Abstract: A method for extracting somatic mutations from single-cell transcriptome sequencing data includes processing single-cell transcriptome raw sequencing data with a first comparison and identification method to obtain a plurality of first somatic mutation sites, processing the single-cell transcriptome raw sequencing data with a second comparison and identification method to obtain a plurality of second somatic mutation sites, integrating the plurality of first somatic mutation sites and the plurality of second somatic mutation sites to obtain a plurality of candidate somatic mutation sites, and performing mutation screening on the plurality of candidate somatic mutation sites to obtain final somatic mutation sites.

Abstract: Systems and methods for providing a neural network with multiple sparsity levels include sparsifying a matrix associated with the neural network to form a first sparse matrix; training the neural network using the first sparse matrix to form a second sparse matrix by fixing values and locations of non-zero elements of the first sparse matrix and updating a zero-value element of the first sparse matrix to be a non-zero value, wherein non-zero elements of the second sparse matrix includes the non-zero elements of the first sparse matrix; and outputting the second sparse matrix for executing the neural network.