Annotation Principles

Annotation of data and workflows within the ARC builds on the ISA model. In this guide we introduce the different building blocks available to annotate your workflows in a study (isa.study.xlsx) or assay (isa.assay.xlsx).

Input

Every annotation table must start with the Input column, which defines the input of your table and can be of type “Source Name”, “Sample Name”, “Material”, or “Data”. This input value must be a unique identifier for an organism or a sample. The number of Input columns per table is limited to one.

Characteristics

Characteristic columns describe inherent properties of the source material, e.g., a certain strain or ecotype, but also the temperature an organism was exposed to. You can add any number of Characteristic columns.

Factor

Use Factor columns to describe independent variables that determine the specific output of your experiment when processes and analysis were identical. Most of the time, Factors are the most important building blocks for downstream computational analysis. You can add any number of Characteristic columns.

Parameter

Parameter columns describe steps in your experimental workflow, e.g., the temperature or extraction buffer used for your assay. Multiple Parameter columns form a protocol. You can add any number of Parameter columns.

Component

Use Component columns to list anything physical of a protocol that can be consumed, e.g. instrument names, software names, or reagents names. You can add any number of Component columns.

Protocol Columns

Use Protocol REF columns to reference the protocol used in the table, i.e., the name of the protocol. Protocol Type columns define the type, e.g. a growth protocol. The number of columns for each subtype is limited to one per table.

Output

Per table only one Output column is allowed, which can either be a “Sample Name”, “Material”, or “Data”. Data files can be sources or outputs of computational workflows. The value of this column must be a unique identifier.