Create 10x Xenium Giotto Object — createGiottoXeniumObject • Giotto

Given the path to a Xenium experiment output folder, creates a Giotto object

createGiottoXeniumObject(
  xenium_dir,
  data_to_use = c("subcellular", "aggregate"),
  load_format = "csv",
  h5_expression = TRUE,
  h5_gene_ids = c("symbols", "ensembl"),
  gene_column_index = 1,
  bounds_to_load = c("cell"),
  qv_threshold = 20,
  key_list = NULL,
  instructions = NULL,
  cores = NA,
  verbose = TRUE
)

Arguments

xenium_dir: full path to the exported xenium directory
data_to_use: which type(s) of expression data to build the gobject with (e.g. default: 'subcellular', 'aggregate', or 'all')
load_format: files formats from which to load the data. Either `csv` or `parquet` currently supported.
h5_expression: (boolean) whether to load cell_feature_matrix from .h5 file. Default is TRUE
h5_gene_ids: use gene symbols (default) or ensembl ids for the .h5 gene expression matrix
gene_column_index: which column from the features or genes .tsv file to use for row ids
bounds_to_load: vector of boundary information to load (e.g. 'cell' or 'nucleus' by themselves or c('cell', 'nucleus') to load both at the same time.)
qv_threshold: Minimum Phred-scaled quality score cutoff to be included as a subcellular transcript detection (default = 20)
key_list: (advanced) list of grep-based keywords to split the subcellular feature detections by feature type. See details
instructions: list of instructions or output result from createGiottoInstructions
cores: how many cores or threads to use to read data if paths are provided
verbose: be verbose when building Giotto object

Value

giotto object

Details

[QC feature types] Xenium provides info on feature detections that include more than only the Gene Expression specific probes. Additional probes for QC are included: blank codeword, negative control codeword, and negative control probe. These additional QC probes each occupy and are treated as their own feature types so that they can largely remain independent of the gene expression information.

[key_list] Related to data_to_use = 'subcellular' workflow only: Additional QC probe information is in the subcellular feature detections information and must be separated from the gene expression information during processing. The QC probes have prefixes that allow them to be selected from the rest of the feature IDs. Giotto uses a named list of keywords (key_list) to select these QC probes, with the list names being the names that will be assigned as the feature type of these feature detections. The default list is used when key_list = NULL.

Default list:


 list(blank_code = 'BLANK_',
      neg_code = 'NegControlCodeword_',
      neg_probe = c('NegControlProbe_|antisense_'))

The Gene expression subset is accepted as the subset of feat_IDs that do not map to any of the keys.