written in front

QIIME is the most widely used analysis process in the microbiome field, with 58,000+ citations in the past 13 years. In 2019, Nature magazine rated it as 25 milestones in the study of human flora in the past 70 years—Milestone 16: Bioinformatics tools facilitate the sequencing of flora data points . In order to meet the current needs of big data and repeatable analysis, Professor Gregory Caporaso of Northern Arizona University developed QIIME 2 from scratch in 2016, and received the participation of 112 peers from 79 units around the world. In 2018, it took over QIIME , the article was officially published in the world's top journal Nature Biotechnology in August 2019 : QIIME 2 is a reproducible, interactive and scalable microbiome data analysis platform .

The metagenomics team joined the whole process of project testing, tutorial writing and article submission in June 2017, mainly responsible for the translation and dissemination of Chinese documents.

In September 2017, the comprehensive translation and testing of QIIME 2 2017.6 version 9 saving 50,000 words of user documentation was completed .
After it was published, it was welcomed by everyone, and it has been read more than ten thousand times in the official account, CSDN and official forum.
In January 2019, the comprehensive translation and testing of QIIME 2 2018.11 version 18 saving 100,000 words of user documentation was completed.
The article was officially published in Nature Biotechnology in August 2019, and the official account of Macrogenome will continue to update the latest 2019.7 Chinese user documentation and supporting video tutorials, with a total of 22 sections and more than 100,000 words. Help peers quickly get started with QIIME 2 and analyze big data easily .
From March to May 2020, the comprehensive translation and testing of QIIME 2 2020.2 version 32 saving 120,000 words of user documentation was completed.
In July 2023, QIIME 2 has been cited 9000+ times.
Recently, the latest QIIME 2 2023.5 version has been launched, and the Chinese tutorial will also be updated simultaneously.

QIIME 2 has added more functions, such as the addition of many new plug-ins such as vsearch, time series analysis, metagenomics and metabolomics. academic analysis platform.

The QIIME 2 article was published online on July 24, 2019, and was officially published in "Nature Biotechnology" on August 2. The Chinese version of the official user documentation for version 2023.5 is now fully updated, and will be published on the Macrogenome public account, official forum, Github , CSDN and Science Network are updated synchronously.

Advantages of QIIME 2

Easy to install:
In the past, the installation of QIIME has caused countless believers to compete. QIIME 2 uses the Conda package manager, which can be easily installed without administrator privileges;
At the same time, the Docker image, VirtualBox virtual machine, etc. are released and can be downloaded and run;
It can be used in various ways:
Supports command line mode (q2cli) and graphical user interface q2studio;
There is also an Artifact API (similar to IPython notebook) that Python users love;
You can also view and interactively explore data and result charts on the web page without installing software;
Analysis can be repeated:
The file system is newly defined, including the analysis data, as well as the analysis process and results. The results of each step can be traced back to the analysis process, which is convenient for inspection and repetition;
Visual enhancements:
QIIME is a latecomer, and the number of citations surpasses the mothur published a year earlier, which is its advantage in visualization. Now the visualization results are more diverse and beautiful, and the new interactive graphics system is adopted to facilitate data exploration;
Convenient cooperation:
Projects can rarely be completed by one person, and the result charts of many people and multiple places are convenient to share, which is suitable for the current needs of multi-person cooperation in scientific research;
Scalable:
QIIME 2 is no longer a software, but a platform that supports custom functions and customized analysis processes;
Experts can write their own plug-ins and join the process of QIIME2;
Community advantage:
At present, more than 100 authors have participated in this project. For those who want to enhance QIIME 2 with new functions, act quickly to contribute to QIIME 2!
Chinese tutorial support: Chinese tutorials will be updated on the Macrogenome official account, QIIME 2 official forum, CSDN and ScienceNet, and there will be video explanations, as well as QIIME 2 special WeChat group (scan code to add editor-in-chief friends at the end of the article, be sure to note "name- Unit-Research Direction-Position/Grade-QIIME2" to join the group ).

