Seurat: PrepLDA – R documentation

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PrepLDA

Function to prepare data for Linear Discriminant Analysis.

Description

This function performs unsupervised PCA on each mixscape class separately and projects each subspace onto all cells in the data.

Usage

PrepLDA(
  object,
  de.assay = "RNA",
  pc.assay = "PRTB",
  labels = "gene",
  nt.label = "NT",
  npcs = 10,
  verbose = TRUE,
  logfc.threshold = 0.25
)

Arguments

`object`	An object of class Seurat.
`de.assay`	Assay to use for selection of DE genes.
`pc.assay`	Assay to use for running Principle components analysis.
`labels`	Meta data column with target gene class labels.
`nt.label`	Name of non-targeting cell class.
`npcs`	Number of principle components to use.
`verbose`	Print progress bar.
`logfc.threshold`	Limit testing to genes which show, on average, at least X-fold difference (log-scale) between the two groups of cells. Default is 0.25 Increasing logfc.threshold speeds up the function, but can miss weaker signals.

Value

Returns a list of the first 10 PCs from each projection.

Seurat

Tools for Single Cell Genomics

v4.0.1

GPL-3 | file LICENSE

Authors

Andrew Butler [ctb] (<https://orcid.org/0000-0003-3608-0463>), Saket Choudhary [ctb] (<https://orcid.org/0000-0001-5202-7633>), Charlotte Darby [ctb] (<https://orcid.org/0000-0003-2195-5300>), Jeff Farrell [ctb], Christoph Hafemeister [ctb] (<https://orcid.org/0000-0001-6365-8254>), Yuhan Hao [ctb] (<https://orcid.org/0000-0002-1810-0822>), Paul Hoffman [aut, cre] (<https://orcid.org/0000-0002-7693-8957>), Jaison Jain [ctb] (<https://orcid.org/0000-0002-9478-5018>), Efthymia Papalexi [ctb] (<https://orcid.org/0000-0001-5898-694X>), Patrick Roelli [ctb], Rahul Satija [ctb] (<https://orcid.org/0000-0001-9448-8833>), Karthik Shekhar [ctb], Avi Srivastava [ctb] (<https://orcid.org/0000-0001-9798-2079>), Tim Stuart [ctb] (<https://orcid.org/0000-0002-3044-0897>), Kristof Torkenczy [ctb] (<https://orcid.org/0000-0002-4869-7957>), Shiwei Zheng [ctb] (<https://orcid.org/0000-0001-6682-6743>), Satija Lab and Collaborators [fnd]

Initial release

2021-03-17