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ondisc: large-scale computing on single-cell data

Single-cell datasets are growing in size, posing challenges as well as opportunities to biology researchers. ondisc (short for “on-disk single cell”) is an R package that enables users to easily and efficiently analyze large-scale single-cell data. ondisc makes computing on large-scale single-cell data FUN:

• Fast: ondisc is powered by several novel, highly efficient algorithms and data structures. All low-level code is written in C++ or C for maximum performance.
• Universal: ondisc runs on all platforms, from laptops to supercomputers. ondisc works seamlessly when the size of the data exceeds the amount of available memory.
• Ntuitive: ondisc leverages ideas from functional programming, making it simple for R users users to pick up and incorporate into their programs.

Take a look at the tutorials on the package website.

Installation

You can install the development version from GitHub with:

install.packages("devtools")
devtools::install_github("timothy-barry/ondisc")

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.