QIIME 2 User Documentation (Version: 2023.5)

https://docs.qiime2.org/2023.5/

Total text: 8575 words 1 picture 2 video

Estimated reading time: 20 minutes, video 21 + 27 minutes

Updated: July 21, 2023

Video: Introduction to QIIME 2 User Documentation 01.1

https://v.qq.com/x/page/r0910dnzmof.html

There are advertisements in the video, is the definition not high enough? Reply "qiime2" in the background to get 1080p video and test data download links .

getting started guide

Getting started

https://docs.qiime2.org/2023.5/getting-started/

Analysis of the microbiome (currently dominated by amplicon 16S) is a complex and mature field. Complexity means that there are so many analysis types, methods, and steps that beginners will feel oppressed, but as long as they are willing to spend a few days, they can still get started easily, and after several months of practice and practice, they will soon become an expert in the field. Compared with the 5-8 years of master's and doctoral careers in China, if the topic involves amplicon analysis, it is worth investing time in learning. It takes 2 weeks to study this tutorial systematically. If only a small part of your project involves amplicon analysis, you can study the upcoming concise tutorial, which can be completed in half a day with more than 6,000 words.

This guide will help you learn the necessary knowledge to understand, install and use QIIME 2, and implement the analysis of your own microbiome data.

Here is the order of learning:

Familiarize yourself with the core concepts of QIIME2;
Install QIIME2;
Follow the QIIME2 tutorial throughout to complete the microbiome analysis.
It is recommended to learn the tutorials of grand overview and moving pictures first, and then learn the tutorials of fecal microbiota transplantation (FMT study) and desert soil (Atacama Desert soils).
Finally, you can try different working interfaces. QIIME 2 runs a variety of user interfaces. Before, you used the command line model of q2cli.
See the interfaces documentation for different working interfaces.
For example, users who like to use a graphical interface can use QIIME2 Studio;
Users who prefer Python3 Jupyter Notebook can choose the Artifact API interface.

What is QIIME 2?

What is QIIME 2?

https://docs.qiime2.org/2023.5/about/

QIIME 2 is a powerful, scalable and decentralized microbiome analysis platform, emphasizing the transparency of data analysis. QIIME 2 enables researchers to start with raw DNA sequences and obtain publication-quality statistical and graphic results directly.

main feature:

Integrate the analysis process and automate the tracking of data sources
Semantic type system to automatically identify input file types
The plug-in system can expand the types of microbial analysis functions
Support multiple user interfaces, such as API, command line, graphical interface

QIIME 2 is a completely redesigned and rewritten microbiome analysis pipeline for QIIME 1. QIIME 2 retains the powerful and widely used advantages of QIIME 1, while improving many of its deficiencies.

QIIME 2 currently supports the complete microbiome analysis pipeline from start to finish. Usually QIIME 2 plugin functionality, new features are constantly available. You can find currently available plugins in the list of available plugins. Plugins that are in development are listed on the Future Available Plugins page.

Core idea

Core concepts

https://docs.qiime2.org/2023.5/concepts/

The amount of learning information for basic concepts is relatively large, and colleagues with basic knowledge can skip this chapter directly and proceed to the following software installation and subsequent data analysis. If you have questions or words that you don’t understand, please return to this chapter to clear the obstacles of new words and concepts.

To understand the analysis process of QIIME2 in depth, the core concepts defined by QIIME need to be understood.

Data files: QIIME 2 object/file format

Data files: QIIME 2 artifacts

Detailed note: In order to standardize the analysis process and make the analysis process repeatable, QIIME2 has formulated a unified analysis process file format; the qza file is similar to .qzaa closed file format (essentially a standard format compressed package), which includes raw data, The process and results of the analysis; this ensures the standard of the file format, and at the same time can trace the analysis of each step, as well as the drawing parameters of the chart. This approach provides the basis for reproducible analysis. For example, when submitting an article, the documentation of the analysis process is provided at the same time, which facilitates peer learning, repeated analysis of results, and reuse of results.

The data types generated by QIIME 2 are called QIIME 2 objects (artifacts), which usually include data and metadata/sample information (metadata). Metadata describes data, including its type, format, and how it was generated. A typical extension is .qza.

QIIME 2 uses objects instead of raw data files (such as fasta files), so analysts must import data to create QIIME 2 objects. Although a typical analysis starts with raw data imported into QIIME 2, you can import data as objects at any step of the analysis. QIIME 2 also has tools to export data from QIIME2 files, see the importing chapter for details.

