spotgear: spotgear: *S*ubset *P*rofiling and *O*rganizing *T*ools for...

In oslerinhealth/spotgear: Subset Profiling and Organizing Tools for Gel Electrophoresis Autoradiography in R

Description

An R Package for Fitting Bayesian Two-Dimensional Image Dewarping Models and Estimating Disease Subsets and Signatures

Details

Autoimmune diseases, e.g., scleroderma, are human immune system’s responses to autoantigens in which the body produces specific autoantibodies that target these autoantigens but also cause tissue damage. The autoantibody composition is strikingly different among patients, as indicated by the many different radiolabeled patterns obtained from the mass-spectrometry-based technology - gel electrophoresis autoradiograms (GEA). Human recognition of patterns is not optimal when the patterns are composite/complex, or patterns are scattered across a large number of sam- ples. However, multiple sources of error (including irrelevant intensity differences across gels and warping of the gels) have traditionally precluded automation of pattern discovery using autoradiograms. In this package, we overcome these limitations by novel initial gel data preprocessing (Bayesian two dimensional image dewarping/registration) and then provide methods to

spotgear functions

dewarp2d

See Also

• https://github.com/zhenkewu/spotgear for the source code and system/software requirements to use spotgear for your data.

oslerinhealth/spotgear documentation built on May 25, 2021, 10:38 p.m.