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ISA File Types

last updated at 2023-06-14 About this guide

In this guide we introduce the different ISA file types used in the ARC.

UserNewbie ModeRead

Before we can start

ARC builds on ISA

The ARC builds on the ISA Abstract Model for metadata annotation. Briefly, the ISA model comes with a hierarchy (ISA: Investigation - Study - Assay) that aligns well with most projects in (plant) biology labs. It allows to group multiple assays to one study, and multiple studies to one investigation.

Image source (left panel): https://isa-tools.org/format/specification.html

Your ARC has one isa.investigation.xlsx workbook at its root (i.e. every ARC collects the data to one investigation). Each study or assay that you add to your ARC contains one isa.study.xlsx or isa.assay.xlsx, respectively.

ISA-Tab for intuitive collection of metadata

The most user-intuitive format of the ISA metadata framework is ISA-Tab. As the name suggest, it's a tabular format. Hence, you can view the files in a spread-sheet program of choice.

Comparison of the ISA file types. Grey cells: keys. White cells: values.

The major difference between the ISA workbooks is their read-direction:

A registry to your ARC

The isa.investigation.xlsx allows to store metadata relevant on the investigation-level (e.g. title, date, contributor and publication details of the investigation). In addition, it functions as a "registry" to your ARC.

Each study (isa.study.xlsx) and assay (isa.assay.xlsx) of your ARC as well as a summary of metadata contained in them are registered and listed in the isa.investigation.xlsx.

The isa.investigation.xlsx functions as registry to your ARC.

💡 When opening the isa.investigation.xlsx for the first time, it may be necessary to widen the first column to make the entries visible.

Communicate how your processes connect

The output of one study or assay can function as the input to another study or assay. By using the same unique identifiers across your isa.study.xlsx and isa.assay.xlsx workbooks, respectively, you can communicate how the experimental processes and workflows connect.

Use unique identifiers across ISA files to connect your workflows.

You can point to data files

By linking files stored in your ARC (e.g. raw data files in a dataset folder), you can let others know which experimental workflow was followed to produce these data files.

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