Imports tabular data files (*.tsv) generated from MRMhub containing peak
integration results. The input files must be in a long format with columns
for the raw data file name, feature ID, peak intensity, and other columns.
Additional information, such as retention time, FWHM, precursor/product m/z,
and CE will also be imported and made available in the MRMhubExperiment
object for downstream analyses.
When a directory path is provided, all matching files in that directory will be imported and merged into a single dataset. This is useful when importing datasets that were pre-processed in blocks, resulting in multiple files. Each unique combination of feature and raw data file must only occur once across all source data files. Duplicate combinations will result in an error.
Arguments
- data
MRMhubExperimentobject- path
One or more file paths, or a directory path (in which case all matching files will be imported)
- import_metadata
Logical, whether to import additional metadata columns (e.g.,
batch_id,qc_type)- silent
Logical, whether to suppress most notifications
Value
MRMhubExperiment object with the imported data
Identifier normalization
All imported identifiers are whitespace-normalized on import: leading and
trailing spaces are removed and internal runs of whitespace are collapsed to
a single space (for example "QC 01" becomes "QC 01"). Raw-data file
extensions (.mzML, .d, .raw, .wiff, .wiff2, .lcd, .chrom,
case-insensitive) are stripped from analysis_id.
The same normalization is applied to both the data and the metadata, which is
what lets an analysis_id typed into metadata match the one derived from a
data-file name instead of silently failing to join. A consequence is that two
identifiers differing only by whitespace collapse to one and are then reported
as duplicates.
Examples
mexp <- MRMhubExperiment()
file_path = system.file("extdata", "MRMhub_demo.tsv", package = "mrmhub")
mexp <- import_data_mrmhub(
data = mexp,
path = file_path,
import_metadata = TRUE)
#> ✔ Imported 499 analyses with 28 features.
#> ℹ feature_area selected as default feature intensity. Modify with `set_intensity_var()`.
#> ✔ Analysis metadata associated with 499 analyses.
#> ✔ Feature metadata associated with 28 features.
print(mexp)
#>
#> ── MRMhubExperiment: ──────────────────────────────────────────────────────────
#> NA | 499 analyses and 28 features | signal: feature_area
#> Last step: Annotated raw AREA values
#> Normalized ✖ Quantitated ✖ Drift/batch ✖ Filtered ✖
#> ℹ Use `mrmhub_status()` for the full processing and metadata report