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Check and preprocess a list of Seurat objects

Source: R/CheckData.R
CheckDataList.Rd

Checks and preprocesses a list of Seurat objects. It performs various checks on the input, including verification of input types, assay type consistency, feature name consistency, and batch column consistency. It also performs data normalization and variable feature finding based on the specified parameters. Finally, it prepares the data for integration analysis based on the highly variable features.

Usage

CheckDataList(
  srt_list,
  batch,
  assay = NULL,
  do_normalization = NULL,
  normalization_method = "LogNormalize",
  do_HVF_finding = TRUE,
  HVF_source = "separate",
  HVF_method = "vst",
  nHVF = 2000,
  HVF_min_intersection = 1,
  HVF = NULL,
  vars_to_regress = NULL,
  verbose = TRUE,
  seed = 11
)

Arguments

srt_list

A list of Seurat objects to be checked and preprocessed.

batch

Batch variable name.

assay

Assay to use. NULL uses the default assay.

do_normalization

Whether data normalization should be performed.

normalization_method

The normalization method to be used. Possible values are "LogNormalize", "SCT", "TFIDF", and "scran".

do_HVF_finding, HVF_method, nHVF, HVF

Highly variable features. HVF_method is "vst", "mvp", "disp", or "scran".

HVF_source

The source of highly variable features. Possible values are "global" and "separate".

HVF_min_intersection

The feature needs to be present in batches for a minimum number of times in order to be considered as highly variable.

vars_to_regress

A vector of variable names to include as additional regression variables.

verbose

Whether to print the message. Default is TRUE.

seed

Random seed.

Value

A list containing the preprocessed Seurat objects, the highly variable features, the assay name, and the type of assay.

Details

For chromatin assays with HVF_source = "separate", Seurat::SelectIntegrationFeatures() ranks peaks by the number of batches selecting them, then by their median variable-feature rank. The nHVF cap is also limited to the smallest per-batch variable-feature count; HVF_min_intersection is applied to the ranked selection. This preserves within-batch peak frequency ranking instead of sorting tied peak IDs.

Examples

counts <- matrix(rep(6:1, 4),
  nrow = 6,
  dimnames = list(
    paste0("chr1-", seq(1, 501, 100), "-", seq(50, 550, 100)),
    paste0("cell", 1:4)
  )
)
peaks <- Signac::CreateChromatinAssay(counts,
  min.cells = 0,
  min.features = 0, verbose = FALSE
)
object <- SeuratObject::CreateSeuratObject(peaks, assay = "peaks")
checked <- CheckDataList(list(object),
  batch = "sample", assay = "peaks",
  do_normalization = FALSE, normalization_method = "TFIDF", nHVF = 3,
  verbose = FALSE
)
checked$HVF
#> [1] "chr1-1-50"    "chr1-101-150" "chr1-201-250"