We developed the package scMetric to apply ITML algorithm on gene expression data. The package let users to assign a few pairs of cells that are similar with each other and assign a few pairs of dissimilar cells. With this weak training information, scMetric learns the metric A to best preserve the similarity and dissimilarity reflected in the training pairs. It then employs tSNE to visualize the data using this metric. The package also outputs the tSNE map using the conventional Euclidean distance metric. The learned metric A as well as the key genes that compose most weights in the metric can also be output to other analysis methods that need a distance or similarity metric.
Package details 


Author  Wenchang Chen 
Maintainer  Wenchang Chen <chenwc17@mails.tsinghua.edu.cn> 
License  GPL3 
Version  1.0.1 
Package repository  View on GitHub 
Installation 
Install the latest version of this package by entering the following in R:

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