awesome-single-cell VS awesome-nascent-rna-analysis

Compare awesome-single-cell vs awesome-nascent-rna-analysis and see what are their differences.

InfluxDB - Power Real-Time Data Analytics at Scale
Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
www.influxdata.com
featured
SaaSHub - Software Alternatives and Reviews
SaaSHub helps you find the best software and product alternatives
www.saashub.com
featured
awesome-single-cell awesome-nascent-rna-analysis
3 1
2,927 6
- -
5.2 2.6
about 2 months ago about 2 years 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-nascent-rna-analysis

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

What are some alternatives?

When comparing awesome-single-cell and awesome-nascent-rna-analysis you can also consider the following projects:

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

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

Baltica - Baltica: integrated differential junction usage

Awesome-Bioinformatics - A curated list of awesome Bioinformatics libraries and software.

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

DGE_workshop