Tutorials
2  Update tidymass
3  Install docker version of tidymass
4  Build your own docker image based on tidymass
5  Create mass_dataset class from other tools
7  Convert raw data to mzXML/mgf
8  Raw data processing
9  Explore data
10  Data cleaning
11  Metabolite annotation
12  Statistical analysis
13  Pathway enrichment
14  Whole workflow using tidymass
15  Case study data
16  Case study for tidyMass
17  Repeat case study by docker
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0  Install tidymass
Brief introduction

Here, you can learn how to use tidyMass to do the data processing and analysis for the metabolomics data. It contains several parts.

packages

If you are new to R or the tidyverse

We recommend that you start by learning some basics about R and the tidyverse first, then return here when you feel ready. Here are some resources to start learning:

Part 1. Installation

You can learn how to install tidymass, and update it. You can also find here how to download the docker version of tidymass and build your own docker image based on tidymass.

Part 2. Demo data

You can find here how to download the demo data and create mass_dataset class by yourself.

Part 3. Data processing and analysis using tidymass

Here, you can learn how to use tidymass for data processing and analysis, from data converting to biological function mining.

workflow

Part 4. Case study

The code, data and docker image of case study in our manuscript are provided here.