generate_analysis {ChromSCape} | R Documentation

## Generate a complete ChromSCape analysis

### Description

Generate a complete ChromSCape analysis

### Usage

    generate_analysis(input_data_folder,
    analysis_name = "Analysis_1",
    output_directory = "./",
    input_data_type = c("scBED", "DenseMatrix", "SparseMatrix",
                       "scBAM")[1],
    feature_count_on = c("bins","genebody","peaks")[1],
    feature_count_parameter = 50000,
    ref_genome = c("hg38","mm10")[1],
    run = c("filter", "CNA","cluster", "consensus","peak_call", "coverage",
           "DA", "GSA", "report")[c(1,3,6,7,8,9)],
    min_reads_per_cell = 1000,
    max_quantile_read_per_cell = 99,
    n_top_features = 40000,
    norm_type = "CPM",
    subsample_n = NULL,
    exclude_regions = NULL,
    n_clust = NULL,
    corr_threshold = 99,
    percent_correlation = 1,
    maxK = 10,
    qval.th = 0.1,
    logFC.th = 1,
    enrichment_qval = 0.1,
    doBatchCorr  = FALSE,
    batch_sels  = NULL,
    control_samples_CNA = NULL,
    genes_to_plot = c("Krt8","Krt5","Tgfb1", "Foxq1", "Cdkn2b",
                     "Cdkn2a", "chr7:15000000-20000000")
    )

### Arguments

`input_data_folder` | Directory containing the input data.
`analysis_name` | Name given to the analysis.
`output_directory` | Directory where to create the analysis and the HTML report.
`input_data_type` | The type of input data.
`feature_count_on` | For raw data type, on which features to count the cells.
`feature_count_parameter` | Additional parameter corresponding to the 'feature_count_on' parameter. E.g. for 'bins' must be a numeric, e.g. 50000, for 'peaks' must be a character containing path towards a BED peak file.
`ref_genome` | The genome of reference.
`run` | What steps to run. By default runs everything. Some steps are required in order to run downstream steps.
`min_reads_per_cell` | Minimum number of reads per cell.
`max_quantile_read_per_cell` | Upper quantile above which to consider cells doublets.
`n_top_features` | Number of features to keep in the analysis.
`norm_type` | Normalization type.
`subsample_n` | Number of cells per condition to downsample to, for performance principally.
`exclude_regions` | Path towards a BED file containing CNA to exclude from the analysis (optional).
`n_clust` | Number of clusters to force choice of clusters.
`corr_threshold` | Quantile of correlation above which two cells are considered as correlated.
`percent_correlation` | Percentage of the total cells that a cell must be correlated with in order to be kept in the analysis.
`maxK` | Upper cluster number to rest for ConsensusClusterPlus.
`qval.th` | Adjusted p-value below which to consider features differential.
`logFC.th` | Log2-fold-change above/below which to consider a feature depleted/enriched.
`enrichment_qval` | Adjusted p-value below which to consider a gene set as significantly enriched in differential features.
`doBatchCorr` | Logical indicating if batch correction using fastMNN should be run.
`batch_sels` | If doBatchCorr is TRUE, a named list containing the samples in each batch.
`control_samples_CNA` | If running CopyNumber Analysis, a character vector of the sample names that are 'normal'.
`genes_to_plot` | A character vector containing genes of interest of which to plot the coverage.

### Value

Creates a ChromSCape-readable directory and saved objects, as well as a multi-tabbed HTML report resuming the analysis.

### Examples

    ## Not run:
    generate_analysis("/path/to/data/", "Analysis_1")

    ## End(Not run)

[Package ChromSCape version 1.2.62 Index]