PLoS Computational BiologyBioinformaticsPeer-reviewed journal article
beachmat: a Bioconductor C++ API for accessing single-cell genomics data from a variety of R matrix types
Abstract
Recent advances in single-cell RNA sequencing have dramatically increased the number of cells that can be profiled in a single experiment. This provides unparalleled resolution to study cellular heterogeneity within biological processes such as differentiation. However, the explosion of data that are generated from such experiments poses a challenge to the existing computational infrastructure for statistical data analysis. In particular, large matrices holding expression values for each gene in each cell require sparse or file-backed representations for manipulation with the popular R programming language. Here, we describe a C++ interface named beachmat, which enables agnostic data access from various matrix representations. This allows package developers to write efficient C++ code that is interoperable with simple, sparse and HDF5-backed matrices, amongst others. We perform simulations to examine the performance of beachmat on each matrix representation, and we demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large single-cell data set.
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- top 18%
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