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  • Overview
  • Use Cases
  • Settings
  • Interface
  • Qualitative Analysis
  1. Widgets
  2. Section Widgets
  3. Biology
  4. Assay

ELISA Qualitative

Streamline qualitative ELISA analysis for a single 96-well plate

Overview

ELISA Qualitative is a type of enzyme-linked immunosorbent assay (ELISA) that determines whether a specific substance, such as an antigen or antibody, is present in a sample, rather than measuring its exact concentration.

The Labii ELISA Qualitative widget is a powerful tool designed to streamline qualitative ELISA analysis for a single 96-well plate. It allows users to input the ELISA layout, enter raw data, and perform a one-click analysis to determine the presence or absence of a target analyte. The results are automatically processed and displayed within the widget, providing a seamless and efficient workflow.

This widget simplifies ELISA data handling, ensuring accurate and rapid analysis.

Use Cases

  • Perform ELISA Qualitative analysis

Settings

Users can customize the analysis parameters to tailor the ELISA Qualitative analysis to their needs.

  • Optical Density (OD) - Default to 450nM

  • NC Validation - Validation for Negative Control (NC) wells.

  • PC Validation - Validation for Positive Control (PC) wells.

  • Cutoff - Cutoff formula for qualitative analysis.

Interface

The interface will present a 96-well ELISA layout, displaying the input data, analysis results, and prediction outcomes in the same 96-well format for easy interpretation.

Qualitative Analysis

Labii perform the following 6 steps for the ELISA qualitative analysis:

Step 1: Generate the average absorbance of the Negative Control (NC)

The Mean NC (Negative Control) absorbance is calculated by averaging the absorbance values of the NC wells.

The Standard Deviation (SD) of NC is also computed

Step 2: Generate the average absorbance of the Positive Control (PC)

The Mean PC (Positive Control) absorbance is calculated similarly by averaging the absorbance values of the PC wells.

The Standard Deviation (SD) of PC is also computed

Step 3: Validate the Negative Control (NC)

Based on the selected NC Validation parameter, the widget will perform Negative Control validation. If no validation method is specified, this step will be automatically skipped.

Step 4: Validate the Positive Control (PC)

Based on the selected PC Validation parameter, the widget will perform Positive Control validation. If no validation method is specified, this step will be automatically skipped.

Step 5: Generate the Cutoff Value

The cutoff value is determined using the selected cutoff method specified in the parameters. By default, the cutoff is set to the NC mean absorbance.

Step 6: Calculate the Classification Result

In this step, each sample’s absorbance value is compared against the calculated cutoff.

Any sample with absorbance greater than or equal to the cutoff is classified as positive, while those below are classified as negative.

The final classification results are displayed in the same layout.

This step-by-step process ensures a robust and automated ELISA qualitative analysis workflow.

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Last updated 2 months ago