Explore results, follow links and export tables

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Open the report or start the explorer

The report and explorer serve different purposes. MP_run_report.html provides accounting and navigation to results/logs. EDA_portal.html queries the SQLite index so you can search, filter, follow related records and export CSVs. The explorer requires its local Python server; double-clicking the explorer HTML alone does not start that server.

After a completed workflow:

metapathways report -o /path/to/analysis --serve --no-rebuild

Keep the terminal open. MP prints a local address and normally opens your browser. Ctrl-C stops the server. To refresh the index after results change, omit --no-rebuild. Report generation reads existing output; it does not rerun annotation or infer missing pathways.

Use the parent directory containing sample folders to combine samples in one report. Using a single sample directory limits that report to the sample. Report files live under the selected root’s reports/ directory.

View a remote report through SSH

On the remote server, activate the MP environment and run:

metapathways report -o /remote/path/to/analysis \
  --serve --no-rebuild --no-browser --port 8765

On your local computer, in a second terminal, replacing user@server with the same SSH destination you normally use:

ssh -N -L 8765:127.0.0.1:8765 user@server

The tunnel command may appear idle; that is normal. Leave both terminals running. Open these addresses in your local browser:

• Explorer: http://localhost:8765/reports/EDA_portal.html

• Run report: http://localhost:8765/reports/MP_run_report.html

-L forwards the local port to the server’s loopback port, and -N asks SSH to provide forwarding without a remote shell. Use your site’s SSH host alias or jump-host configuration when required. MP listens only on loopback; you do not need to expose the server publicly or open a firewall port.

If local port 8765 is busy, forward another local port with -L 8766:127.0.0.1:8765, then browse to localhost:8766. If the remote port is busy, choose a different --port and update the tunnel’s destination port too. A page that loads but cannot query may be an old static copy or an HTML file opened without the server.

Start with accounting

Open the run report before interpreting tables. Review which samples and products were found, source/import notes, and task execution records. Optional MAG failures can coexist with overall workflow success. A file from an earlier successful attempt can coexist with a failed newer attempt; output availability and latest task status answer different questions.

Check a few known sample IDs and original contig IDs. If expected tables are empty, inspect the inventory and task logs before interpreting zeros. Missing output does not mean the organism lacks a function.

Follow one annotation through the results

1. Choose ORFs and taxonomy and filter to a sample.

2. Search for an ORF ID or product term you recognize.

3. Follow its related annotation records to inspect database accessions and EC/reaction assignments.

4. Follow pathway associations, keeping both sample and entity IDs selected.

5. Export the filtered table with identifying columns included.

A primary ORF annotation is not identical to all database hits. Functional annotations retains reference records; a gene can have more than one. Pathway genes contains pathway/ORF associations, so a gene in several pathways appears several times. The schema describes each row unit and join key.

Select useful subsets

Question	Starting table and filters
Which SwissProt annotations mention kinase in this sample?	Functional annotations: sample, reference database, product text
Which genes support a particular MAG pathway?	Pathways: sample, entity, pathway ID; follow Pathway genes
What are all reported genes on contigs assigned to a MAG?	MAG ORFs: sample and entity
Which genes were supplied to MAG pathway inference?	MAG input genes: sample and entity
What abundance measurements exist for an ORF?	Abundance: sample, feature type, feature ID, measurement
Where is the raw GFF, RNA output, BAM or PGDB archive?	File inventory / run-report output links

MAG ORFs uses the full contig map. MAG input genes is the smaller set selected for Pathway Tools; it is not the total gene content of the bin. Similarly, input genome-bin counts need not equal successful PGDB counts.

The portal provides text searches and column/related-result filters, not biological plotting. Choose the columns needed for downstream work and export all matching rows as CSV. Pagination limits what is displayed, not the full filtered export. Retain the query definition or bookmarked URL and record the report snapshot used for an analysis.

Avoid accidental double counting

Always keep sample_id. Keep entity_id for pathways and genome results. The same ORF-looking identifier can occur in different samples, and the same pathway can occur in the community and many bins.

Do not sum abundance after joining each gene to all its annotations and all its pathways: many-to-many joins multiply rows. Decide whether you need unique genes, annotation records or pathway associations before aggregating. Pathway scores are reported inference values, not universal probabilities of biological truth. See safe SQL examples.

Share or archive a result

Filtered CSVs can be shared independently. To retain the explorer and original-file navigation, preserve the complete output root, including its reports/, sample results and logs, and serve it with a compatible MP installation. results.sqlite and schema.json also support direct read-only analysis in Python/R/SQLite.

Not every raw product becomes a relational table: the inventory links additional sequences, alignments, RNA reports and PGDB products. Import notes identify missing or unsupported sources. The portal does not silently infer missing data, recalculate abundance or validate historical mapping provenance.

Starting at the sample level

A fresh explorer URL opens Samples. Use a sample row’s related-results buttons to inspect its ORFs, then follow annotations, pathways and abundance. Saved query URLs retain their selected table and filters. The footer shows the recorded run version, sample count, command, executor and status when available, plus the report update time and a GitHub link for bug reports and feature requests. For older outputs without a recorded run version, the footer labels the report-builder version instead. Diagnostic details remain available in the Import notes and Execution history tables.