Use QIIME2 objects instead of simple data to automatically track file types, formats and analysis processes. Using QIIME 2 files, researchers can focus on analysis without having to think about the various data types in the process.

The QIIME2 object can view the previous analysis process, the input data used at each step. This automated, integrated, and decentralized data traceability allows researchers to keep track of QIIME2, send it to collaborators, and know exactly what steps it took in its analysis. This makes the analysis process repeatable, learnable, and also produces text and diagrams used in the method. Traceability supports and encourages the generation of QIIME2 objects with appropriate attributes (such as FastTree for building phylogenetic trees).

NOTE: We have noted that the use of artifact(对象)the term can be confusing because of what biologists usually understand it to mean 实验偏差的来源. By this we artifactmean objects that have been processed in multiple steps, a bit like artifacts in archaeology. In our documentation and other tutorials, we need to be clear about the meaning of the QIIME2 artifacts (artifacts) described here.

Data Files: Visualization

Data files: visualizations

The chart result object or file type generated by QIIME2 .qzvis vrepresented by the extension and the end visual; it is qzasimilar to the file, including the analysis method and results, which is convenient for tracing how the chart is generated; the only difference from qza is that it is the end of the analysis. That is, the presentation of the results will not continue the analysis in the process. Visualized results include statistical result tables, interactive images, static pictures and other combined visual presentations. Such files can qiime tools viewbe viewed using the QIIME2 command.

Tip: Without installing the QIIME2 program, you can also import files online at https://view.qiime2.org/ and display the result charts, and at the same time view the data analysis process; this will facilitate sharing results with collaborators who do not use QIIME 2.

semantic type

Semantic types

The qza files generated in each step of QIIME2 analysis have corresponding semantic types for program recognition and analysis. For example, if the input expected by the analysis is a distance matrix, QIIME2 can determine which language type the file has a distance matrix in case an unreasonable input file is used for analysis (such as a QIIME2 object representing a phylogenetic tree).

Language semantics also help users avoid introducing unreasonable analysis processes. For example, a feature table includes presence and absence data (1 means the OTU was observed at least once, 0 means no). However, when it is used as input to compute a weighted UniFrac, it operates successfully, but the result is meaningless.

Only by understanding the results of each step of the analysis can we have a deeper and more comprehensive understanding of the analysis. Semantic Types page to view all supported semantic types

plug-in

Plugins

A specific function of the user in QIIME2 is a plug-in, which you can install and complete the analysis, such as a plug-in for splitting samples q2-demux, a plug-in for Alpha- or beta-diversity analysis q2-diversity, etc.

Plugins are software packages that anyone can develop. The QIIME 2 team has developed a complete microbiome analysis process, and third-party tools are also encouraged to provide additional analysis functions as plug-ins. The QIIME 2 community has established development instructions for standardized analysis plug-ins, and specific analyzes developed by other users according to their standards can be published in contact with the team and integrated into the analysis platform. This decentralized method allows the latest technologies and methods to be quickly deployed on the QIIME 2 platform, making it easy for QIIME 2 users to use. Plug-ins also allow users to select and customize the analysis process for a specific requirement.

Check the Available Plugins page to see currently available plugins. Check out the future plugins page to see what features are being developed.

Methods and Visualizers

Methods and visualizers

The methods and visualizer types defined by the QIIME 2 plugin to perform the analysis.

A method is a process that operates on an input object defined by QIIME2, including commands and parameters, and produces one or more outputs in a standard format. This result can be subsequently analyzed or visualized, producing intermediate or terminal outputs. For rarefyexample, the input file is q2-feature-tablethe feature table generated by the plug-in, and the output file is the feature table with consistent sample depth. It can be used as an input file for methods in alpha diversity analysis q2-diversity. Both input and output are qzafiles;

The visualization tool defines the standard input, including the combination of QIIME 2 objects and parameters, and generates statistical tables or visual graphics, which are convenient for users to interpret. The input is in the format and the output is. The file includes not only the results, but also the analysis qzacommands qzvand parameters for processing, which is convenient for repetition and check the accuracy of the analysis process. The visualized result file qzv is the end point of the analysis and cannot be further analyzed.

