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Hierarchical, iterative clustering for analysis of transcriptomics data in R

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scrattch.hicat: Hierarchical, Iterative Clustering for Analysis of Transcriptomics

A hicat

Master: Travis build status Coverage status

Dev: Travis build status Coverage status

Installation

scrattch.hicat has several dependencies, including two from BioConductor and one from Github:

source("https://bioconductor.org/biocLite.R")
biocLite("limma")

devtools::install_github("JinmiaoChenLab/Rphenograph")

Once these dependencies are installed, scrattch.hicat can be installed with:

devtools::install_github("AllenInstitute/scrattch.hicat")

Vignettes

An overview of the main functions in scrattch.hicat

Tutorials

An interactive walkthrough of the major steps in clustering for scrattch.hicat.

Roadmap

The next few updates to scrattch.hicat will be aimed at getting code testing in place for major clustering functions:
0.0.22: Current version; Tests in place for de.genes.R functions.
0.0.23: Tests in place for cluster.R functions.
0.1.0: Vignette re-integrated; Adding pkgdown page; Update to Master branch.

Previous updates: 0.0.21: Added TravisCI and covr integration.

The scrattch suite

scrattch.hicat is one component of the scrattch suite of packages for Single Cell RNA-seq Analysis for Transcriptomic Type CHaracterization from the Allen Institute.

License

The license for this package is available on Github at: https://github.com/AllenInstitute/scrattch.hicat/blob/master/LICENSE

Level of Support

We are planning on occasional updating this tool with no fixed schedule. Community involvement is encouraged through both issues and pull requests.

Contribution Agreement

If you contribute code to this repository through pull requests or other mechanisms, you are subject to the Allen Institute Contribution Agreement, which is available in full at: https://github.com/AllenInstitute/scrattch.hicat/blob/master/CONTRIBUTION

Image attribution:

By Internet Archive Book Images [No restrictions], via Wikimedia Commons

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Hierarchical, iterative clustering for analysis of transcriptomics data in R

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