kmeans_haystack_raw

Function for k-means clustering of genes according to their distribution on a 2D plot.

One key exploratory analysis step in single-cell genomics data analysis
is the prediction of features with different activity levels. For example, we want
to predict differentially expressed genes (DEGs) in single-cell RNA-seq data,
spatial DEGs in spatial transcriptomics data, or differentially accessible
regions (DARs) in single-cell ATAC-seq data. 'singleCellHaystack' predicts differentially
active features in single cell omics datasets without relying on the clustering
of cells into arbitrary clusters. 'singleCellHaystack' uses Kullback-Leibler
divergence to find features (e.g., genes, genomic regions, etc) that are active
in subsets of cells that are non-randomly positioned inside an input space (such as
1D trajectories, 2D tissue sections, multi-dimensional embeddings, etc). For
the theoretical background of 'singleCellHaystack' we refer to our original paper
Vandenbon and Diez (Nature Communications, 2020) <doi:10.1038/s41467-020-17900-3>
and our update Vandenbon and Diez (Scientific Reports, 2023) <doi:10.1038/s41598-023-38965-2>.

Alexis Vandenbon

singleCellHaystack

A Universal Differential Expression Prediction Tool for
Single-Cell and Spatial Genomics Data

Diego Diez

kmeans_haystack_raw function

<dl><dt>x</dt>
<dd>x-axis coordinates of cells in a 2D representation (e.g. resulting from PCA or t-SNE)</dd>
<dt>y</dt>
<dd>y-axis coordinates of cells in a 2D representation</dd>
<dt>detection</dt>
<dd>A logical matrix showing which genes (rows) are detected in which cells (columns)</dd>
<dt>genes</dt>
<dd>A set of genes (of the 'detection' data) which will be clustered.</dd>
<dt>k</dt>
<dd>The number of clusters to return.</dd>
<dt>...</dt>
<dd>Additional parameters which will be passed on to the kmeans function.</dd></dl>

Arguments

Function for k-means clustering of genes according to their distribution on a 2D plot. — kmeans_haystack_raw

<dl>

<dt>x</dt>
<dd>x-axis coordinates of cells in a 2D representation (e.g. resulting from PCA or t-SNE)</dd>


<dt>y</dt>
<dd>y-axis coordinates of cells in a 2D representation</dd>


<dt>detection</dt>
<dd>A logical matrix showing which genes (rows) are detected in which cells (columns)</dd>


<dt>genes</dt>
<dd>A set of genes (of the 'detection' data) which will be clustered.</dd>


<dt>k</dt>
<dd>The number of clusters to return.</dd>


<dt>...</dt>
<dd>Additional parameters which will be passed on to the kmeans function.</dd>

</dl>

kmeans_haystack_raw: Function for k-means clustering of genes according to their distribution on a 2D plot.

Description

Usage

Value

Arguments