Process peptidomic data, search for bioactive peptides, and export results.
Upload a pre-computed functional annotation table, or search a functional database by sequence similarity.
Group your abundance columns into experimental conditions. If any columns are technical replicates, define them below first — they will be averaged into a single biological replicate and become available in the group selector.
Instrument exports often use long sample names (e.g. Abundance F1 Sample Threshold). Map them to shorter labels here first — the simplified names are used throughout the technical-replicate and grouping steps below.
{"T_0.2a": "Abundance F1 Sample Threshold"}{"Sample_A": ["Sample_A ( rep1)", "Sample_A ( rep2)"]}{"Control": ["T_0_2a", "T_0_2b"]}Resolve ambiguous protein mapping from search engines. Then, if your data has unknown protein names, you can provide your own FASTA file or fetch from UniProt.
Select which protein ID to use for rows where a peptide maps to more than one protein.
Fold several protein accessions (including single-protein ones the section above can't reach,
e.g. β-casein variants P02666A1 and P02666A2) into one canonical protein,
or simply rename one. Resolve any combined (multi-protein) peptides above first: merges here are
applied last and take precedence.
Merge all data, calculate group averages, and extract bioactive peptides.