Install QIIME 2

Installing QIIME 2

https://docs.qiime2.org/2023.5/install/

There are many installation methods. Friends with Linux servers recommend using Conda installation. If there are still compatibility issues, you can try Docker installation to solve it. Friends who want to experience it on a windows laptop can use the Virtualbox virtual machine to install and learn. In other cases, choose one of the following methods according to your own environment.

Video: QIIME 2 User Documentation 01.2 Installation

The latest version of Station B: https://www.bilibili.com/video/BV1Aj41197iE/

https://v.qq.com/x/page/v0910kbk3o0.html

There are advertisements in the video, is the definition not high enough? Reply "qiime2" in the background to get 1080p video and test data download links .

Install QIIME 2 natively

Natively installing QIIME 2

https://docs.qiime2.org/2023.5/install/native/

The following tutorial will introduce how to install QIIME 2 Core 2023.5 distribution

Note: QIIME 2 cannot currently run in the Windows environment. We recommend using QIIME 2 virtual machines to run (Translator's Note: Virtual machines are less efficient and generally cannot run large data. It is only recommended to learn and develop small data within 100 samples. analysis experience).

The conda command provided by the Miniconda package manager installation (a Linux server is required, but administrator privileges are not required), can quickly install the QIIME 2 program and related plug-ins.

I tested using Miniconda3 to install QIIME 2 2019.7 on 18.04.3 LTS (64-bit). Of course, you can also use other Linux distributions such as CentOS 7, or macOS 64-bit.

Install Miniconda

Install Miniconda

Miniconda official website: https://conda.io/miniconda.html

If you have conda, please skip 安装Minicondathe paragraph. For more conda experience, please read

"Nature Method: Bioconda solves the troubles of biological software installation"

Download and install MiniConda3

# 下载最新版miniconda3
wget -c https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
# 运行安装程序
bash Miniconda3-latest-Linux-x86_64.sh
# 删除安装程序，下次你会下载新版
rm Miniconda3-latest-Linux-x86_64.sh

Follow the prompts during the installation process:

Please, press ENTER to continue, press the Enter key to view the license agreement, and then press the space bar to turn the page to complete the full text reading;
Do you accept the license terms? [yes|no], whether to agree to the license agreement, enter yesthe consent license;
It prompts that the default installation directory is the directory under your home directory ~/miniconda3. You can manually enter an installation directory you specify. It is recommended to press Enter to confirm the use of this directory;
Do you wish the installer to initialize Miniconda3 by running conda init? [yes|no], prompting whether to start the conda environment by default, enter here yesand press Enter.

Note: The installation is successful, and it prompts that if you want to close the self-starting conda base environment, you can use conda config --set auto_activate_base falseclose.

If you do not have permission to run the installation below, please run to export PATH="~/miniconda3/bin:$PATH"manually add the newly installed miniconda3 to the environment variable, or try to source ~/.bashrcupdate the environment variable

Note: At the end of the installation, you will be prompted whether to add it to your environment variable ~/.bashrc. I choose the general option no. Because you yescan directly add the conda environment to the highest priority of the environment variable, it is convenient to use, but the environment in conda, such as Python, becomes the default environment, destroying your previous software environment that relied on Python. Select no to ensure that the previous software installation environment remains unchanged, but when running conda and related programs, you need to run a command to temporarily add the ~/miniconda3/bindirectory to the environment variable, or use an absolute path to execute related programs.

If you want to use conda in the future, you need to run the following command to temporarily add environment variables to conda

export PATH="~/miniconda3/bin:$PATH"

But if it is a new environment, or you want to use QIIME 2 frequently, it is recommended to use the default environment variable to add more convenient . You agreed to add environment variables just now, close the current terminal after completion, and open a new terminal to continue the operation to take effect. If your system already has many programs, adding conda to the environment variable may cause the dependencies of the previous software to be destroyed.

(Optional) Add frequently used software download channels, as well as domestic mirrors to accelerate downloads.
Upgrade conda to the latest version: the new version has the fewest bugs, and the chance of encountering problems is also small.

