“Strategies for design of protein biomarker studies” This white paper describes important aspects of study design to consider when planning your future research. These include a well-defined study objective, adequate sample size, control of confounding factors and biases and appropriate statistical analysis. All procedures relevant to biomarker studies are covered, from initial planning, through sample collection and analysis to the final report. With the help of these guidelines, you can plan your studies to improve the chances of a successful outcome.
“Data normalization and standardization” This white paper describes how Olink data is processed and normalized to rapidly and reliably generate the easily understandable output from an Olink study. The topics covered include Olink’s built-in Quality Control system and a full description of how our Normalized Protein eXpression (NPX) values for relative quantification are calculated. The different normalization methods that can be used to optimize the output from often large and complex projects are also described in detail.
“Pre-analytical variation in protein biomarker research” This white paper considers some of the factors to consider when collecting, storing and handling human blood samples for use in protein biomarker studies. This article will discuss that while proteins are more sensitive than DNA in terms of potential pre-analytical factors, taking some basic precautions and documenting your sample-handling procedures should result in a successful outcome. The white paper draws on both the published literature and Olink’s experience in analyzing hundreds of thousands of samples over the past few years.