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scUtils

The goal of scUtils is to collect utility functions that make single-cell RNAseq data analysis simple and understandable for anyone. At the same time, I will use it when writing my PhD thesis.

Installation

You can install the released version of scUtils from CRAN with:

install.packages("scUtils")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("FelixTheStudent/scUtils")

Example: Single-Cell Feature Plot

Feature Plots highlight gene expression in a 2-dimensional embedding (computed e.g. with UMAP or tSNE).

library(scUtils)

# simulate some data
set.seed(100)
my_umap <- matrix(rnorm(2000, c(.1, 3)), ncol=2, dimnames = list(NULL, c("umap_1", "umap_2")))
my_expr <- rpois(1000, c(.1, 11))

feat(my_umap, my_expr)

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Version

Install

install.packages('scUtils')

Monthly Downloads

40

Version

0.1.0

License

GPL-3

Maintainer

Felix Frauhammer

Last Published

June 25th, 2020

Functions in scUtils (0.1.0)

closed_labels

Human-readable labels for closed breaks
closed_breaks_log2

Closed breaks for log scale
is_wholenumber

Check if number(s) is/are integers. In contrast to is.integer, is_wholenumber does not check the class but accepts all numbers that are integers with reasonable precision.
colVars_spm

Variance computation for sparse matrices
feat

Feature Plot