# 添加常用下载频道
conda config --add channels defaults
conda config --add channels conda-forge
conda config --add channels bioconda

# 添加清华镜像加速下载
site=https://mirrors.tuna.tsinghua.edu.cn/anaconda
conda config --add channels ${site}/pkgs/free/ 
conda config --add channels ${site}/pkgs/main/
conda config --add channels ${site}/cloud/conda-forge/
conda config --add channels ${site}/pkgs/r/
conda config --add channels ${site}/cloud/bioconda/
conda config --add channels ${site}/cloud/msys2/
conda config --add channels ${site}/cloud/menpo/
conda config --add channels ${site}/cloud/pytorch/

# 升级conda及相关程序
conda update conda

# 安装下载工具
conda install -y wget

Note: When the software is installed, it will prompt whether to install, click yand press Enter to complete the installation. It can also be determined directly by adding the -y parameter like the above code, without prompting.
When installing conda, sometimes you need to wait for a long time in the steps of Collecting package metadata and Solving environment, such as a few minutes to tens of minutes. Please be patient. Generally, it will save more time than manually installing the software.

For the installation and use of Conda, see the tutorial below for details:

Nature Method: Bioconda solves the trouble of biological software installation

Install QIIME 2 in the conda environment

Install QIIME 2 within a conda environment

There are macOS and Linux (64-bit) two systems to choose from, here we take Linux (64-bit) as an example

mkdir -p 2023.5 && cd 2023.5
# 下载软件安装列表，官方源不容易下载
# wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-linux-conda.yml
# 只有6k，但数据来源于github，有时无法下载，可以从我的github或后台回复“qiime2”获取备份链接，
# 或访问 http://www.imeta.science/github/QIIME2ChineseManual/2023.5/qiime2-2023.5-py38-linux-conda.yml下载
wget -c http://www.imeta.science/github/QIIME2ChineseManual/2023.5/qiime2-2023.5-py38-linux-conda.yml
# 创建虚拟环境并安装qiime2，防止影响其它己安装软件
# 我用时13m，供参考，主要由网速决定
time conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-linux-conda.yml
# 删除软件列表
# rm qiime2-2023.5-py38-linux-conda.yml

Mac software list download, and alternate links, please refer to the official website for details

# 官方下载链接
wget https://data.qiime2.org/distro/core/qiime2-2023.5-py38-osx-conda.yml
# 备用下载链接
wget -c http://www.imeta.science/github/QIIME2ChineseManual/2023.5/qiime2-2023.5-py38-osx-conda.yml
# 安装qiime2 
conda env create -n qiime2-2023.5 --file qiime2-2023.5-py38-osx-conda.yml

From the yml software list file, we can know that QIIME 2 depends on as many as 336 software.

Download and install all dependencies. The time is mainly determined by the speed of the network. My first installation was interrupted for more than an hour. Retrying again is a task that can continue to be completed at the end, and it will succeed soon. If you add a domestic mirror, it can be done within half an hour. For details, the above conda configuration article will be done in 33m this time.

Install QIIME 2 locally

Installation package download link
https://pan.baidu.com/s/1Ikd_47HHODOqC3Rcx6eJ6Q?pwd=0315 Among them db/conda/qiime2-2023.5.tar.gz, it is placed in the temp folder of the C drive

mkdir -p 2023.5 && cd 2023.5
#新环境安装，将安装包存放于C盘（/mnt/c/temp/qiime2-2023.5.tar.gz)
mkdir -p ~/miniconda3/envs/qiime2-2023.5
tar -xzf /mnt/c/temp/qiime2-2023.5.tar.gz -C ~/miniconda3/envs/qiime2-2023.5
# 激活并初始化环境
conda activate qiime2-2023.5
conda unpack

Start of QIIME 2 environment

Activate the conda environment
Next, we enter the virtual environment.
If you can’t remember the name of the virtual environment you suggested, use the following command to check:

conda info --envs

It takes dozens of seconds to activate the working environment , the command is as follows:

conda activate qiime2-2023.5

Test whether the installation was successful

Test your installation

Check whether the installation is successful , and the pop-up program help is successful

qiime --help

QIIME 2 runs successfully, and the following help information is displayed:

Usage: qiime [OPTIONS] COMMAND [ARGS]...
  QIIME 2 command-line interface (q2cli)
Commands:
  info                Display information about current deployment.
  tools               Tools for working with QIIME 2 files.
  dev                 Utilities for developers and advanced users.

close working environment

conda deactivate

Close the environment when not using QIIME 2, otherwise your other programs may not be found or may run incorrectly

software upgrade

How do I update to the newest version of QIIME 2?

