YSI Processor Live

Replicate QC and statistics for YSI 2950 BioSample exports

→ Open the live app

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What is YSI Processor?

YSI Processor is a live web app for analyzing YSI 2950 BioSample exports directly in the browser. Upload one or more raw BioSample*.csv files and get:

• replicate groups with mean, SD, and CV per well and analyte
• automated outlier detection with discard recommendations
• a pivot table with one row per well and one column group per analyte
• CSV exports ready for reports or downstream analysis

It is designed for routine metabolite review in CHO and other mammalian cell culture workflows, particularly when glucose, lactate, glutamine, and glutamate readings drive feeding decisions or process tracking.

Everything runs locally in the browser. No data leaves your machine.

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Why it matters

YSI 2950 workflows typically involve repetitive manual review after each session:

• exporting raw CSVs and opening them in spreadsheets
• checking whether replicates from different plate sequences belong to the same sample
• calculating mean, SD, and CV by hand
• guessing which replicate caused a high CV
• reformatting everything for downstream reports

YSI Processor reduces that friction to a single CSV drop. The core question it answers is:

Can I trust this reading, and if not, which replicate should I re-inspect?

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How it works

1. Replicate grouping

Rows are grouped by BatchName + WellId + ChemistryId. This means all measurements of the same physical well across multiple plate sequences within the same batch are treated as replicates of the same sample — which is the correct behavior when running the same samples through multiple YSI plate sequences (e.g. routine run + MCR mid-cycle run).

PlateSequenceName is preserved as metadata and shown in the results table under Plates, but it does not fragment the replicate groups.

2. Outlier detection

Three independent tests run on each replicate group (minimum 3 replicates required):

Test	Logic
Modified Z-Score	Uses median and MAD — robust to non-normal distributions. Flags if |0.6745 × (value − median) / MAD| exceeds the threshold.
IQR Fence	Flags values outside Q1 − k × IQR or Q3 + k × IQR.
Leave-One-Out CV	Tests whether removing each replicate reduces group CV below threshold. Only the candidate that gives the greatest improvement is flagged.

A replicate is recommended for discard when it accumulates at least N flags (configurable via Consensus signals). When multiple replicates qualify, the one with the highest flag score, then best CV improvement, then largest deviation from the median is chosen.

3. Status labels

Each well+analyte group receives one of four statuses:

Status	Meaning
PASS	CV below threshold, no flags
CLEANED	Outlier discarded; cleaned CV now passes
REVIEW	CV above threshold but no single outlier identified
FAIL	CV above threshold even after removing the worst replicate

4. Results pivot table

The Results panel shows one row per well with column groups per analyte (Glucose, Lactate, Glutamine, Glutamate). Each group displays:

• Mean — cleaned mean after recommended discard
• SD — cleaned standard deviation
• CV% — highlighted in red if above threshold
• Status — color-coded badge

Rows with FAIL or REVIEW status appear first. The table can be copied for direct pasting into Excel.

5. Exports

File	Contents
ysi_summary.csv	One row per replicate group with raw and cleaned statistics
ysi_measurements_annotated.csv	Replicate-level QC detail with all flag scores
ysi_outliers.csv	Only the rows that triggered review or discard
ysi_file_manifest.csv	Metadata summary of the uploaded files

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How to use it

Option 1 — Live app (recommended)

Open ebalderasr.github.io/ysi-processor in any modern browser.

1. Set QC thresholds if needed (CV%, Modified Z, IQR multiplier, Consensus signals)
2. Drop one or more BioSample*.csv files onto the dropzone
3. Click Process Files
4. Review the KPI strip, Results pivot table, Variability Snapshot chart, and Flagged Replicates table
5. Copy the pivot table for Excel or download individual CSV exports

No installation required. Files are processed entirely in your browser session.

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Option 2 — Python CLI (local, batch processing)

The ysi_toolkit package provides a full Python backend with the same analysis logic. Useful for batch processing, integration into pipelines, or running from scripts.

