Analytical data, i.e. preprocessed data from mass spectrometry experiments, can be imported from different sources.
Data files present in a folder can also be imported and merged as well. This can be useful when the raw data processing is broken down in batches resulting in separate result files.
Data Sources
Following formats are currently supported:
| Source | MiDAR function | Details | File |
|---|---|---|---|
| Agilent MassHunter | import_data_massshunter() |
Flat and nested tables from MassHunter Quant. | .csv |
| MRMkit | import_data_mrmkit() |
Long format output format | .tsv |
| Plain wide CSV | import_data_table() |
Samples/analyses as rows and features as columns. Can contain columns specific sample annotations. | .csv |
Metadata within analytical results
When the analytical results contain metadata, such as sample and
feature annotations, these can be imported as metadata in the
MidarExperiment object as well. The imported metadata is
checked for integrity and consistency (see TODO) and then added to the
annotation tables within the MidarExperiment. To include
available metadata, set the argument
import_metadata = TRUE.
MRMkit Results
Output files from MRMkit, an open-source peak integration software for MRM data () can imported directly. Specific metadata present in the data file can be imported as well (`import_metadata = TRUE`)
library(midar)
filepath <- system.file("extdata/MRMkit_demo.tsv", package = "midar")
myexp <- MidarExperiment()
myexp <- import_data_mrmkit(myexp, filepath, import_metadata = TRUE)Agilent MassHunter Quantitative
Peak integration results exported from Agilent Masshunter Quant in the CSV format can be imported. Samples must be present in rows, features as columns. Import of qualifier results is supported. Sample, method and result metadata present in the files can also be imported (`import_metadata = TRUE`)
filepath <- system.file("extdata/MHQuant_demo.csv", package = "midar")
myexp <- MidarExperiment()
myexp <- import_data_masshunter(myexp, filepath, import_metadata = TRUE)Plain CSV files
Analysis results, whether raw intensities (e.g., peak areas) or
preprocessed data (e.g., concentrations), can be provided as plain CSV
tables. In these tables, analyses (samples) should be arranged in rows,
and features in columns. The specific data type in the table (e.g., area
or concentration) is defined using
the variable_name argument.
filepath <- system.file("extdata/plain_wide_dataset.csv", package = "midar")
myexp <- MidarExperiment()
myexp <- midar::import_data_csv(
myexp, path = filepath,
variable_name = "area",
import_metadata = TRUE)Importing and merging multiple files
Multiple data files can be imported and merged simultaneously. Users can either provide a list of file paths or specify a folder path to import all data files within that directory. This support for multiple files is useful when raw data processing is divided into batches, leading to separate result files.
The imported merged data is checked for consistency, ensuring that each analysis ID and feature ID pair is unique. This means that the same feature cannot be reported multiple times within the same analysis, which can happend for example if the same feature in the same sample was integrated in different raw data processing batches.