

Creator benefits（创作者福利）

  • The creator is one of the authors of the chapter;
  • 创作者作为章节的作者之一；
  • Get to know the core members of the metagenomics team, and trainee editors can get basic training in editing;
  • 结识宏基因组核心团队成员，见习编辑可获取编辑的基础培训；
  • Publish three articles or more than 10,000 words to become a formal editor, and get the latest amplicon and metagenomic analysis process worth 10,000 yuan for free, or participate in training and conferences.
  • 发布文章三篇或过万字，可成为正式编辑，免费获得价值万元的最新扩增子、宏基因组分析流程或参加培训、会议的机会；
  • Related tutorials and technical documents can be recommended for publishing SCI papers, see: "JoVE Microbiome Special Issue Call for Papers, Write Methods, Shoot Video Tutorials, and Publish SCI"
  • 相关教程、技术文档可推荐发表SCI论文，详见：《JoVE微生物组专刊征稿，写方法拍视频教程发SCI》
  • Based on your contribution, you will get the right to publish papers and books by your team;
  • 根据贡献，获得团队发表论文、出版图书的署名权；

Reviewer requirements（审稿人要求）

  • Professional reviewers, who are recommended to have experience in publishing articles, will comprehensively revise the logic and language of the chapters in their areas of expertise and make suggestions for improvement** (same as paper review);
  • 专业审稿人，建议有发表文章经历，对自己擅长领域章节的逻辑、语言的全面修改和提出改进建议(同论文审稿)；
  • Public reviewers, who can make comments or suggestions on areas for improvement in articles published by the public account**, can communicate by leaving a message below the article or contacting the public account administrator;
  • 大众审稿人，对公众号发布文章中可改进地方提出意见或建议，可通过文章下方留言、联系公众号管理员等方式沟通；

Reviewer benefits（审稿人福利）

  • Professional reviewers can join the editorial department and serve as responsible editors for reviewing articles, and obtain the right to sign their names and units in the responsible editor column;
  • 专业审稿人可进入编辑部，作为审核文章的责任编辑，获得责编栏姓名和单位的署名权；
  • The names and affiliations of public reviewers may appear in the chapter acknowledgments;
  • 大众审稿人的姓名和单位可出现在章节的致谢部分；
  • Holiday bonus for reviewers!
  • 审稿人节日福利红包！

Contact Metagenome WeChat Public Account (联系宏基因组公众号)

Creator and reviewer task registration: https://kdocs.cn/l/c7CGfv9Xc

创作者和审稿人任务登记： https://kdocs.cn/l/c7CGfv9Xc

Registration form for metagenome authors and reviewers.xlsx, use WeChat to log in to Kingsoft Document, register name, unit, research direction, title, specific division of labor in charge of chapters, etc. 宏基因组创作者和审稿人登记表.xlsx，使用微信登陆金山文档，登记姓名、单位、研究方向、职称、负责章节具体分工等信息

Contact: Defeng Bai / Yong-Xin Liu

联系人：白德凤 / 刘永鑫

WeChat (微信)：baidefeng1234win / meta-genomics

There are many advertising and marketing personnel. When adding WeChat, please be sure to indicate your name, unit, position, and research direction. Otherwise, your friend request will not be accepted.

广告营销人员较多，添加微信务必备注姓名-单位-职位-研究方向，否则无法通过好友申请

Email (邮箱)：[email protected] / [email protected]

At present, we have organized the catalog of basic knowledge, common analysis, and essential skills in this field. Some chapters have previously released resources and tutorials for reference. Authors who have chapters they are good at are welcome to claim the corresponding chapters for update or creation from scratch. If you think you have knowledge and methods that you are good at and important, please contact us to discuss the update of the catalog.

目前整理本领域基础知识、常用分析、必备技能的目录。部分章节有前期发布的资源和教程供参考。有自己擅长章节的作者，欢迎认领相应章节进行更新或从头创作。如果你觉得有自己擅长而且重要的知识和方法，欢迎联系我们一起讨论目录的更新。

The Chinese Encyclopedia of Metagenomics awaits your contribution!

