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<!-- PROJECT LOGO --> <br /> <p align="center"> <h3 align="center">SignacX 2.2.4</h3> <p align="center"> Get the most out of your single cell data. <br /> <a href="https://mathewchamberlain.github.io/SignacX/"><strong>Explore the Website »</strong></a> <br /> <br /> <a href="https://htmlpreview.github.io/?https://github.com/mathewchamberlain/SignacX/master/vignettes/signac-Seurat_pbmcs.html">View Demo</a> · <a href="https://github.com/mathewchamberlain/SignacX/">View Code Base</a> · <a href="https://github.com/mathewchamberlain/SignacX/issues">Request Feature</a> </p> </p> <!-- ABOUT THE PROJECT -->

What is SignacX?

SignacX is software that classifies the cellular phenotype for each individual cell in single cell RNA-sequencing data using neural networks trained with sorted bulk gene expression data from the Human Primary Cell Atlas. To learn more, check out the pre-print, website and code base. You can install SignacX from CRAN by running:

install.packages("SignacX")
library(SignacX)
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Contact

Mathew Chamberlain - chamberlainphd@gmail.com

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SignacX version history

SignacX 2.2.4 (2021-07-20)

Enabled SignacX to classify datasets >300,000 cells -- fixed a memory allocation issue. First degree nearest KNN neighbors are now used for Shannon entropy calculation for datasets > 100,000 cells.

SignacX 2.2.3 (2021-07-16)

Fixed a typo in the help section for SignacX::MASC.

SignacX 2.2.2

Addressed issues in the GitHub repository: Labeling of individual cell states corresponding to broad cell types.

SignacX 2.2.1

Addressed issues in the GitHub repository: Integration with Seurat 4.0.0 clustering

SignacX 2.2.0 (2021-02-24)

First CRAN release.