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beachmat: A Bioconductor C++ API for accessing high-throughput biological data from a variety of R matrix types.
- Source :
-
PLoS Computational Biology . 5/3/2018, Vol. 14 Issue 5, p1-15. 15p. 1 Diagram, 4 Graphs. - Publication Year :
- 2018
-
Abstract
- Biological experiments involving genomics or other high-throughput assays typically yield a data matrix that can be explored and analyzed using the R programming language with packages from the Bioconductor project. Improvements in the throughput of these assays have resulted in an explosion of data even from routine experiments, which poses a challenge to the existing computational infrastructure for statistical data analysis. For example, single-cell RNA sequencing (scRNA-seq) experiments frequently generate large matrices containing expression values for each gene in each cell, requiring sparse or file-backed representations for memory-efficient manipulation in R. These alternative representations are not easily compatible with high-performance C++ code used for computationally intensive tasks in existing R/Bioconductor packages. 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 dense, sparse and file-backed matrices, amongst others. We evaluated the performance of beachmat for accessing data from each matrix representation using both simulated and real scRNA-seq data, and defined a clear memory/speed trade-off to motivate the choice of an appropriate representation. We also demonstrate how beachmat can be incorporated into the code of other packages to drive analyses of a very large scRNA-seq data set. [ABSTRACT FROM AUTHOR]
- Subjects :
- *RNA sequencing
*C++
*GENOMICS
*COMPUTATIONAL biology
Subjects
Details
- Language :
- English
- ISSN :
- 1553734X
- Volume :
- 14
- Issue :
- 5
- Database :
- Academic Search Index
- Journal :
- PLoS Computational Biology
- Publication Type :
- Academic Journal
- Accession number :
- 129415490
- Full Text :
- https://doi.org/10.1371/journal.pcbi.1006135