searchCluster.batch {MetaCyto} | R Documentation

## Search for clusters using pre-defined labels in cytometry data from different studies in batch

### Description

A function that searches for clusters using pre-defined labels in cytometry data from different studies in batch.

### Usage

    searchCluster.batch(preprocessOutputFolder, outpath = "search_output",
      clusterLabel, ifPlot = TRUE)

### Arguments

`preprocessOutputFolder` | Directory where the pre-processed results are stored.
`outpath` | A string indicating the directory the results should be written to.
`clusterLabel` | A vector containing labels, such as c("CD3+|CD4+|CD8-")
`ifPlot` | True or False. Used to specify if a the density plot for each cluster should be plotted

### Details

The function writes out the summary statistics for each cluster. A separate directory will be created for each study.

### Value

Results will be written to the outpath folder

### Examples

    #get meta-data
    fn=system.file("extdata","fcs_info.csv",package="MetaCyto")
    fcs_info=read.csv(fn,stringsAsFactors=FALSE,check.names=FALSE)
    fcs_info$fcs_files=system.file("extdata",fcs_info$fcs_files,
                                   package="MetaCyto")
    # Make sure the transformation parameter "b" and the "assay" argument
    # are correct of FCM and CyTOF files
    b=assay=rep(NA,nrow(fcs_info))
    b[grepl("CyTOF",fcs_info$study_id)]=1/8
    b[grepl("FCM",fcs_info$study_id)]=1/150
    assay[grepl("CyTOF",fcs_info$study_id)]="CyTOF"
    assay[grepl("FCM",fcs_info$study_id)]="FCM"
    # preprocessing
    preprocessing.batch(inputMeta=fcs_info,
                        assay=assay,
                        b=b,
                        outpath="Example_Result/preprocess_output",
                        excludeTransformParameters=c("FSC-A","FSC-W","FSC-H",
                        "Time","Cell_length"))
    # Make sure marker names are consistant in different studies
    files=list.files("Example_Result",pattern="processed_sample",recursive=TRUE,
                     full.names=TRUE)
    nameUpdator("CD8B","CD8",files)
    # find the clusters
    cluster_label=c("CD3-|CD19+","CD3+|CD4-|CD8+")
    searchCluster.batch(preprocessOutputFolder="Example_Result/preprocess_output",
                        outpath="Example_Result/search_output",
                        clusterLabel=cluster_label)

[Package MetaCyto version 1.2.1 Index]