中文的宏基因组学百科全书期待你的贡献！

Recommendations (推荐序)

We will find experts and scholars with many years of experience in this field, such as Academician Zhu Yongguan, President Lan Canhui, Researcher Zhao Fangqing, Researcher Wang Jun, Researcher Chu Haiyan, Professor Wei Zhong, etc. to comment on this book.

找在本领域积累多年的专家、学者，如朱永官院士、蓝灿辉总裁、赵方庆研究员、王军研究员、褚海燕研究员、韦中教授等对本书进行点评。

Editor's Preface（编者序）

What you can learn, an overview of technological developments in recent years and prospects.

你能学到什么、近年来技术发展概述和展望。

1.Bioinformatic and microbiome (生物信息与微生物组)

1.1 Overview of bioinformatics (生物信息概述)

1.1.1 Study design and metadata (实验设计和元数据)

1.1.2 Basic idea pf analysis (分析的基本思路)

1.2 Shell and Linux tutorials (Shell和Linux教程)

1.3 Statistics and plotting using R (R统计与绘图教程)

1.3.1 R language basics (R语言基础)

1.3.2 ggplot2 drawing basics (ggplot2绘图基础)

1.3.3 R language drawing album (R语言绘图专辑)

1.3.4 Advanced statistical graphics (高级统计绘图)

1.4 Python data processing and plotting (Python数据处理和绘图)

1.5 Microbiome overview (微生物组概述)

Development history: groping, initial exploration, establishing methods, and letting a hundred flowers bloom.

发展史：摸索，初步探索，建立方法，百花齐放。

Sequencing platform and data

测序平台和数据

Common research methods (常用研究手段)

1.5.1 Culturome (培养组)

1.5.2 Amplicon 16S (扩增子16S)

1.5.3 Metagenomics (宏基因组)

1.5.4 Other meta-omics (其他宏组学)

Fungal 18S/ITS (真菌组 18S/ITS)

Functional genes (功能基因)

Metabolome (代谢组)

Genome (基因组)

Transcriptome (转录组)

Sometimes the research also involves the study of gene expression of hosts and microorganisms. For more articles on transcriptomes and single cells, please follow the Bioinformatics Guide WeChat public account.

有时研究也会涉及宿主、微生物的基因表达研究。更多转录组、单细胞的文章可关注生信宝典公众号。

2.Microbiome analysis pipelines 微生物组分析流程 (原始数据到特征表)

Take stock of mainstream software. The advanced stage should be a free combination of various methods and steps, or even design and develop methods according to needs.

盘点主流软件。高级阶段应该是各种方法步骤的自由组合，甚至是根据需要设计、开发方法。

2.1 Culturome (培养组)

2.2 Amplicon (扩增子)

Format coversion (格式转换)

2.2.1 USEARCH/VSEARCH

2.2.2 QIIME 2

2.3 Metagenomics (宏基因组)

2.3.1 Read-based analysis (有参分析Read-based)

2.3.2 Assemble-based analysis (无参Assembly-based)

2.3.3 Functional annotation database (功能注释数据库)

2.3.4 Binning (分箱专题)

2.4 Feature table (认识特征表)

特征表是上游大数据分析的终点，是里程碑式的成果，同时也是下游分析的起始。

3.Visualization and interpretation (特征表的统计、可视化和解读)

3.1 Basic statistics (统计学基础)

3.1.1 Normality test and analysis of variance homogeneity (正态性检验和方差齐性分析)

3.1.2 Notes on using t-test, ANOVA, and chi-square test (t检验、方差分析、卡方检验使用注意事项)

3.1.3 Two-group and multiple-group rank sum test (两组和多组秩和检验)

3.1.4 P value correction for multiple comparisons (多重比较的P值校正)

3.1.5 Species data standardization methods and considerations (物种数据标准化方法和注意事项)

3.2 Alpha diversity (Alpha多样性)

3.2.1 Box plots and bar plots (箱线图或柱状图)

3.2.2 Rare curve (稀释曲线)

3.2.3 Venn (维恩图)

Variations of Venn diagrams, such as UpsetView, network diagrams, etc.

