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Good data organization is the foundation of any research project. It not only sets you up nicely for analysis, but it also makes it easier to come back to the project later and share it with collaborators, including your most crucial collaborator - future you.
Organizing a project that includes sequencing involves many components. There's the experimental setup and conditions metadata, measurements of experimental parameters, sequencing preparation, and sample information, the sequences themselves, and the files and workflow of any bioinformatics analysis. So much of the information of a sequencing project is digital, and we need to keep track of our digital records in the same way we have a lab notebook and sample freezer. This organization makes you a more effective bioinformatics researcher and prepares your data and project for publication, as grant agencies and publishers increasingly require this information. In this lesson, we'll go through the project organization and documentation that will make an efficient bioinformatics workflow possible.
In this lesson, we'll be using data from a study of experimental evolution using data from Cuatro Ciénegas Basin. In this study, there are several types of files:
- spreadsheet data from the experiment that tracks the microbiome and its phenotype over time
- spreadsheet data with information on the samples that were sequenced, the names of the samples, how they were prepared, and the sequencing conditions
- the sequence data
Throughout the analysis, we'll also generate files from the steps in the bioinformatics pipeline and documentation on the tools and parameters that we used.
In this lesson, you will learn the following:
- How to structure your metadata, tabular data, and information about the experiment.
- The metadata is the information about the experiment and the samples you're sequencing.
- How to prepare for, understand, organize, and store the sequencing data that comes back from the sequencing center.
- How to access and download publicly available data that may need to be used in your bioinformatics analysis.
This lesson assumes no prior experience with the tools covered in the workshop. However, learners are expected to have familiarity with some biological concepts, such as that each living organism has a genome and what can be obtained from DNA sequencing. Participants should bring their laptops and plan to participate actively.
This lesson is part of a workshop that uses data hosted on an Amazon Machine Instance (AMI). Workshop participants will be given information on how to log in to the AMI during the workshop. Learners using these materials for the self-directed study will need to set up their own AMI. Information on setting up an AMI and accessing the required data is provided on the Metagenomics Workshop Setup page. {: .prereq}
If you are teaching this lesson in a workshop, please see the Instructor notes. {: .prereq}
This lesson is the first one of the Metagenomics Workshop, comprised of four lessons.
This page and the three episodes in this lesson are adapted from the lesson Project Organization and Management for Genomics.
Please cite as:
Claudia Zirión Martínez; Diego Garfias Gallegos; Tania Vanessa Arellano Fernández; Aarón Espinosa Jaime; Edder D Bustos Díaz; José Abel Lovaco Flores; Luis Gerardo Tejero Gómez; J Abraham Avelar Rivas; Nelly Sélem (March , 2023) A Data Carpentry- Style Metagenomics Workshop