knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)

Overview

infercna aims to provide functions for inferring CNA values from scRNA-seq data and related queries.

See Reference tab for a full list and documentation pages.

Installation

To install infercna:

# install.packages("devtools")
devtools::install_github("jlaffy/infercna")

References

The methodology behind infercna has been tried and tested in several high-impact publications. It was actually in the earliest of these papers (last listed) that the idea to infer CNAs from single-cell RNA-sequencing data was first formulated.

Data requirements

The bare minimum for use in infercna is:

If you would like to compute absolute (rather than relative) CNA values, you should additionally provide:

Finally, if your genome is not available in the current implementation of infercna, you should additionally provide:

Example data

infercna is built with two example datasets of scRNA-seq data from two patients with Glioblastoma, infercna::bt771 and infercna::mgh125, along with two normal reference groups, infercna::refCells. The matrices are stored as sparse matrices and you can use infercna::useData() to load them as normal matrices. These patients are taken from a much larger cohort of 28 Glioblastoma samples. You can look at the complete study here and can download the complete dataset via the Single Cell Portal.

Future implementations

Future implementations will include:



jlaffy/infercna documentation built on Jan. 26, 2024, 11:24 p.m.