f_annot_ctgenes

Identifying cell types based on expression profiles is a pillar of single cell analysis. 'scROSHI' identifies cell types based on expression profiles of single cell analysis by utilizing previously obtained cell type specific gene sets. It takes into account the hierarchical nature of cell type relationship and does not require training or annotated data. A detailed description of the method can be found at: Prummer, Bertolini, Bosshard, Barkmann, Yates, Boeva, The Tumor Profiler Consortium, Stekhoven, and Singer (2022) <doi:10.1101/2022.04.05.487176>.

Lars Bosshard

scROSHI

Robust Supervised Hierarchical Identification of Single Cells

Michael Prummer

f_annot_ctgenes function

<dl><dt>m.cts</dt>
<dd>Matrix containing the cell type scores. The rows represent the cell types, whereas the columns represent the samples.</dd>
<dt>unknown</dt>
<dd>If none of the probabilities is above this threshold,
the cell type label is assigned to the class unknown.</dd>
<dt>uncertain</dt>
<dd>If the ratio between the largest and the second largest
probability is below this threshold, the cell type label is assigned to the
class uncertain for the major cell types.</dd></dl>

Arguments

Choose best matching cell type — f_annot_ctgenes

<dl>

<dt>m.cts</dt>
<dd>Matrix containing the cell type scores. The rows represent the cell types, whereas the columns represent the samples.</dd>


<dt>unknown</dt>
<dd>If none of the probabilities is above this threshold,
the cell type label is assigned to the class unknown.</dd>


<dt>uncertain</dt>
<dd>If the ratio between the largest and the second largest
probability is below this threshold, the cell type label is assigned to the
class uncertain for the major cell types.</dd>

</dl>

f_annot_ctgenes: Choose best matching cell type

Description

Usage

Value

Arguments

Examples