Although QIIME 2 is frequently updated, each version is independent and does not support upgrades. If a new version is available, you can follow the instructions to install it into another new conda environment without interfering with each other, but the environment names are different, distinguished by version numbers.
Remove old versions of QIIME 2

For example, I still have QIIME 2 2020.8 installed before

The way to delete is:

conda env remove -n qiime2-2020.8

You can instantly delete the environment you have installed for so long.

virtual machine installation

Installing QIIME 2 using Virtual Machines

https://docs.qiime2.org/2023.5/install/virtual/

There are three optional methods for virtual machine installation, namely VirtualBox, Amazon Cloud Services, and Docker. At present, only the conda method mentioned above is recommended for installation, which can meet the needs of most users. If there is still a lot of demand for virtual machine installation, if there are more than 10 messages, we will consider updating the detailed Chinese tutorial for virtual machine installation. The following is a concise tutorial for reference, and refer to the original text for details.

Install using VirtualBox (not recommended)

https://docs.qiime2.org/2023.5/install/virtual/virtualbox/

This step requires at least ~25 GB hard disk space

Virutalbox is a powerful virtual machine that can run on Windows / Linux / Mac platforms, and load the prepared system image to run. Suitable for desktops and notebooks with high Windows configuration to learn QIIME 2.

Main steps (take Win operating system as an example):

First download the virtual machine, the URL is:
https://www.virtualbox.org。
It must be noted that the version of the virtual machine needs to match the version of the QIIME 2 image, otherwise it cannot be used.
The following address can check the matching of the two:
https://s3-us-west-2.amazonaws.com/qiime2-data/distro/core/virtualbox-images.txt
Download the QIIME 2 image, the latest version download address is:
https://data.qiime2.org/distro/core/2022.5, 5.8GB in size.
Note that this version needs to be used with the virtual machine version 6.1.34. The download address of this version of the virtual machine is:
https://download.virtualbox.org/virtualbox/6.1.46/VirtualBox-6.1.46-158378-Win.exe
Unzip the downloaded QIIME2 image compression package;
Double-click the image file in the compressed package QIIME 2 Core - X.Y.Z (build_number).ovf, and follow the prompts to import the image.
Start the virtual machine and enter the QIIME 2 working environment based on the Ubuntu system;
Install in the menu Guest Additions, get the function of loading directory, and set the shared directory for reading external data.

For detailed graphic tutorials, see the official website. For the Chinese Virutal box tutorial, please refer to "Amplifier Analysis QIIME. 1 Virtual Machine Installation and Configuration and Mounting External Directories"

Install using Docker

Installing QIIME 2 using Docker

Generally, only when conda cannot be installed or cannot be used after installation, try this installation method to improve the success rate of operation.

Install Docker, see https://www.docker.com for details, Linux may need to install and set user groups with administrator privileges

Take Ubuntu system installation as an example (installed, please skip)

sudo apt install docker.io

Add a user to the docker group, please run it under administrator privileges, and modify it to your own user name

USER=yourname
sudo usermod -aG docker ${USER}

I prefer to use docker, directly download the pre-configured system and use it, without affecting the local system

For the basic operation of Docker, please refer to the tutorial "Amplifier Analysis Process 2. Using Docker to Run QIIME" and "Basic Use of Docker-Ubuntu 18.04" in the official account of Macrogenome

Download the QIIME 2 mirror

It is necessary to download 3Gb of image data. It usually takes 1 hour to download during working hours, and there is no speed limit during off-duty hours. It can be done in 7 minutes. The speed of the Docker server is still quite good (this version of docker has not yet been updated during the test).

time docker pull qiime2/core:2023.5 # real    7m16.499s

Determine if the installation was successful

run QIIME2 docker

docker run -t -i -v $(pwd):/data qiime2/core:2023.5 qiime
# 启动docker命令行，挂载当前目录至虚拟机中/data目录，运行qiime测试

# 方法2. 进入镜像分析数据
docker run --rm -v $(pwd):/data --name=qiime -it  qiime2/core:2023.5
# 这就相当于打开了一个软件工作环境，目录/data为当前工作目录，可方便分析数据
# 可以按Ctrl+D退出当前虚拟机的环境，详见上面docker的使用教程

Install using Windows Subsystem for Linux (recommended)

This method is recommended for Windows 10 users. It is easy to install and has high efficiency. See below for details.

