plot_fpc

Produces a ggplot with mean plus or minus two standard deviations of a selected FPC.

Methods and tools for deriving spatial summary functions from single-cell imaging
data and performing functional data analyses. Functions can be applied to other single-cell
technologies such as spatial transcriptomics. Functional regression and functional principal component analysis methods
are in the 'refund' package <https://cran.r-project.org/package=refund> while calculation of the
spatial summary functions are from the 'spatstat' package <https://spatstat.org/>.

Alex Soupir

mxfda

A Functional Data Analysis Package for Spatial Single Cell Data

Julia Wrobel

plot_fpc function

<dl><dt>obj</dt>
<dd>fpca object to be plotted.</dd>
<dt>pc_choice</dt>
<dd>FPC to be plotted.</dd></dl>

Arguments

Julia Wrobel <a href="/link/julia.wrobel%40emory.edu?package=mxfda&version=0.2.2-1" data-mini-rdoc="mxfda::julia.wrobel@emory.edu">julia.wrobel@emory.edu</a>

Author

Create plot of mean +/- scaled eigenfunctions from FPCA — plot_fpc

<dl>

<dt>obj</dt>
<dd>fpca object to be plotted.</dd>


<dt>pc_choice</dt>
<dd>FPC to be plotted.</dd>

</dl>

Julia Wrobel <a href='mailto:julia.wrobel@emory.edu'>julia.wrobel@emory.edu</a>

plot_fpc: Create plot of mean +/- scaled eigenfunctions from FPCA

Description

Usage

Value

Arguments

Author

Details