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Run copy-number alteration inference

Source: R/RunCNV.R
RunCNV.Rd

Run copy-number alteration inference

Usage

RunCNV(
  object,
  method = c("copykat", "fastCNV", "scevan", "infercnv", "numbat"),
  assay = NULL,
  layer = "counts",
  group.by = NULL,
  reference.by = NULL,
  reference = NULL,
  genome = c("hg38", "hg19", "mm10"),
  gene_order = NULL,
  sample.by = NULL,
  allele_counts = NULL,
  reference_counts = NULL,
  output_dir = NULL,
  prefix = "CNV",
  tool_name = "CNV",
  store_matrix = TRUE,
  verbose = TRUE,
  srt = NULL,
  ...
)

Source

The example uses expression and cell annotations from GSE70630.

Arguments

object

A Seurat object.

method

CNA/CNV method. Supported methods are "copykat", "fastCNV", "scevan", "infercnv", and "numbat".

assay

Assay to use. NULL uses the default assay.

layer

Assay layer used as the expression matrix.

group.by

Optional metadata column forwarded to supported methods and stored as cell annotation.

reference.by

Metadata column identifying reference/normal cells. Required for "infercnv" and "fastCNV".

reference

Reference labels in reference.by.

genome

Reference genome label.

gene_order

Gene coordinate table or a path to one. The table should contain gene, chromosome, start, and end columns. If NULL, SCOP tries to resolve these columns from assay feature metadata.

sample.by

Optional sample metadata column.

allele_counts

Allele count table for "numbat". This is forwarded to numbat::run_numbat() as df_allele.

reference_counts

Reference expression profile for "numbat". This is forwarded to numbat::run_numbat() as lambdas_ref.

output_dir

Optional output directory.

prefix

Prefix for metadata columns.

tool_name

Name used for srt@tools.

store_matrix

Whether to store the normalized CNV matrix in srt@tools[[tool_name]].

verbose

Whether to print the message. Default is TRUE.

srt

Deprecated alias for object; supply exactly one of the two. It will be removed in scop 1.0.0.

...

Arguments passed to other functions.

Value

A Seurat object with CNV metadata columns and a result bundle in srt@tools[[tool_name]].

See also

CNVPlot

Examples

base_url <- paste0(
  "https://raw.githubusercontent.com/broadinstitute/infercnv/",
  "1def6c930335d00ddf251474abb0a31a1c74b0da/inst/extdata/"
)
files <- c("oligodendroglioma_expression_downsampled.counts.matrix.gz",
           "oligodendroglioma_annotations_downsampled.txt")
counts_file <- tempfile(fileext = ".gz")
labels_file <- tempfile()
utils::download.file(paste0(base_url, files[1]), counts_file, mode = "wb")
utils::download.file(paste0(base_url, files[2]), labels_file, mode = "wb")
counts <- as.matrix(utils::read.delim(counts_file, row.names = 1, check.names = FALSE))
labels <- utils::read.delim(labels_file, header = FALSE, row.names = 1)
cohort <- labels[colnames(counts), 1]
colnames(counts) <- paste0("cell_", colnames(counts))
srt <- SeuratObject::CreateSeuratObject(Matrix::Matrix(counts, sparse = TRUE))
srt$group <- factor(
  ifelse(startsWith(cohort, "malignant_"), sub("^malignant_", "Tumor ", cohort), "Reference"),
  levels = c("Reference", "Tumor 93", "Tumor 97", "Tumor MGH36", "Tumor MGH53")
)
set.seed(42)
srt <- RunCNV(srt, method = "copykat", reference.by = "group", reference = "Reference")
#> ℹ [2026-11-12 05:25:46] Run copykat CNV backend with 10338 features and 184 cells
#> ℹ [2026-11-12 05:25:46] Attached copykat to the search path so its lazy data objects are resolvable by the backend
#> [1] "running copykat v1.2.5"
#> [1] "step1: read and filter data ..."
#> [1] "10338 genes, 184 cells in raw data"
#> [1] "9450 genes past LOW.DR filtering"
#> [1] "step 2: annotations gene coordinates ..."
#> [1] "start annotation ..."
#> [1] "step 3: smoothing data with dlm ..."
#> [1] "step 4: measuring baselines ..."
#> [1] "42 known normal cells found in dataset"
#> [1] "run with known normal..."
#> [1] "baseline is from known input"
#> [1] "step 5: segmentation..."
#> [1] "step 6: convert to genomic bins..."
#> [1] "step 7: re-adjust baseline ..."
#> [1] "step 8: final prediction ..."
#> [1] "step 9: saving results..."
#> [1] "step 10: ploting heatmap ..."
#> Time difference of 1.171434 mins
#> ✔ [2026-11-12 05:26:56] copykat CNV results stored in `srt@tools[[CNV]]`
CNVPlot(srt, group.by = "group", heatmap_limits = "auto")