CIS_grubbs {ISAnalytics} | R Documentation

## Grubbs test for Common Insertion Sites (CIS).

### Description

Statistical approach for the validation of common insertion sites significance based on the comparison of the integration frequency at the CIS gene with respect to other genes contained in the surrounding genomic regions. For more details please refer to this paper: https://ashpublications.org/blood/article/117/20/5332/21206/Lentiviral-vector-common-integration-sites-in

### Usage

    CIS_grubbs(
      x,
      genomic_annotation_file = system.file("extdata", "hg19.refGene.oracle.tsv.xz",
        package = "ISAnalytics"),
      grubbs_flanking_gene_bp = 1e+05,
      threshold_alpha = 0.05,
      add_standard_padjust = TRUE
    )

### Arguments

`x` | An integration matrix, must include the `mandatory_IS_vars()` columns and the `annotation_IS_vars()` columns
`genomic_annotation_file` | Database file for gene annotation, see details
`grubbs_flanking_gene_bp` | Number of base pairs flanking a gene
`threshold_alpha` | Significance threshold
`add_standard_padjust` | Compute the standard padjust?

### Details

#### Genomic annotation file

This file is a data base, or more simply a .tsv file to import, with genes annotation for the specific genome. The annotations for the human genome (hg19) is already included in this package. If for any reason the user is performing an analysis on another genome, this file needs to be changed respecting the USCS Genome Browser format, meaning the input file headers should be:

    ## name2, chrom, strand
    ##  min_txStart, max_txEnd, minmax_TxLen
    ##  average_TxLen, name, min_cdsStart
    ##  max_cdsEnd, minmax_CdsLen, average_CdsLen

### Value

A data frame

### See Also

Other Analysis functions: `comparison_matrix()`, `compute_abundance()`, `cumulative_count_union()`, `sample_statistics()`, `separate_quant_matrices()`, `threshold_filter()`, `top_integrations()`

### Examples

    op <- options(ISAnalytics.widgets = FALSE)

    path_AF <- system.file("extdata", "ex_association_file.tsv",
        package = "ISAnalytics"
    )
    root_correct <- system.file("extdata", "fs.zip",
        package = "ISAnalytics"
    )
    root_correct <- unzip_file_system(root_correct, "fs")

    matrices <- import_parallel_Vispa2Matrices_auto(
        association_file = path_AF, root = root_correct,
        quantification_type = c("seqCount", "fragmentEstimate"),
        matrix_type = "annotated", workers = 2, patterns = NULL,
        matching_opt = "ANY",
        dates_format = "dmy"
    )

    cis <- CIS_grubbs(matrices)

    options(op)

[Package ISAnalytics version 1.2.1 Index]