run_harmony: Local implementation of RunHarmony function

In andreaskapou/SeuratPipe: Packaging common Seurat analysis tasks

Local implementation of RunHarmony function

Description

This is a local implementation of RunHarmony function (from harmony package) which solves the bug where the 'dims.use' parameter is ignored.

Usage

run_harmony(
  object,
  group.by.vars,
  reduction = "pca",
  dims.use = NULL,
  theta = NULL,
  lambda = NULL,
  sigma = 0.1,
  nclust = NULL,
  tau = 0,
  block.size = 0.05,
  max.iter.harmony = 10,
  max.iter.cluster = 20,
  epsilon.cluster = 1e-05,
  epsilon.harmony = 1e-04,
  plot_convergence = FALSE,
  verbose = TRUE,
  reference_values = NULL,
  reduction.save = "harmony",
  assay.use = NULL,
  project.dim = TRUE,
  ...
)

Arguments

object	Seurat object.
group.by.vars	Which variable(s) to remove (character vector).
reduction	Dimensionality reduction to use.
dims.use	Which PCA dimensions to use for Harmony. By default, use all
theta	Diversity clustering penalty parameter. Specify for each variable in group.by.vars. Default theta=2. theta=0 does not encourage any diversity. Larger values of theta result in more diverse clusters.
lambda	Ridge regression penalty parameter. Specify for each variable in group.by.vars. Default lambda=1. Lambda must be strictly positive. Smaller values result in more aggressive correction.
sigma	Width of soft kmeans clusters. Default sigma=0.1. Sigma scales the distance from a cell to cluster centroids. Larger values of sigma result in cells assigned to more clusters. Smaller values of sigma make soft kmeans cluster approach hard clustering.
nclust	Number of clusters in model. nclust=1 equivalent to simple linear regression.
tau	Protection against overclustering small datasets with large ones. tau is the expected number of cells per cluster.
block.size	What proportion of cells to update during clustering. Between 0 to 1, default 0.05. Larger values may be faster but less accurate
max.iter.harmony	Maximum number of rounds to run Harmony. One round of Harmony involves one clustering and one correction step.
max.iter.cluster	Maximum number of rounds to run clustering at each round of Harmony.
epsilon.cluster	Convergence tolerance for clustering round of Harmony Set to -Inf to never stop early.
epsilon.harmony	Convergence tolerance for Harmony. Set to -Inf to never stop early.
plot_convergence	Whether to print the convergence plot of the clustering objective function. TRUE to plot, FALSE to suppress. This can be useful for debugging.
verbose	Whether to print progress messages. TRUE to print, FALSE to suppress.
reference_values	(Advanced Usage) Defines reference dataset(s). Cells that have batch variables values matching reference_values will not be moved
reduction.save	Keyword to save Harmony reduction. Useful if you want to try Harmony with multiple parameters and save them as e.g. 'harmony_theta0', 'harmony_theta1', 'harmony_theta2'
assay.use	(Seurat V3 only) Which assay to Harmonize with (Default Assay as default).
project.dim	Project dimension reduction loadings. Default TRUE.
...	other parameters

Author(s)

C.A.Kapourani [e-mail]

andreaskapou/SeuratPipe documentation built on Nov. 22, 2022, 4:16 p.m.