Using Tesorai Trove

Trove is Tesorai’s searchable catalogue of curated public proteomics studies. Find a study relevant to your question, inspect its data and sample metadata, then open it in Chat to run your own analysis. You do not need to upload raw data to get started.

Trove contains a curated subset of studies from public proteomics repositories. Check each study’s organism and biological material, including whether it uses tissue, biofluid, or cell-line samples. A dataset found in a publication or recommended by Chat may not yet be available in Trove.

1. Find a study

Select Trove in the platform navigation to open the catalogue.

Use the search and filters to narrow the results:

• Search matches dataset IDs, titles, authors, and keywords.
• Disease, Tissue, and Year help you find relevant studies.
• Sort by changes the order of the results.
• Clear all filters resets your search.

The result count updates as you filter. Use the pagination controls and Rows per page selector to browse the matches.

Each dataset card summarizes the study, including its title, disease and tissue, accession and year, sample and patient counts, and data completeness. Click a card to inspect its details; use its checkbox to select it for analysis.

2. Check the study and sample metadata

Open the Dataset details panel to review the study description, authors, accession, and available metadata.

Before deciding on a comparison, check:

• Biological material: Is the tissue or biofluid relevant to your question?
• Sample groups: Are the conditions, controls, and sample assignments clear?
• Replication: How many independent participants or biological samples support each group? Sample counts and patient counts can differ.
• Study design: Are measurements paired, fractionated, repeated over time, or collected in different batches?
• Analysis inputs: Are the abundance data and metadata needed for your question available?

Some information may require consulting the original publication or repository record. If an assignment is missing or ambiguous, resolve it before running a comparison.

Data completeness

In the dataset details panel, hover over the info icon next to Data completeness to see which components are available:

Tooltip item	What to check
Patient-metadata	Information describing the participants or biological sources and their relevant characteristics.
Sample-patient mapping	The link between measured samples and their participants or biological sources.
Sample-protein matrix	Protein measurements organized by sample.

The tooltip uses checkmarks to indicate available components. Read this checklist alongside the completeness label, such as Medium or Needs review. A dataset can show all three checkmarks and still be labeled Needs review; the checkmarks alone do not confirm that its metadata or sample assignments have been validated.

Before comparing groups, confirm that sample identifiers in the protein matrix match the metadata and mapping, and that the grouping needed for your question is clear.

3. Understand where the protein data came from

Trove datasets include a protein matrix for analysis. This often comes from the original publication or repository deposit. Where a study has been reprocessed with Tesorai Search, its protein data may instead come from that reprocessing. Check Data source and status in the dataset details.

Data source	What it means for your analysis
Author-provided results	You are analyzing processed data from the original study. Its search, quantification, and preprocessing choices affect the values available.
Tesorai-generated results	You are analyzing results from Tesorai reprocessing. These may differ from the original publication’s results.

Analysis and reprocessing are different

Opening a study in Chat analyzes its available processed data. It does not automatically rerun the raw mass spectrometry files through Tesorai Search.

Use Request re-process, where available, to request Tesorai Search reprocessing. This is a request for a different processing source, not an indication that the study has no protein matrix.

Before applying normalization or log transformation, check whether those steps have already been applied to the selected matrix.

4. Add datasets to Data or analyze in Chat

1. Select the checkboxes on the dataset cards you want to use. You can select up to 10 datasets.
2. Review the accessions and selection count in the footer.
3. Choose Add to Data to add the selected datasets to Data, or Analyze in Chat to begin analyzing them in Chat.

You can also use the Show in Data toggle in a dataset’s details panel to control whether it appears in Data.

The footer shows your selected accessions. Use an accession to reopen its details, or Clear selection to start again. Keep your selection within the 10-dataset limit.

In Chat, choose an analysis template or type your own question. Start by confirming the data and sample assignments, for example:

Summarize this study’s protein matrix and available sample metadata. Identify the experimental groups, abundance scale, and missing information. Confirm which samples support a disease-versus-control comparison before running statistics.

Then explore data quality, compare groups, inspect individual proteins, or investigate pathways. See the Chat quickstart for the full workflow, including reviewing code and exporting results.

5. Compare evidence with other data

To investigate whether a finding also appears in a public study, save the relevant analysis of your own data to Data, then bring those files and the Trove data into Chat. Identify each source and explain the comparison you want to make.

For example:

Compare the direction of change for the proteins in my saved results with this Trove study. First check protein identifiers, sample groups, and the meaning of the abundance values. Report shared, conflicting, and unavailable evidence separately.

Choose comparisons that fit the inputs. Differences in tissue, sample preparation, acquisition, quantification, and study design can affect the results. Check compatibility before combining abundance values across studies; comparing effect directions or pathway findings may be more appropriate.

Cite the original study

When using Trove data in a report or publication, cite the original study and repository accession. Also describe the data source used, any Tesorai reprocessing, and the analysis you performed. A new Chat analysis may use different methods or sample selections from the original publication.

Request a study or report a problem

Use Request a new dataset to suggest a study missing from the catalogue. Include the repository accession and publication details when available.

For metadata corrections or help, email info@tesorai.com with the dataset accession and the issue you found.

Chat analyses of Trove data use your shared platform credit balance. See Plans and Credits for details.