added networkType option to TestSoftPowers

Package: hdWGCNA

Title: hdWGCNA

Version: 0.1.2.0000

Version: 0.1.2.0001

Authors@R: c(

    person("Sam", "Morabito", , "smorabit@uci.edu", role = c("aut", "cre"),

           comment = c(ORCID = "0000-0002-7768-4856")),

# hdWGCNA 0.1.2.0001 (2022-09-19)

## Added

- None

## Changes

- networkType option in `TestSoftPowers`.

# hdWGCNA 0.1.2.0000 (2022-09-08)

## Added

- Differential Module Eigengene (DME) tutorial

#'

#' @param seurat_obj A Seurat object

#' @param powers numeric vector specifying soft powers to test

#' @param setDatExpr logical flag indicating whether to run setDatExpr

#' @param use_metacells logical flag for whether to use the metacell expression matrix

#' @param networkType The type of network to use for network analysis. Options are "signed" (default), "unsigned", or "signed hybrid". This should be consistent with the network chosen for ConstructNetwork

#' @param corFnc Correlation function for the gene-gene correlation adjacency matrix.

#' @param setDatExpr logical flag indicating whether to run setDatExpr.

#' @param group.by A string containing the name of a column in the Seurat object with cell groups (clusters, cell types, etc). If NULL (default), hdWGCNA uses the Seurat Idents as the group.

#' @param group_name A string containing a group present in the provided group.by column or in the Seurat Idents. A character vector can be provided to select multiple groups at a time.

#' @param ... additional parameters passed to SetDatExpr

#' @keywords scRNA-seq

#' @export

TestSoftPowers <- function(

  seurat_obj,

  powers=c(seq(1,10,by=1), seq(12,30, by=2)),

  setDatExpr = FALSE,

  use_metacells = TRUE,

  group.by=NULL, group_name=NULL

  networkType="signed",

  corFnc='bicor',

  setDatExpr = FALSE,

  group.by=NULL, group_name=NULL,

  ...

){

  # add datExpr if not already added:

      datExpr,

      powerVector=powers,

      verbose = 100,

      networkType="signed",

      corFnc="bicor"

      networkType=networkType,

      corFnc=corFnc,

      ...

    )[[2]]

  );

#'

#' @param seurat_obj A Seurat object

#' @param powers numeric vector specifying soft powers to test

#' @param setDatExpr logical flag indicating whether to run setDatExpr

#' @param use_metacells logical flag for whether to use the metacell expression matrix

#' @param networkType The type of network to use for network analysis. Options are "signed" (default), "unsigned", or "signed hybrid". This should be consistent with the network chosen for ConstructNetwork

#' @param corFnc Correlation function for the gene-gene correlation adjacency matrix.

#' @param setDatExpr logical flag indicating whether to run setDatExpr.

#' @param group.by A string containing the name of a column in the Seurat object with cell groups (clusters, cell types, etc). If NULL (default), hdWGCNA uses the Seurat Idents as the group.

#' @param group_name A string containing a group present in the provided group.by column or in the Seurat Idents. A character vector can be provided to select multiple groups at a time.

#' @param multi.group.by A string containing the name of a column in the Seurat object with groups for consensus WGCNA (dataset, sample, condition, etc)

#' @param multi_groups A character vecrtor containing the names of groups to select

#' @param ... additional parameters passed to SetDatExpr

#' @keywords scRNA-seq

#' @export

#' @examples

#' TestSoftPowers(pbmc)

#' # TestSoftPowers(pbmc)

TestSoftPowersConsensus <- function(

  seurat_obj,

  powers=c(seq(1,10,by=1), seq(12,30, by=2)),

  setDatExpr = FALSE,

  use_metacells = TRUE,

  networkType="signed",

  corFnc='bicor',

  setDatExpr = FALSE,

  group.by=NULL, group_name=NULL,

  multi.group.by = NULL,

  multi_groups = NULL

  multi_groups = NULL,

  ...

){

  # add multiExpr if not already added:

        multiExpr[[cur_group]]$data,

        powerVector=powers,

        verbose = 100,

        networkType="signed",

        corFnc="bicor"

        networkType=networkType,

        corFnc=corFnc,

        ...

      )[[2]]

    );

    powerTable$data$group <- cur_group

#' SetDatExpr

#'

#' This function sets up the gene expression matrix for co-expression network analysis.

#' This function specifies the gene expression matrix for co-expression network analysis.

#'

#' @param seurat_obj A Seurat object

#' @param group_name A string containing a group present in the provided group.by column or in the Seurat Idents. A character vector can be provided to select multiple groups at a time.

Our original description of applying WGCNA to single-nucleus RNA-seq data:

* [Single-nucleus chromatin accessibility and transcriptomic characterization of Alzheimer’s disease](https://doi.org/10.1038/s41588-021-00894-z)

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