CreateInfercnvObject: CreateInfercnvObject

In infercnv: Infer Copy Number Variation from Single-Cell RNA-Seq Data

Description

Creation of an infercnv object. This requires the following inputs: A more detailed description of each input is provided below:

The raw_counts_matrix:

MGH54_P16_F12 MGH53_P5_C12 MGH54_P12_C10 MGH54_P16_F02 MGH54_P11_C11 ... DDX11L1 0.0000000 0.000000 0.000000 0.000000 0.0000000 WASH7P 0.0000000 2.231939 7.186235 5.284944 0.9650009 FAM138A 0.1709991 0.000000 0.000000 0.000000 0.0000000 OR4F5 0.0000000 0.000000 0.000000 0.000000 0.0000000 OR4F29 0.0000000 0.000000 0.000000 0.000000 0.0000000 ...

The gene_order_file, contains chromosome, start, and stop position for each gene, tab-delimited:

chr start stop DDX11L1 chr1 11869 14412 WASH7P chr1 14363 29806 FAM138A chr1 34554 36081 OR4F5 chr1 69091 70008 OR4F29 chr1 367640 368634 OR4F16 chr1 621059 622053 ...

The annotations_file, containing the cell name and the cell type classification, tab-delimited.

V1 V2 1 MGH54_P2_C12 Microglia/Macrophage 2 MGH36_P6_F03 Microglia/Macrophage 3 MGH53_P4_H08 Microglia/Macrophage 4 MGH53_P2_E09 Microglia/Macrophage 5 MGH36_P5_E12 Oligodendrocytes (non-malignant) 6 MGH54_P2_H07 Oligodendrocytes (non-malignant) ... 179 93_P9_H03 malignant 180 93_P10_D04 malignant 181 93_P8_G09 malignant 182 93_P10_B10 malignant 183 93_P9_C07 malignant 184 93_P8_A12 malignant ...

and the ref_group_names vector might look like so: c("Microglia/Macrophage","Oligodendrocytes (non-malignant)")

Usage

CreateInfercnvObject(
  raw_counts_matrix,
  gene_order_file,
  annotations_file,
  ref_group_names,
  delim = "\t",
  max_cells_per_group = NULL,
  min_max_counts_per_cell = c(100, +Inf),
  chr_exclude = c("chrX", "chrY", "chrM")
)

Arguments

raw_counts_matrix	the matrix of genes (rows) vs. cells (columns) containing the raw counts If a filename is given, it'll be read via read.table() otherwise, if matrix or Matrix, will use the data directly.
gene_order_file	data file containing the positions of each gene along each chromosome in the genome.
annotations_file	a description of the cells, indicating the cell type classifications
ref_group_names	a vector containing the classifications of the reference (normal) cells to use for infering cnv
delim	delimiter used in the input files
max_cells_per_group	maximun number of cells to use per group. Default=NULL, using all cells defined in the annotations_file. This option is useful for randomly subsetting the existing data for a quicker preview run, such as using 50 cells per group instead of hundreds.
min_max_counts_per_cell	minimum and maximum counts allowed per cell. Any cells outside this range will be removed from the counts matrix. default=(100, +Inf) and uses all cells. If used, should be set as c(min_counts, max_counts)
chr_exclude	list of chromosomes in the reference genome annotations that should be excluded from analysis. Default = c('chrX', 'chrY', 'chrM')

Value

infercnv

Examples

data(infercnv_data_example)
data(infercnv_annots_example)
data(infercnv_genes_example)

infercnv_object_example <- infercnv::CreateInfercnvObject(raw_counts_matrix=infercnv_data_example, 
                                               gene_order_file=infercnv_genes_example,
                                               annotations_file=infercnv_annots_example,
                                               ref_group_names=c("normal"))

infercnv documentation built on Nov. 8, 2020, 11:10 p.m.