Windows 10 installs the Linux subsystem Ubuntu 20.04LTS, easy to use bio-information software, and kills virtual machines efficiently

suggestion

Recommendations

A native conda install is generally recommended, but this isn't always available, nor is it an easy-to-use option in all cases. Generally, we recommend the following:

macOS users
- A local conda install usually works well
- Docker and VirtualBox are great backup options
Windows users
- On newer versions of Windows, it's usually fine to do a native conda install in the Windows Subsystem for Linux.
- See the WSL guide for instructions on how to set up the Windows Subsystem for Linux .
- Docker and VirtualBox are great backup options
Linux users
- A local conda install usually works well
- Docker and VirtualBox are great backup options

QIIME 2 2023.5 version core plugin

QIIME 2 Core 2025.5 distribution

https://docs.qiime2.org/2023.5/install/#qiime-2-core-2023-5-distribution

The default installation q2cliof QIIME 2 2023.5 includes the command line analysis working environment and the following plug-ins, with a total of 22 main functional modules:

q2-alignment # generate and manipulate multiple sequence alignments
q2-composition # for species data analysis
q2-cutadapt # remove adapter sequences, primers and other unwanted sequences from sequence data
q2-dada2 # sequence quality control
q2-deblur # sequence quality control
q2-demux # Split pool sequencing samples and view sequence quality
q2-diversity # Explore community diversity
q2-diversity-lib #Diversity analysis plug-in, newly added in August 2020
q2-emperor # beta diversity 3D visualization
q2-feature-classifier # species annotation
q2-feature-table # Operate the feature table by condition
q2-fragment-insertion # Phylogenetic tree expansion to determine accurate evolutionary status
q2-gneiss # Build a combined model
q2-longitudinal # paired samples and time series analysis
q2-metadata # processing metadata
q2-phylogeny # generate and manipulate phylogeny trees
q2-quality-control # for feature and sequence data quality control
q2-quality-filter # PHRED-based filtering and pruning
q2-sample-classifier # machine learning prediction of sample metadata
q2-taxa # processing feature species taxonomy annotations
q2-types # Define the types of microbiome analysis
q2-vsearch # clustering and de-redundancy

qiime --helpSee the pop-up information above for the function of the plug-in

Note: The QIIME 2 Core 2023.5 release includes plugins and interfaces developed, maintained, tested and published by the QIIME 2 development team. The core release is required to run the commands in the QIIME 2 tutorial. If you want to install other QIIME 2 plugins or interfaces, please refer to the relevant package documentation. In addition to Core, other types of distributions may be available in the future.

Translator profile

Liu Yongxin, researcher, doctoral supervisor. In 2014, he graduated from the University of Chinese Academy of Sciences, majoring in bioinformatics, and then worked in the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences as a postdoctor, engineer, and senior engineer. In October 2022, he joined the Shenzhen Institute of Agricultural Genomics, Chinese Academy of Agricultural Sciences as the research team leader . Research directions are metagenomic method development, function mining and science communication. Participated in the QIIME 2 project, led the development of EasyAmplicon, EasyMetagenome, Culturome analysis process, data analysis website (EVenn, ImageGP) and R package (amplicon, ggClusterNet), etc. It is to comprehensively build the methodological infrastructure in the field of metagenomics and promote the development of microbiomics. Published more than 20 papers in journals such as Nature Biotechnology, Nature Microbiology, and iMeta as the (co-) first or corresponding author. He has co-published more than 20 papers in journals such as Science, Cell Host & Microbe, and Microbiome, and has published more than 50 papers in total, which have been cited 13,000+ times. Editor-in-chief of the monograph "Microbiome Experiment Manual", with the participation of more than 300 colleagues, to jointly create a long-term updated Chinese encyclopedia in this field. Founded the Metagenome public account, followed by 150,000+ peers, shared more than 3,000 original articles, and accumulated more than 40 million readings, creating the most influential scientific communication platform in this field. Initiated the "iMeta" journal, united thousands of experts from all over the world to jointly create top journals in metagenomics, microbiome and bioinformatics, and solved the bottleneck problem of journal publishing in this field in my country. The research group has been recruiting postdoctoral fellows and guest graduate students for a long time. If you are interested, you can add WeChat yongxinliu to discuss in detail.

