Interfacing Seurat with the R tidy universe
Bioinformatics, 2021•academic.oup.com
Motivation Seurat is one of the most popular software suites for the analysis of single-cell
RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a
large set of data display, query, manipulation, integration and visualization utilities, a great
opportunity exists to interface the Seurat object with the tidyverse. This interface gives the
large data science community of tidyverse users the possibility to operate with familiar
grammar. Results To provide Seurat with a tidyverse-oriented interface without …
RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a
large set of data display, query, manipulation, integration and visualization utilities, a great
opportunity exists to interface the Seurat object with the tidyverse. This interface gives the
large data science community of tidyverse users the possibility to operate with familiar
grammar. Results To provide Seurat with a tidyverse-oriented interface without …
Motivation
Seurat is one of the most popular software suites for the analysis of single-cell RNA sequencing data. Considering the popularity of the tidyverse ecosystem, which offers a large set of data display, query, manipulation, integration and visualization utilities, a great opportunity exists to interface the Seurat object with the tidyverse. This interface gives the large data science community of tidyverse users the possibility to operate with familiar grammar.
Results
To provide Seurat with a tidyverse-oriented interface without compromising efficiency, we developed tidyseurat, a lightweight adapter to the tidyverse. Tidyseurat displays cell information as a tibble abstraction, allowing intuitively interfacing Seurat with dplyr, tidyr, ggplot2 and plotly packages powering efficient data manipulation, integration and visualization. Iterative analyses on data subsets are enabled by interfacing with the popular nest-map framework.
Availability and implementation
The software is freely available at cran.r-project.org/web/packages/tidyseurat and github.com/stemangiola/tidyseurat.
Supplementary information
Supplementary data are available at Bioinformatics online.
Oxford University Press