chenwenchang/scMetric: Metric learning and visualization for single cell RNA-seq data

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 t-SNE to visualize the data using this metric. The package also outputs the t-SNE 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.

install.packages("remotes")
remotes::install_github("chenwenchang/scMetric")