| Type: | Package |
| Title: | Utility Functions for Single-Cell RNA Sequencing Data |
| Version: | 0.1.0 |
| Description: | Analysis of single-cell RNA sequencing data can be simple and clear with the right utility functions. This package collects such functions, aiming to fulfill the following criteria: code clarity over performance (i.e. plain R code instead of C code), most important analysis steps over completeness (analysis 'by hand', not automated integration etc.), emphasis on quantitative visualization (intensity-coded color scale, etc.). |
| License: | GPL-3 |
| Encoding: | UTF-8 |
| LazyData: | true |
| RoxygenNote: | 7.1.0 |
| Imports: | ggplot2, Matrix, scales, assertthat, dplyr, viridis, viridisLite, methods |
| Suggests: | testthat, tibble |
| NeedsCompilation: | no |
| Packaged: | 2020-06-23 10:03:01 UTC; felix |
| Author: | Felix Frauhammer [aut, cre], Simon Anders [ctb] (Simon Anders wrote the colVars_spm function.) |
| Maintainer: | Felix Frauhammer <felixwertek@gmail.com> |
| Repository: | CRAN |
| Date/Publication: | 2020-06-25 16:20:02 UTC |
Closed breaks for log scale
Description
Finds breaks that are powers of 2, and forces inclusion of upper and lower limits (displaying the closed interval). Including limits specifically is particularly useful for ggplot2's color/fill, as it emphasizes the meaning of maximal/minimal color intensities (see examples).
Usage
closed_breaks_log2(lims)
Arguments
lims |
Vector with lower and upper limits (in that order) of the data that you want breaks for. |
Details
The feat function uses closed_breaks_log2 to color by
gene expression,
where the maximal expression gives valuable
intuition for a gene's overall expression strength.
For x- or y-axis (scale_*_log10),
I still recommend breaks_log from the scales package.
Value
Numeric vector with breaks.
See Also
Examples
# closed breaks include maximum, breaks_log do not:
closed_breaks_log2(lims = c(.01, 977.1))
scales::breaks_log()(c(.01, 977.1))
Human-readable labels for closed breaks
Description
Complements the closed_breaks_log2 function.
Usage
closed_labels(x, min_is_zero = FALSE)
Arguments
x |
Vector of breaks for which to produce labels.
Typically, this is the output of |
min_is_zero |
Should the smallest break be displayed as zero (TRUE) or as the actual value (FALSE). Default: FALSE |
Details
This is a helper for the feat function.
feat replaces numeric zeros with the next-smallest expression value
to avoid taking the logarithm of zero. min_is_zero can be used to
display the lowest break of the color scale as zero in these cases.
Value
Character vector with labels, used by feat function.
See Also
label_scientific
label_number_auto
Examples
# human readable output:
closed_labels(c(.001111,.122, 0.5, 10, 100, 1800))
Variance computation for sparse matrices
Description
Compute variance for each column / each row of a dgCMatrix (from Matrix package).
Usage
colVars_spm(spm)
rowVars_spm(spm)
Arguments
spm |
A sparse matrix of class dgCMatrix from the Matrix package. |
Details
The only supported format currently is dgCMatrix. While the Matrix package has other formats, this one is used for scRNAseq raw count data. Function code written by Simon Anders.
Value
Vector with variances.
See Also
vignette("Intro2Matrix", package="Matrix")
CsparseMatrix-class
Examples
library(Matrix)
mat <- as(matrix(rpois(900,1), ncol=3), "dgCMatrix")
colVars_spm(mat)
Feature Plot
Description
Highlight gene expression data in a 2D-embedding (UMAP, tSNE, etc.).
Usage
feat(embedding, expression, legend_name = "Expression")
Arguments
embedding |
A matrix/data.frame/tibble/... with exactly two columns.
If colnames are missing, the axis will be named "Dim1" and "Dim2".
Other classes than matrix/data.frame/tibble are possible, as long as
|
expression |
Numeric vector with expression values of the gene of
interest. Order has to correspond to the row order in |
legend_name |
Text displayed above the legend. Most commonly the name of the displayed gene. |
Details
This function discourages customization on purpose, because it bundles geoms, themes and settings that I found important for visualizing gene expression in scRNAseq data:
coord_fixed, to avoid distortion of embeddings
geom_point with size=.4, to ameliorate overplotting
No background grid, because distances and axis units in embeddings do not carry meaning for most dimensionality reduction techniques.
Intensity-coded color scales (viridis) displayed with log2-transformation. Makes visualization independent of colorblindness and appropriate for gene expression data (which is usually Log Normal distributed).
Color scale breaks are displayed as 'closed interval', i.e.
max(expression)andmin(expression)are the most extreme breaks. Rounding makes them human-readable. This functionality is provided by closed_breaks_log2 and closed_labels.
If you insist on customizing, think of this function as a great starting point, you can simply
copy-paste the code after typing feat into your
console.
Value
A ggplot2 object storing a colored scatter plot.
See Also
ggplot,
closed_labels,
closed_breaks_log2
Examples
# expression goes from 0 to 22:
set.seed(100)
feat(matrix(rnorm(2000, c(.1, 3)), ncol=2), rpois(1000, c(.1, 11)))
# expression goes from 2 to 52:
set.seed(100)
feat(matrix(rnorm(2000, c(.1, 3)), ncol=2), rpois(1000, c(10, 31)))
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.
Description
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.
Usage
is_wholenumber(x, tol = .Machine$double.eps^0.5)
Arguments
x |
Number to test |
tol |
tolerance for testing |