Recommended Awesome Lists for Bioconductor Community: Oct 2022 Edition

This blog post consolidates web links to different Awesome Lists that may be useful to those just starting up in bioinformatics and those experienced in the field.

education
Author

Jeremy Selva

Published

October 22, 2022

Introdution

Initiated by Sindre Sorhus, an awesome list repository is a list of specific applications or resources that is curated by a domain/field specific community to be useful. They are a great place for those new to the domain to find out what tools others are using. Likewise a curated list of awesome lists can be found in this web page in alphabetical order. There is even a Twitter account giving updates to new awesome lists.

However, with more than 5000 public repository of awesome lists, it can be hard to navigate them to find lists that are relevant to the field of bioinformatics and computational biology. This post aims to lighten the work load by providing a manageable list grouped by specific fields of bioinformatics that is of interest to the Bioconductor Community.

Omics

Omics data is known to be heterogenous, available in numerous forms such as genome, proteome, transcriptome, and metabolome. Recently, imaging or spatial omics have recent joined into the omics family, making multi omics analysis far more challenging. Here we list up some awesome list from the different groups.

Genomics

There are many Bioconductor packages that made it in the awesome-single-cell list.

Proteomics

Bioconductor package PGA is mentioned in the awesome-proteomics list but the package is deprecated on version 3.12 of Bioconductor.

Lipidomics

Bioconductor packages found in the awesome-lipidomics lists are

Spatial Omics

Bioconductor packages that made it in crazyhottommy/awesome_spatial_omics lists are

Bioconductor packages that made it in drighelli/awesome-spatial-omics lists are

  • mistyR It is called MISTy in drighelli’s list.

Multi-omics

Bioconductor packages in the awesome-multi-omics lists are

Bioimaging

Bioimaging is useful in helping researcher understand biological processes in real time. Here are a list of useful resources with respect to their specific domain.

Microscopy

Only Bioconductor package EBImage is mentioned in the awesome-biological-image-analysis list.

Medical Images

No Bioconductor packages are found in this list

Cytodata

Only Bioconductor package EBImage is mentioned in the awesome-cytodata list.

Biological Visualisation

Visualisation of biological data can be complex. While there are many web based visualisation tools, they can be hard to find on the Internet. Thankfully, Mark Keller has consolidated them based on different fields of biological research from genomics, microscopy, to mass spectrometry.

Only Bioconductor package iSEE is mentioned in the awesome-biological-visualizations list.

Dynamic Reports

Jupyter and Quarto are few of the most popular tools used in creating dynamic reports that is compatible with several programming languages like R and Python. Here are some of the links to their awesome lists.

Jupyter

Quarto

Note

The Bioconductor Community Blog is mentioned.

Code Version Control

Version control systems (VCS) are software tools that help data analysts manage changes to their programming code over time. One of the most popular VCS tools in use today is Git. GitHub and GitLab are one of many cloud-based Git repository hosting services.

Git

GitHub

GitLab

Gitea

Note

Unfortunately, I could not find awesome list specific to Bitbucket and Gitee

Reproducible Research

Jeremy Leipzig have created a small encyclopedia of reproducible research resources from journals, data repositories, relevant organisations and other awesome lists like the Awesome Reproducible R and Awesome Docker .

Research Software

It can be daunting task to create a R package as there are many things to do like creating the package skeleton correctly, writing documentation and unit test etc. While there are many R packages created to make this process easily. It is nice to organise these R packages based on their specific roles and Indrajeet Patil has done just that.

In addition, it is also important for research software, no matter how useful it is to be deployed in the right registry so that the right group of people can find the software easily. In the case of R, we are blessed with many places to deploy an R package CRAN, Bioconductor, Neuroconductor, R-universe. Similar things are also done on other programming languages as well. The Netherlands eScience Center have created a list of relevant registries based on location, domain and programming language.

Developing R packages

Only Bioconductor package biocthis is mentioned in the awesome-r-pkgtools list.

Research Software Registry

Note

The Bioconductor repository is mentioned in the awesome-research-software-registries list.

Moving Foward

We hope that the information listed above are helpful. The creation of these awesome lists is made possible with the hard work of volunteers and the unconditional help from contributors. If there are any suggestions for improving or new information to add, do let the respective maintainers know.

Acknowlegments

This blog post is made possible from an online Biocondutor meetup for Hacktoberfest on 26 October 2022.

© 2024 Bioconductor. Content is published under Creative Commons CC-BY-4.0 License for the text and BSD 3-Clause License for any code. | R-Bloggers