awesome-single-cell VS Awesome-Bioinformatics

Compare awesome-single-cell vs Awesome-Bioinformatics and see what are their differences.

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awesome-single-cell Awesome-Bioinformatics
3 5
2,927 2,912
- -
5.2 0.0
about 2 months ago about 1 month ago
MIT License -
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

awesome-single-cell

Posts with mentions or reviews of awesome-single-cell. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-08-21.

Awesome-Bioinformatics

Posts with mentions or reviews of Awesome-Bioinformatics. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-11-17.

What are some alternatives?

When comparing awesome-single-cell and Awesome-Bioinformatics you can also consider the following projects:

cellsnp-lite - Efficient genotyping bi-allelic SNPs on single cells

bioinformatics - :microscope: Path to a free self-taught education in Bioinformatics!

MultiQC - Aggregate results from bioinformatics analyses across many samples into a single report.

awesome-protein-design - A curated list of awesome protein design research, software and resources.

Baltica - Baltica: integrated differential junction usage

awesome-cheminformatics - A curated list of Cheminformatics libraries and software.

scDblFinder - Methods for detecting doublets in single-cell sequencing data

awesome-pipeline - A curated list of awesome pipeline toolkits inspired by Awesome Sysadmin

DGE_workshop

awesome-multi-omics - List of software packages for multi-omics analysis