Abstract
Here, we present an open source computational toolbox, scHiCTools, which provides three commonly used methods for smoothing scHi-C data (linear convolution, random walk, and network enhancing) and three projection methods for embedding single cells into a lower dimensional Euclidean space (fastHiCRep, Selfish, and InnerProduct). We benchmark the embedding performance and run time of these methods on a recent scHi-C datasets, and provide some suggestions for practice use.
Copyright
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