There seem to be Top 10 lists for everything these days so why not have one as well for **Luminex/Bio-Plex® Data Analysis**.

### 1. Use Data Points with at least 35 Bead or Microsphere Counts

35 is the minimum bead count needed for statistically significant analyses. MasterPlex QT Quantitative Analysis software for Luminex/Bio-Plex has a built-in feature for setting thresholds and marking outliers automatically for you based on many parameters including **MFI**, **bead count**, **concentration**, and **standard deviation**.

### 2. Use Weighting to Offset Heteroscedasticity

Heteroscedasticity is a situation that arises in almost all fields, including chemical- and immuno-assays, in which the variance of the dependent variable varies across the data. When dealing with MFI and concentration values, the concentrations usually increase as the MFI increases. When dealing with the high end of the standard curve, it is natural for the concentration values to have a greater variance when compared to the small concentration values on the low end of the standard curve. Many of the regression analyses used in analyzing Luminex data, such as the popular 5PL, **assume equal variance**.

For analyzing Luminex/Bio-Plex data, the **1/Y^2** (preferred) and **1/Y** weighting algorithms are recommended in addition to using the 5-PL model equation.

**1/Y^2**– Minimizes residuals (errors) based on relative MFI values**1/Y**– This algorithm is useful if you know the errors follow a Poisson distribution

MasterPlex QT offers these weighting algorithms in addition to a couple of other options.

### 3. Use the 5 Parameter Logistic (5PL) Nonlinear Regression Model

The **5 Parameter Logistic** or **5PL** nonlinear regression model is an asymmetric function that is ideal for analyzing Luminex immunoassay data. Learn more about the 5PL model equation.

MasterPlex QT offers the 5PL curve-fit regression model in addition to a number of other curve-fitting model equations.

### 4. Run your samples in replicates

Having replicate samples will bring good karma in addition to the following:

**Backups**– If one sample well is accidentally prepared, you will have backups that you can rely on.**Statistics**– Naturally, you will obtain more reliable results when dealing with a larger pool of data. You will also be able to obtain statistics such as %CV and standard deviation that will tell how much variation or dispersion you have amongst data points of the same replicate group.

MasterPlex QT allows you to group your replicate samples and automatically generates the **mean**, **%CV**, and **standard deviation** statistics for the **MFI **and **concentration** values.

### 5. Knock out those standard outliers

One of the simplest ways to identify outliers in your standards is by analyzing the **Residuals** and **% Recovery**.

**Residual**= Calculated Concentration – Expected Concentration**% Recovery**= ( Calculated Concentration / Expected Concentration ) * 100

% Recovery is a better metric to use because it is a relative metric. Obviously, the further the % Recovery deviates from 100%, the higher the probability that the data point is an outlier.

Although there is no strict rule or standard on what the limits are for considering outliers, I tend to mark any standard that has < 50% recovery or > 150% recovery as outliers and that has generated pretty good results.

MasterPlex QT has a user-friendly interface that allows one to view the Residuals, % Recovery, and the Standard Curve all at the same time while being able to mark outliers.

### 6. Use controls

This should go without saying but it is quite alarming for me to see that most of the analysis data files that I see are missing control groups. It should be as important as your background groups. Not only will they tell you if your assay worked but knowing this information is invaluable when it comes time to have to troubleshoot when something goes wrong. As you may already know, the workflow for the Luminex/Bio-Plex technology can become quite complicated and there are many opportunities for things to go awry. Having control groups will keep you sane.

### 7. Use a sufficient standard curve range for your unknowns

Extrapolation is the process of inferring or estimating the concentrations for points that are within calculable limits but outside of the standard curve range. Extrapolations are often less meaningful especially when the values lie on the flatter parts of the curve. Please read this blog post for more on the dangers of extrapolating data.

There are several ways to avoid extrapolating data:

- If your unknown MFI is
**above the standard curve range**, you can dilute the unknown sample enough to bring it back within range and just take the dilution factor into account when calculating your concentrations. MasterPlex QTallows you to input the dilution factors of your unknown samples and it will automatically take them into account when calculating the concentrations. - If your unknown MFI is
**below the standard curve range**, you can create one or more standard groups on the lower end by extending your serial dilutions.

### 8. Individual Standard Points vs. Mean of each Standard Replicate Group

Generally speaking, the more standard points you have (using individual standard points for the curve fit), the better the curve fit because you will have a greater number of degrees of freedom. This method will be more sensitive to outliers though so it is recommended that you first knock out any outliers that you might have and proceed with the standard calculations.

Using the mean of each standard replicate group will lead to less data points and that in turn will lead to a worse curve fit. This method is less susceptible to outliers though if you do not intend to mark them.

Unlike some of the Luminex data analysis packages that are out there, MasterPlex QT let’s the user choose between both these methods.

### 9. Use the R-PE Reporter Dye for Best Signal

R-phycoerythrin (R-PE) is the primary reporter molecule used in Luminex/Bio-Plex assays. Out of all the reporter dyes tested with the Luminex xMAP platform, R-PE will output the highest signals. Alexa 532 is second to R-PE but it’s relative fluorescence intensity is **only 28% **that of R-PE.

### 10. Keep it in the Linear Range

Depending on what is coupled to your beads, the maximum MFI values that can be reported will generally top out between 20000-30000 MFI. You definitely do not want to be interpolating or extrapolating any concentration values near the top of this curve where it is flat. In general, it is best to keep all your MFI values between 0-10000 MFI where it is more linear.

If you found this post useful, you may also be interested in the **10 Tips for MasterPlex QT v4.0 Power Users** blog post.

Try **MasterPlex QT** Desktop – The World’s First Multiplex Curve-Fitting, quality control and reporting desktop software for multiplex ELISA data (Luminex 100 / 200 / xMAP, Bio-Plex, Meso Scale Discovery and Applied BioCode platforms)

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Bio-Plex® is a registered trademark of Bio-Rad Laboratories, Inc.

Hi, do you know any literature/publication that may support the idea that “35 is the minimum bead count needed for statistically significant analyses”? We sometimes run into “insufficent beads count” issues. It would be great if we can justfy that the samples with 35-100 beads count are still reliable.

Hi Min Shi,

The 35 minimum bead count was something that everyone is told during the Luminex trainings but we never received any supporting documentation on it. I recently talked with a Luminex tech support person who did a lot of digging and told me that Luminex did in fact hire some statisticians to do the study around 1999 and they came up with that number. The reason why this study was never published was because the instrumentation was changed. I was told that the changes were not really significant but, to play it safe, Luminex decided not to publish.

I hope this helps.

Is the bead count only counting the beads that are bound with the target and the detection antibodies? Or is it the total bead count in the well that has the bound and the unbound beads?

Thanks.

Hi,

That is a very good question. It is for the specific bead count of beads that are bound with the target and corresponding detection antibodies.

Allen

We set our minimum bead count to 100, yet still get MFI values so low that they do not fall within our standard curve. Why is that? Should we be acquiring bead counts >100?

Hi Nichole,

It looks like you are acquiring enough beads; 100 beads is usually what we recommend to our customers. There could be other things that is causing the low readings. First, instrument issues, you may have an instrument that lost it’s sensitivity. In that case, you many need to work with the instrument maker to see if they can perform a maintenance. Second, the assay kit and assay procedure, there maybe something specific to your assay kit that could be giving off a low MFI. Make sure you have follow the recommended procedures in the kit to run your analysis. If the procedure was performed correctly, then you may need to contact the assay maker to confirm the quality of the kit.

I hope this was helpful.

Thanks,

Charles Ma

Senior Technical Support

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