lung_df

This data is adapted from the VectraPolarisData Bioconductor package. There are multiple ROIs for each patient.
Data was filtered to include only the cells in the tumor compartment.

datasets

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

lung_df function

<div class="section" id="lung-df">
<h3><code>lung_df</code></h3>
A data frame with 879,694 rows and 19 columns:<dl>
<dt>image_id</dt>
<dd>Image id for a given patient</dd><dt>patient_id</dt>
<dd>Unique patient id</dd><dt>age</dt>
<dd>Patient age at time of cancer diagnosis</dd><dt>survival_days</dt>
<dd>Survival time from diagnosis, in days</dd><dt>survival_status</dt>
<dd>Censoring variable, 1 = death, 0 = censor</dd><dt>x</dt>
<dd>Cell x position</dd><dt>y</dt>
<dd>Cell y position</dd>...</dl></div>

Format

Multiplex imaging data from a non-small cell lung cancer study. — lung_df

<div class='section' id='lung-df'>
<h3><code>lung_df</code></h3>


A data frame with 879,694 rows and 19 columns:<dl>
<dt>image_id</dt>
<dd>Image id for a given patient</dd>

<dt>patient_id</dt>
<dd>Unique patient id</dd>

<dt>age</dt>
<dd>Patient age at time of cancer diagnosis</dd>

<dt>survival_days</dt>
<dd>Survival time from diagnosis, in days</dd>

<dt>survival_status</dt>
<dd>Censoring variable, 1 = death, 0 = censor</dd>

<dt>x</dt>
<dd>Cell x position</dd>

<dt>y</dt>
<dd>Cell y position</dd>

...

</dl>

</div>

lung_df: Multiplex imaging data from a non-small cell lung cancer study.

Description

Usage

Arguments

Format

`lung_df`