Wang Huiling, Hunan Agricultural University, undergraduate student in bioinformatics, graduated and practiced in Liu Yongxin's group. Responsible for updating and testing this version.

Reference

https://docs.qiime2.org/2023.5

Evan Bolyen, Jai Ram Rideout, Matthew R. Dillon, Nicholas A. Bokulich, Christian C. Abnet, Gabriel A. Al-Ghalith, Harriet Alexander, Eric J. Alm, Manimozhiyan Arumugam, Francesco Asnicar, Yang Bai, Jordan E. Bisanz, Kyle Bittinger, Asker Brejnrod, Colin J. Brislawn, C. Titus Brown, Benjamin J. Callahan, Andrés Mauricio Caraballo-Rodríguez, John Chase, Emily K. Cope, Ricardo Da Silva, Christian Diener, Pieter C. Dorrestein, Gavin M. Douglas, Daniel M. Durall, Claire Duvallet, Christian F. Edwardson, Madeleine Ernst, Mehrbod Estaki, Jennifer Fouquier, Julia M. Gauglitz, Sean M. Gibbons, Deanna L. Gibson, Antonio Gonzalez, Kestrel Gorlick, Jiarong Guo, Benjamin Hillmann, Susan Holmes, Hannes Holste, Curtis Huttenhower, Gavin A. Huttley, Stefan Janssen, Alan K. Jarmusch, Lingjing Jiang, Benjamin D. Kaehler, Kyo Bin Kang, Christopher R. Keefe, Paul Keim, Scott T. Kelley, Dan Knights, Irina Koester, Tomasz Kosciolek,Jorden Kreps, Morgan GI Langille, Joslynn Lee, Ruth Ley,Yong-Xin Liu, Erikka Loftfield, Catherine Lozupone, Massoud Maher, Clarisse Marotz, Bryan D. Martin, Daniel McDonald, Lauren J. McIver, Alexey V. Melnik, Jessica L. Metcalf, Sydney C. Morgan, Jamie T. Morton, Ahmad Turan Naimey, Jose A. Navas-Molina, Louis Felix Nothias, Stephanie B. Orchanian, Talima Pearson, Samuel L. Peoples, Daniel Petras, Mary Lai Preuss, Elmar Pruesse, Lasse Buur Rasmussen, Adam Rivers, Michael S. Robeson, Patrick Rosenthal, Nicola Segata, Michael Shaffer, Arron Shiffer, Rashmi Sinha, Se Jin Song, John R. Spear, Austin D. Swafford, Luke R. Thompson, Pedro J. Torres, Pauline Trinh, Anupriya Tripathi, Peter J. Turnbaugh, Sabah Ul-Hasan, Justin J. J. van der Hooft, Fernando Vargas, Yoshiki Vázquez-Baeza, Emily Vogtmann, Max von Hippel, William Walters, Yunhu Wan, Mingxun Wang, Jonathan Warren, Kyle C. Weber, Charles H. D. Williamson, Amy D. Willis, Zhenjiang Zech Xu, Jesse R. Zaneveld, Yilong Zhang, Qiyun Zhu, Rob Knight & J. Gregory Caporaso#. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nature Biotechnology. 2019, 37(8): 852-857. https://doi.org/10.1038/s41587-019-0209-9

written in the back

In order to encourage readers to communicate and quickly solve scientific research difficulties, we have established a "Metagenome" discussion group, with 6000+ researchers at home and abroad joining. Please add the editor-in-chief's WeChat meta-genomics to bring you into the group, and be sure to note "name-unit-research direction-title/grade". Please indicate your identity for senior professional titles, and there are also microbial PI groups at home and abroad for cooperation and exchange. To seek help for technical problems, first read "How to Ask Elegantly" to learn how to solve the problem. If the problem has not been resolved in the group discussion, do not chat privately with the problem, and help the peers.

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QIIME 2 Tutorial. 01 Introduction and Installation Introduction & Install (2023.5)