Nandb-number and brightness in R with a novel automatic detrending algorithm.

Rory Nolan,Maro Iliopoulou,Jonathan Elegheert,G Maria Jakobsdottir,Marina Rodriguez-Muñoz,A Radu Aricescu,Sergi Padilla-Parra,Luis A J Alvarez

doi:10.1093/bioinformatics/btx434

Abstract

SummaryAn R package for performing number and brightness image analysis, with the implementation of a novel automatic detrending algorithm.Availability and implementationAvailable at https://github.com/rorynolan/nandb for all platforms.Contact rnolan@well.ox.ac.uk or spadilla@well.ox.ac.ukSupplementary information Supplementary data are available at Bioinformatics online.

Highlights

"Number and brightness" (N&B) [Digman et al (2008)] is a fluorescence fluctuation spectroscopy technique to measure the average number and oligomeric state of mobile molecules in each pixel of an image
Define an entity as a set of molecules which are chemically bound and the brightness of an entity as the average number of photon detector counts it gives per unit time when in the illumination volume
Is the "apparent brightness", ݊ is the average number of entities and ܰ is the "apparent number." The brightness ߳ of an entity is directly proportional to its oligomeric state

Summary

Introduction

"Number and brightness" (N&B) [Digman et al (2008)] is a fluorescence fluctuation spectroscopy technique to measure the average number and oligomeric state of mobile (freely diffusing) molecules in each pixel of an image. Is the "apparent brightness", ݊ is the average number of entities and ܰ is the "apparent number." The brightness ߳ of an entity is directly proportional to its oligomeric state. This is because a dimer will have twice as much fluorescent protein as a monomer, it will give twice as many detector counts per unit time (and so on). In this way, it is possible to directly relate changes in brightness to changes in oligomeric state. The package implements novel features such as automatic detrending of image series (to correct for bleaching), creation of N&B videos (time-series of N&B images) and functions to perform N&B analyses in high-throughput (on many files in parallel)

Regions of Interest

Detrending

Number and Brightness

Findings

FKBP12