维恩图的变形，如UpsetView，网络图等。

3.3 Beta diversity (Beta多样性)

3.3.1 PCoA/NMDS (非限制性排序)

  1. PCA (主成分分析)
  2. PCoA (主坐标分析)
  3. NMDS (非度量多维尺度分析)
  4. CA (对应分析)
  5. pls-da，opls-da，t-sne (其他排序)

3.3.2 PERMANOVA (统计方法)

  1. PERMANOVA
  2. ANOSIM
  3. MRPP

3.3.3 Constrained sorting (限制性排序)

  1. Constrained PCoA (限制性主坐标分析)
  2. RDA (冗余分析)
  3. CCA (典范对应分析)
  1. LDA

3.4 Species composition (物种组成)

3.4.1 Stacked bar plot (堆叠柱状图)

3.4.2 Chord plot (弦图)

3.4.3 Tree plot/Bubble plot (树图/气泡图)

3.5 Differential analysis (差异比较)

3.5.1 t-test and rank-sum test (t检验和秩和检验)

3.5.2 Negative binomial distribution and count variance analysis (负二项分布和计数型差异分析) edgeR/DESeq2

  1. 什么是物种数据的过度离散现象和负二项分布
  2. 用edgeR包进行差异分析
  3. DESeq2包进行差异分析

3.5.3 STAMP and extended bar chart (STAMP与扩展柱状图)

3.5.4 LEfSe and Lcadogram (LEfSe和Cladogram)

3.5.5 Other commonly used difference analysis methods (其他常用差异分析方法)

  1. ANCOM分析
  2. ALDEx2分析
  3. songbird和DEICODE介绍
  4. limma

3.6 Network analysis (网络分析)

3.6.1 Network basics (网络基础知识)

3.6.2 Visualization introduction (可视化入门)

  1. Coloring networks by categories or modules (按分类或模块着色网络)
  2. Network properties (网络属性)
  3. Global properties (全局属性)
  4. Nodes properties (节点属性)

3.6.3 Advanced visualization (可视化进阶)

  1. Dual network comparison (双网络比对)
  2. Multi-network time series (多网络时间序列)
  3. Gephi beautification（Gephi美化）

3.7 Machine learning (机器学习)

3.7.1 Common algorithms for machine learning (机器学习的常用算法)

3.7.2 Random forest classification (随机森林分类)

黄适：这个RandomForest package 非常慢，已经完全不适应大数据分析需求。推荐使用ranger https://github.com/imbs-hl/ranger

  1. 分类
  2. 分类评估-ROC曲线及DCA分析

3.7.3 Random forest regression (随机森林回归)

  1. 回归
  2. 回归及效果评价

3.7.4 Adaboost/slime2

3.7.5 Deep learning (深度学习)

3.7.6 SourceTracker/FEAST (来源追溯)

3.7.7 Other commonly used algorithms (其他常用算法)

  1. Artificial neural network classification (人工神经网络分类)
  2. Support vector machine classification (支持向量机分类)
  3. Logistic regression (逻辑回归) (GLM)

3.8 Phylogenetic tree (树形)

3.8.1 Phylogenetic tree construction (进化树构建)

  1. Multiple sequence alignment (多序列比对)
  2. Fastree/RaxL (建树)
  3. Phylophlan3 (宏基因组中建树)
  4. iTOL (美化进化树)
  5. ggtree (美化进化树)

