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LabWits
Assay Analysis & Quality Control

Percent Viability and Percent Inhibition Calculator

Normalize and interpret cell viability, cytotoxicity, and inhibition assay data using background subtraction and experimental controls. Generate clear results tables, assay quality metrics, and professional visualizations from CellTiter-Glo, MTT, alamarBlue, reporter, antiviral, and related plate-based assays.

Percent Viability and Percent Inhibition Calculator

Assay Setup

Control Replicate Inputs

Paste raw replicate values directly from Excel/Sheets, one per line or separated by commas or tabs.

Optional. If empty, blank mean is treated as 0.
Defines the 100% viability reference.
Required only for Min-Max Control.

Sample Table

Enter raw assay signals for each sample or replicate group.

Results

Results Table

Calculated viability and inhibition rows will appear here.

Assay Quality Panel

Control separation, background-subtracted signals, and quality notes will appear here.

Graph

Bars show calculated sample means with approximate replicate SD error bars.

Visualization placeholder

Export

Formula and Calculation Logic

This calculator starts with raw replicate signals from plate-based assays and calculates mean, sample SD, replicate count, blank-corrected mean, percent viability, and percent inhibition. Media-only blanks are optional, but when provided they help remove background from media, reagent, plate, or instrument signal.

Corrected signal = raw signal - blank mean
Percent viability = corrected sample mean / corrected vehicle control mean x 100
Percent inhibition = 100 - percent viability
Min-max viability = (corrected sample mean - corrected positive control mean) / (corrected vehicle control mean - corrected positive control mean) x 100

Use Simple Control normalization for quick viability or inhibition assays where the vehicle or untreated condition is the main 100% reference. Use Min-Max Control normalization for screening assays that include both a high-signal reference and a low-signal positive or max-inhibition control.

SD is calculated from the raw replicate signals for each row. Graph error bars are approximate normalized replicate SD, not full propagated uncertainty. Values above 100% viability or below 0% inhibition can be biologically real, but they can also point to control selection, background correction, or plate variability issues.

Example Workflow

A scientist runs a viability or inhibition assay, collects raw plate-reader measurements, and pastes replicate values into the calculator. The calculator performs background correction, normalization, quality assessment, graph generation, and export-ready reporting.

1

Prepare controls

Include media-only blanks, vehicle or untreated controls, treated samples, and optional positive/max inhibition controls.

2

Paste raw measurements

Paste replicate values directly from Excel or Sheets. The calculator accepts line breaks, commas, and tab-separated values.

3

Review normalized results

Generate percent viability, percent inhibition, assay quality metrics, graphs, and export-ready summaries.

Condition Example raw replicate values Interpretation
Blank 100, 120, 110 Background signal to subtract.
Vehicle 10000, 9800, 10200 Defines the 100% viability reference.
Compound A 8000, 7900, 8100 About 80% viability / 20% inhibition.
Compound B 2000, 2100, 1900 About 19% viability / 81% inhibition.

Common Mistakes

Forgetting to subtract background signal

Media-only or reagent background can inflate every signal. Paste blank replicates when background is meaningful for the assay.

Using the wrong control condition

The vehicle or untreated condition defines 100% viability. A media-only blank is background, not a biological reference; for compound treatment, the vehicle control is often the right reference.

Mixing raw and corrected values

Paste raw replicate values into the calculator. Do not mix raw sample values with blank-corrected control values.

Treating >100% viability as automatically wrong

Signals above the vehicle control can happen, but they should prompt a check of controls, background, and biology.

Using min-max mode with a weak positive control

Min-max normalization depends on clear separation between vehicle and positive or max-inhibition controls.

Comparing results from weak dynamic range assays

If the positive control barely separates from vehicle, normalized inhibition values may look precise but be hard to trust.

Assuming viability assays directly measure cell number

CellTiter-Glo, MTT, and alamarBlue measure metabolic or reagent-based proxy signals, not direct cell counts or mechanism.

Ignoring replicate variability and outlier wells

Large SD or one obvious outlier well can change the interpretation. Review replicate spread and plate issues before reporting results.

Frequently Asked Questions

What is percent viability?

Percent viability is the sample signal normalized to a reference control, usually vehicle or untreated cells, where the reference is treated as 100%.

What is percent inhibition, and how is it related to percent viability?

Percent inhibition describes how much the sample reduces signal relative to the viability reference. In this workflow, it is calculated as 100 minus percent viability, so 80% viability corresponds to 20% inhibition.

Do I need a media-only blank?

No. If the blank field is empty, the calculator uses a blank mean of 0. Add media-only blanks when background signal is meaningful.

What is the vehicle or untreated control?

It is the condition used as the 100% viability reference, such as DMSO-only wells for a compound screen or untreated cells for a basic comparison.

When should I use simple control normalization vs. min-max normalization?

Use Simple Control when the vehicle or untreated control is the main reference. Use Min-Max Control when the assay includes both a high-signal vehicle control and a positive or max-inhibition control that defines the low-signal reference.

Why is my viability above 100% or my inhibition below 0%?

The sample signal may be higher than the reference control, which can be biologically real or reflect control/background issues. Review replicate spread, blank correction, and whether the reference condition is appropriate.

Can this calculator be used for CellTiter-Glo, MTT, and alamarBlue assays?

Yes. Paste raw numeric plate-reader signals from these assays and normalize them to appropriate controls. Remember that these assays measure proxy signals such as luminescence, absorbance, fluorescence, or metabolism, not direct cell counts.

Is this the same as an IC50 calculator, and what do the graph error bars represent?

No. This calculator normalizes assay data at individual conditions; it does not fit a dose-response curve or calculate IC50. Graph error bars show approximate normalized replicate SD as a visual guide, not full uncertainty propagation.