Cookies on this website
We use cookies to ensure that we give you the best experience on our website. If you click 'Continue' we'll assume that you are happy to receive all cookies and you won't see this message again. Click 'Find out more' for information on how to change your cookie settings.

<jats:p>Recent advances in protein labelling-gene tagging with CRIPSR-Cas9-have made it possible to label proteins of interest endogenously. This represents a major breakthrough in the field of quantitative microscopy, especially when quantifying protein-protein interactions. This is because over-expression of labelled proteins may cause a distortion in localization, function and perhaps artificially force protein-protein interactions due to crowding effects. A microscopy technique that is particularly well suited to detect protein interactions with low photon budgets is number and brightness (N&amp;B). Detrending (removal of global trends in data) is a necessary pre-processing step to N&amp;B calculations, but all current detrending methods perform poorly at low intensities. Here, we present the Robin Hood automatic detrending algorithm which performs well at low intensities, evaluating it with simulated and low photon budget live cell images. RH is available as an ImageJ plugin and as an R package.</jats:p>

Original publication

DOI

10.1101/667824

Type

Journal article

Publisher

Cold Spring Harbor Laboratory

Publication Date

15/06/2019