3.8.2 Classification tree construction (分类树构建)

  1. Graphlan and Cladogram (Graphlan与Cladogram)
  2. Krona
  3. Metacoder

3.9 Correlation analysis (相关分析)

3.9.1 Traits and environmental factors correlations (特征与环境因子相关)

3.9.2 Correlation between features (特征间相关(同网络))

3.9.3 Visualization of correlation analysis (相关分析的可视化)

4. Routine and ideas (文章套路总结)

4.1 Amplicon (扩增子)

4.2 Metagenome (宏基因组)

4.2.1 Reference genomes (参考基因集)

4.2.2 Carbohydrate (碳水化合物)

4.2.3 Antibiotic resistance (抗生素抗性)

4.3 Amplicon and metagenome (扩增子+宏基因组)

4.4 Other research hotspots (其他研究热点)

  • Human: enterotype, obesity, type 2 diabetes, IBD, preterm birth, association analysis (人类：肠型、肥胖、二型糖尿病、IBD、早产、关联分析)
  • Animal: Germ-free mice, bovine rumen, diet, host-microbe coevolution (动物：无菌小鼠、牛瘤胃、食性、宿主和微生物共进化)
  • Plant: rhizosphere, phyllosphere, metabolites, nitrogen utilization, disease resistance (植物：根际、叶际、代谢物、氮利用、抗病)
  • Environment: Antibiotic Resistance, Antibiotic Mining, Extreme Environments, Tree of Life (环境：抗生素耐药、抗生素挖掘、极端环境、生命之树)

5. Appendix (附录)

5.1 Study design (实验设计)

Experimental protocol, sample metadata collection, sample naming conventions and examples.

实验方案，样本元数据收集，样本名命名规则和示例。

5.2 Sequencing platform and technology (测序平台和测序技术)

5.3 Data backup and release (数据备份与发布)

NCBI，GSA，EBI

5.4 Image layout and beautification (图片排版和美化)

5.5 Journal comments (杂志点评)

CNS，Microbiome，ISME

Related articles by magazine (相关文章按杂志分类)

5.6 Paper writing, submission and literature compilation (论文写作、投稿和文献整理)

5.7 Opportunities and challenges (机遇与挑战)

Current advantages, disadvantages and shortcomings, and future development directions.

目前的优缺点和不足，未来的发展方向。

5.8 Next-generation sequencing (三代测序)

NBT's PacBio and ONT article introduction

NBT的PacBio和ONT文章简介

5.9 Experience and resource recommendations (经验和资源推荐)

Experience (经验)

Work efficiency (办工效率)

Books and monographs (书籍专著)

Foreign tutorial (国外教程)

5.10 Metagenomics featured articles (Special topic) (宏基因组精品文章) (专题)

Full text of the main references of this book

本书主要参考文献全文解读

Online database (网站数据库)

Software algorithms and pipelines (软件算法和流程)

Method evaluation (方法评测)

Culturome (培养组)

Enterotype (肠型)

Funds (基金)

Biography (人物传记)

Reference genomes (参考基因(组)集)

Viromics (病毒组)

5.11 You may also like (猜你喜欢)

Write at the back (写在后面)

To encourage readers to communicate and quickly solve scientific research difficulties, we have established a "Metagenomics" professional discussion group, which has more than 5,000 frontline researchers at home and abroad. To participate in the discussion and get professional answers, please share this article with your friends and scan the code to add the editor-in-chief to join the group. Be sure to note "name-unit-research direction-professional title/grade". To seek help with technical problems, first read "How to Ask Elegant Questions" to learn how to solve problems. If you still have not solved the problem, discuss it in the group. Don't chat privately about the problem. Help your peers.

为鼓励读者交流、快速解决科研困难，我们建立了“宏基因组”专业讨论群，目前己有国内外5000+ 一线科研人员加入。参与讨论，获得专业解答，欢迎分享此文至朋友圈，并扫码加主编好友带你入群，务必备注“姓名-单位-研究方向-职称/年级”。技术问题寻求帮助，首先阅读《如何优雅的提问》学习解决问题思路，仍末解决群内讨论，问题不私聊，帮助同行。

Learn about amplicon and metagenomic research ideas and analysis practices, and focus on "metagenomics"

学习扩增子、宏基因组科研思路和分析实战，关注“宏基因组”

Click to read the original text and jump to the latest article directory https://mp.weixin.qq.com/s/5jQspEvH5_4Xmart22gjMA

点击阅读原文，跳转最新文章目录阅读

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