MethylDeconv_pipeline: Deconvolution Pipeline

In jysonganan/methylDeConv: Computational pipeline for deconvolution of methylation data.

Deconvolution Pipeline

Description

Deconvolution Pipeline

Usage

MethylDeconv_pipeline(
  input_methyl,
  normalized = FALSE,
  array_type = "450k",
  feature_selection = "oneVsAllttest",
  deconv_algorithm = "Houseman",
  tissue = "general",
  extend_reference = TRUE,
  custom_probes = NULL
)

Arguments

input_methyl	Methylation array for mixture samples. The rows correpsond to the probes/CpGs; the columns correspond to the samples.
normalized	If TRUE, the methylation array is the beta value matrix. Default value: FALSE.
array_type	The array type can be 450k or EPIC. Default value: "450k".
feature_selection	Different feature selection methods such as "oneVsAllttest" (Default value), "oneVsAllLimma", "pairwiseLimma", "pairwiseGlmnet", "multiGlmnet", "glmnetpreselect", "RFpreselect", "OptVariables".
deconv_algorithm	Different deconvolution algorithms such as "Houseman" (default value), "RPC", "CBS", "MethylResolver", "MCP-counter", "ssGSEA", "ESTIMATE".
tissue	Different tissue types such as "general" (default value) which correspond to blood tissue and general epithelial tissue; "brain" correpsonds to brain tissues.
extend_reference	Default: TRUE. If TRUE, extend the reference library.
custom_probes	Default: NULL. The user-defined probe lists.

Value

The deconvolution results (cell type proportions) with rows as the samples and the columns as cell types.

jysonganan/methylDeConv documentation built on Aug. 8, 2022, 6:25 a.m.