Median filter algorithm for estimating the threshold of detection on custom protein arrays
Author(s) -
David Smith,
Susan Kovats,
Terry D. Lee,
Leticia Cano
Publication year - 2006
Publication title -
biotechniques
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 131
eISSN - 1940-9818
pISSN - 0736-6205
DOI - 10.2144/000112204
Subject(s) - smoothing , thresholding , filter (signal processing) , algorithm , signal (programming language) , feature (linguistics) , pattern recognition (psychology) , noise (video) , artificial intelligence , median filter , computer science , mathematics , computer vision , image processing , image (mathematics) , linguistics , philosophy , programming language
We constructed protein arrays according to a titration design to estimate the assay sensitivities over varying concentrations of flu vaccine and human immunoglobulin G (IgG). After imaging, we considered the problem of appropriately distinguishing background noise from foreground signal. We applied the median filter smoothing technique and estimated the differences of the observed signal compared to the smoothed signal. If the absolute value of the difference was large, the feature was easily detectable, indicating that the spot did not blend with its surrounding neighbors. After estimating the residuals, we applied thresholding algorithms to estimate the limits of detection for each assay. At sufficiently large smoothing spans, our median filter approach performed as well or better than visual inspection and two other competing analysis methods. This suggests that a median filter approach has utility in high-throughput arrays where visual inspection is impractical.
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