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Input preparation

HexNAcQuest tutorial

Prepare one CSV row per spectrum for GlcNAc or GalNAc classification.

Required CSV format

The CSV must include id plus summed intensities for the characteristic fragments at m/z 126, 138, 144, 168, and 186. Use the exact headers f126, f138, f144, f168, and f186.

id,f126,f138,f144,f168,f186
scan_101,37564.4248,27138.75293,32261.40771,15646.51221,20015.9458

Download example CSV

On the analysis page, Load example opens this CSV directly for preview. Prediction starts only when you choose Run prediction.

Individual raw files

  1. Convert vendor RAW data to mzML, for example with ProteoWizard.
  2. Extract oxonium-ion spectrum intensities with a suitable local workflow.
  3. Remove spectra showing larger-glycan oxonium ions at m/z 274, 292, 366, or 372 when appropriate for your protocol.
  4. Save the six required columns as CSV and open Analysis.

Multiple files or enriched samples

MSConvertGUI settings for conversion to mzMLOpen full-size conversion example ↗

1. Convert data

Select the raw file and output folder, choose mzML, and start conversion. You may first create a scan-number list from peptide-spectrum matches to restrict extraction.

Example scan-number worksheet filtered for HexNAc modificationOpen full-size worksheet ↗

2. Select spectra

If using a scan filter, place the scan number in the first worksheet column and retain HexNAc-modified peptide-spectrum matches.

Example R code for extracting characteristic fragment intensitiesOpen full-size extraction code ↗

3. Sum characteristic peaks

For each selected spectrum, sum signal in the chosen tolerance around m/z 126, 138, 144, 168, and 186. Apply the larger-glycan filters required by your experiment.

Example HexNAcQuest input CSVOpen full-size CSV example ↗

4. Export CSV

Put the scan identifier in id, retain the five required intensity columns, and export a comma-separated file.

Analysis in your browser
  1. Choose your CSVSix required columns
  2. Review the previewInspect intensities and skipped-row reasons
  3. Run predictionClassify every valid row on your device

5. Analyze

Select the CSV on the analysis page. Review the valid-row preview and any skipped-row reasons before choosing Run prediction.

Select a preview row to see its five fragment intensities. The preview includes up to 500 valid rows; prediction includes every valid row.

From prediction to CSV
  1. Check the summaryPredicted, skipped, GlcNAc, and GalNAc counts
  2. Review the resultsClassification beside each original row
  3. Download all resultsyour_file_Predicted_results.csv

6. Save results

Review the GlcNAc/GalNAc summary and choose Download all results. The CSV adds a pred_outcome column before the original six input columns.

The original intensity text and row order are preserved for valid rows. Skipped rows are excluded from the prediction download; their reasons remain on the analysis page.