Overview
The MidarExperiment object organizes
data into two main categories: data and
metadata. The data category includes tables
for raw data, processed data, and feature metrics, while the
metadata category encompasses analysis annotations, feature
annotations, internal standard annotations, batch annotations, response
curve annotations, and calibration curves. Key identifiers, such as
analysis_id for analyses and feature_id for
features, are used to link data and metadata and are integral to the
functions of the package.
MidarExperiment
The MidarExperiment object serves as the primary data
container in the MiDAR workflow. It encompasses all experimental and
processed data, metadata, details of applied processing steps, and the
current data status. All MiDAR functions for data processing,
management, and visualization utilize MidarExperiment
objects as both input and output.
Data and Metadata
Data within the MidarExperiment is organized into data and metadata categories, each
divided into tables (data.frames).
Data
| Category | Table name (Slot) | Description |
|---|---|---|
| Raw Data | dataset_orig |
Original imported analysis data. |
| Processed Data | dataset |
Annotated raw and processed data with available metadata. |
| Feature metrics | feature_metrics |
Information and various quality control metrics for features. |
Metadata
| Data Type | Table name (Slot) | Description |
|---|---|---|
| Analyses Annotation | annot_analyses |
Details sample categories, amounts, dilutions, processing batches, and other relevant information. |
| Features Annotation | annot_features |
Describes internal standards for normalization, response factors, feature classification, and specifies quantifiers and internal standards. |
| Internal Standard | annot_istds |
Concentrations of internal standards added to samples. |
| Batches | annot_batches |
Specifies the boundaries (start and end) for each defined batch. |
| Response Curves | annot_responsecurves |
Defines response curves, detailing sample amounts across different steps. |
| Calibration Curves | annot_standards |
Defines concentrations of unlabelled and labelled standards in calibration curves and other quality control materials. |
Key Data Identifiers
The following key data fields are essential for organizing data within MiDAR. Many MiDAR functions depend on these fields, and exported data utilizes these identifier names.
| Table | Field | Description |
|---|---|---|
| Analyses | analysis_id |
Unique identifier for each analysis. |
sample_category |
Describes the function of sample in the analysis, such as Blank, QC, or study sample. Must be a subset of SPL, TQC, BQC, PBLK, SBLK, UBLK, MBLK, | |
batch_id |
Unique identifier for each batch level. | |
| Features | feature_id |
Unique identifier for each feature. |
istd_feature_id |
The feature_id of the internal standard used to
normalize raw intensities (each internal standard must be defined as a
feature). |
Field Naming Considerations
Certain field names differ from conventional terminology
(e.g., analysis_id instead of sample_id) to
enhance clarity and prevent confusion with other identifiers. A sample
may be measured multiple times across different methods or processing
replicates, necessitating distinct identifiers. Similarly, analytes can
be quantified through multiple transitions or adducts, which is
why feature_id is designated as the primary identifier.