awesome-single-cell VS cellsnp-lite

Compare awesome-single-cell vs cellsnp-lite and see what are their differences.

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awesome-single-cell cellsnp-lite
3 1
2,927 118
- 3.4%
5.2 7.1
about 2 months ago about 1 month ago
C
MIT License Apache License 2.0
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.

cellsnp-lite

Posts with mentions or reviews of cellsnp-lite. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-20.
  • Genotype single cell data?
    2 projects | /r/bioinformatics | 20 Mar 2022
    Commenting in case anyone else needs a solution: cellSNP-lite took in the bam files and generated variant calls. Can be used with or without a list of SNPs for comparisons, RNA, ATAC, bulk or single cell!

What are some alternatives?

When comparing awesome-single-cell and cellsnp-lite you can also consider the following projects:

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

popscle - A suite of population scale analysis tools for single-cell genomics data including implementation of Demuxlet / Freemuxlet methods and auxilary tools

Baltica - Baltica: integrated differential junction usage

cellSNP - Pileup biallelic SNPs from single-cell and bulk RNA-seq data

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

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

DGE_workshop