Requirements

pip install -r requirements.txt

requirements.txt:

pandas
numpy
matplotlib

Basic usage

Place your BioSample*.csv files in a directory and run:

python ysi_processor.py --input ./data --output ./results

All options

--input            Directory with BioSample*.csv files  (default: current dir)
--output           Directory for output files            (default: current dir)
--cv               CV threshold for review               (default: 5.0)
--modified-z       Modified z-score threshold            (default: 3.5)
--iqr-multiplier   IQR fence multiplier                  (default: 1.5)
--consensus-min-flags  Minimum flags to recommend discard (default: 1)
--title            HTML report title
--verbose          Enable debug logging

Example

python ysi_processor.py \
  --input ./20260317-T2 \
  --output ./results \
  --cv 5.0 \
  --modified-z 3.5 \
  --verbose

Outputs written to --output

results/
├── ysi_summary.csv
├── ysi_measurements_annotated.csv
├── ysi_outliers.csv
├── ysi_file_manifest.csv
├── ysi_quality_report.html
├── ysi_cv_overview.png
└── ysi_flagged_replicates.png

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Input format

Required columns

Column	Accepted aliases	Description
PlateSequenceName	PlateName, PlateID	Plate run identifier
BatchName	Batch, BatchID	Experiment batch name
WellId	WellID, Well, Position	Sample position
ChemistryId	ChemistryID, Chemistry, Analyte	Analyte name
Concentration	Result, Value	Measured value

Optional columns

Column	Accepted aliases	Use
CompletionState	Status, ResultState	If present, only Complete rows are used
Units	Unit, MeasurementUnits	Displayed in analyte column headers
LocalCompletionTime	DateTime, Timestamp	Included in exports
Errors	Error, ErrorMessage	Included in manifest
SampleSequenceName	SampleName, SampleId	Included in summary

Typical YSI 2950 export header

PlateSequenceName, BatchName, LocalCompletionTime, CompletionState,
WellId, ChemistryId, ProbeId, Concentration, Units, Endpoint,
SampleSize, InitialBaseline, Plateau, FinalBaseline, NetPlateau,
NetPlateauTempAdj, CrossNetPlateau, CrossNetPlateauTempAdj,
PlateauSlope, Temperature, Errors

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Features

No installation	Runs fully client-side — no Python, no pip, no server
Multi-file support	Load several plate sequences in one session
Cross-plate replicate grouping	Groups by Batch + Well + Analyte; plate sequences merged correctly
Three-method outlier detection	Modified Z-Score · IQR Fence · Leave-One-Out CV
Pivot results table	One row per well, column groups per analyte with units
Status badges	PASS · CLEANED · REVIEW · FAIL with color-coded rows
CV chart	Variability snapshot for the top 20 wells
Copy for Excel	Pivot table copied as tab-separated text
Four CSV exports	Summary · Measurements · Outliers · Manifest
Python CLI	Same analysis engine available as a local command-line tool

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Project structure

ysi-processor/
├── index.html              ← GitHub Pages entry point
├── assets/
│   ├── app.js              ← in-browser parser, analysis, rendering, export
│   └── styles.css          ← live app styles
├── ysi_toolkit/            ← Python analysis engine
│   ├── analysis.py         ← replicate grouping, outlier detection, summary
│   ├── pipeline.py         ← batch processing pipeline
│   ├── cli.py              ← command-line interface
│   ├── config.py           ← ProcessingConfig dataclass
│   ├── io.py               ← CSV reading and output writing
│   └── reporting.py        ← HTML report and chart generation
├── ysi_processor.py        ← CLI entry point
├── requirements.txt
├── demo_input/             ← sample input files
└── demo_output/            ← sample output files

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Author

Emiliano Balderas Ramírez Bioengineer · PhD Candidate in Biochemical Sciences Instituto de Biotecnología (IBt), UNAM

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Related — Host Cell Lab Suite

PulseGrowth — growth kinetics and process timing for mammalian cell culture.

Clonalyzer 2 — fed-batch kinetics analysis for CHO cell cultures.

CellSplit — passage planning and split calculations for adherent cell culture.

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YSI Processor — drop your BioSample CSV, get your replicate QC.