Analysis of antibody data using Finite Mixture Models based on Scale Mixtures of Skew-Normal distributions, 2021, Domingues et al

Preprint.
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Abstract
Finite mixture models have been widely used in antibody (or serological) data analysis in order to help classifying individuals into either antibody-positive or antibody-negative. The most popular models are the so-called Gaussian mixture models which assume a Normal distribution for each component of a mixture. In this work, we propose the use of finite mixture models based on a flexible class of scale mixtures of Skew-Normal distributions for serological data analysis. These distributions are sufficiently flexible to describe right and left asymmetry often observed in the distributions associated with hypothetical antibody-negative and antibody-positive individuals, respectively. We illustrate the advantage of these alternative mixture models with a data set of 406 individuals in which antibodies against six different human herpesviruses were measured in the context of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome."

https://www.medrxiv.org/content/10.1101/2021.03.08.21252807v1

 

The text on the News page includes this:
"In terms of the results concerning the example of application, there is no evidence for a different level of exposure of the patients with ME/CFS to these herpesviruses when compared to healthy controls and patients with multiple sclerosis."

Really just a statistics paperi.e. comparing different statistical methods -- they all give the same result "no evidence for a different level of exposure of the patients with ME/CFS---".

Not the purpose of the paper but the fact that exposure levels are the same doesn't mean there is no role for herpesviruses i.e. since the immune response could be a reason for different outcomes.

Mark Davis, & Ron Davis, were looking at gene which deal with immune response - Sequencing key immune-related genes: HLA and KIR [https://www.omf.ngo/omf-funded-research-t-cells-molecular-immunology/]. - any recent updates?

 

Apologise @Trish - it was a good idea to include it. E.g. it reminded me that I'm not sure how the NIH research award to Ron Davis/Mark Davis worked out/is progressing. Also, it's interesting how it might indicate that the issue is more subtle/complicated than getting an infection - Prusty's Research. I was interested in the skewed distribution tests too!

Thanks