Fetch data from the hdf5 file and returns a Seurat object

Usage

FetchH5(
  data_file,
  meta_file,
  name = NULL,
  features = NULL,
  layer = NULL,
  assay = NULL,
  metanames = NULL,
  reduction = NULL,
  verbose = TRUE
)

Arguments

data_file: The path to the hdf5 file containing the data.
meta_file: The path to the hdf5 file containing the metadata.
name: Dataset in the hdf5 file. If not specified, the function will attempt to find the shared group name in both files.
features: The names of the genes or features to fetch. If specified, only these features will be fetched.
layer: The layer for the counts in the hdf5 file. If not specified, the first layer will be used.
assay: Assay to use. If not specified, the default assay in the hdf5 file will be used.
metanames: The names of the metadata columns to fetch.
reduction: Reduction to fetch.
verbose: Whether to print the message. Default is TRUE.

Value

A Seurat object with the fetched data.

Examples

data(pancreas_sub)
pancreas_sub <- RunStandardWorkflow(pancreas_sub)
#> ℹ [2026-10-11 22:56:35] Start standard processing workflow...
#> ℹ [2026-10-11 22:56:35] Checking a list of <Seurat>...
#> ! [2026-10-11 22:56:35] Data 1/1 of the `srt_list` is "unknown"
#> ℹ [2026-10-11 22:56:35] Perform `NormalizeData()` with `normalization.method = 'LogNormalize'` on 1/1 of `srt_list`...
#> ℹ [2026-10-11 22:56:35] Perform `FindVariableFeatures()` on 1/1 of `srt_list`...
#> ℹ [2026-10-11 22:56:35] Use the separate HVF from `srt_list`
#> ℹ [2026-10-11 22:56:35] Number of available HVF: 2000
#> ℹ [2026-10-11 22:56:35] Finished check
#> ℹ [2026-10-11 22:56:35] Perform `ScaleData()`
#> ℹ [2026-10-11 22:56:35] Perform pca linear dimension reduction
#> ℹ [2026-10-11 22:56:36] Use stored estimated dimensions 1:23 for Standardpca
#> ℹ [2026-10-11 22:56:36] Perform `Seurat::FindClusters()` with `cluster_algorithm = 'louvain'` and `cluster_resolution = 0.6`
#> ℹ [2026-10-11 22:56:36] Reorder clusters...
#> ℹ [2026-10-11 22:56:36] Skip `log1p()` because `layer = data` is not "counts"
#> ℹ [2026-10-11 22:56:36] Perform umap nonlinear dimension reduction
#> ✔ [2026-10-11 22:56:42] Standard processing workflow completed
PrepareSCExplorer(pancreas_sub, base_dir = tempdir())
#> ℹ [2026-10-11 22:56:42] Set the project name of each <Seurat> to their dataset name
#> ℹ [2026-10-11 22:56:42] Prepare data for object: "SeuratProject"
#> ℹ [2026-10-11 22:56:42] Write the expression matrix to: /tmp/RtmpvxnYGg/data.hdf5
#> ℹ [2026-10-11 22:56:44] Write the meta information to: /tmp/RtmpvxnYGg/meta.hdf5
srt <- FetchH5(
  data_file = paste0(tempdir(), "/data.hdf5"),
  meta_file = paste0(tempdir(), "/meta.hdf5"),
  features = c("Ins1", "Ghrl"),
  metanames = c("SubCellType", "Phase"),
  reduction = "UMAP"
)

Fetch data from the hdf5 file and returns a Seurat object

Usage

Arguments

Value

See also

Examples