Method to automatically decode microarray images

Abstract

A method of automatically identifying the microarray chip corners and probes, even if there are no probes at the corners, in a high density and high resolution microarray 5 scanned image having an image space, wherein the method minimizes the error distortions in the image arising in the scanning process by applying to the image a multipass corner finding algorithm comprising: (a) applying a Radon transform to an input microarray image to project the image into an angle and distance space where it is possible to find the orientation of the straight lines; (b) applying a fast Fourier transform to the projected image 10 of (a) to find the optimal tilting angle of the projected image; (c) determining the optimal first and last local maxima for the optimal tilting angle; (d) back projecting the determined first and last local maxima to the image space to find the first approximation of the first and last column lines of the image; (e) rotating the image and repeating steps (a) through (d) to find the first approximation of the top and bottom row lines of the image; (f) determining 15 the first approximation of the four corners of the image from the intersection of the column and row lines; (g) applying a heuristic for determining if the first approximation of step (f) is sufficient; and (h) optionally trimming the scanned image around the first approximation of the four corners and repeating steps (a) through (f).

Description

[0001] Cross References to Related Applications [0002] Applicants claim priority to provisional application Serial No. 60 / 868,129, filed December 1, 2006. technical field [0003] The present invention relates to methods for automatically determining the position of probe spots on microarray images so that the image data can be converted into a measure of biological activity. Background technique [0004] DNA microarray technology is relatively new and is developing rapidly. Currently, it is widely used in systematic studies of global gene expression projects: using microarrays to infer gene function, measuring polymorphisms in gene copy number, and genomic DNA-protein interactions. Extracting data from microarray images has many inherent problems: inconsistent hybridization leads to uneven probe intensities and geometries; placement of the chip into the scanner is not fixed, meaning the corners of the chip can be anywhere ; Scanners often distort the resulting images, a...

AI Technical Summary

Problems solved by technology

Extracting data from microarray images has many inherent problems: inconsistent hybridization leads to uneven probe intensities and geometries; placement of the chip into the scanner is not fixed, meaning the corners of the chip can be anywhere ;scanners often distort the resulting images, which creates problems for converting these images into the required data; since there are many different design patterns at the same time, benchmarks can be placed in many different combinations

Brandle et al. [Ref. 1] and Uehara and Kakadia...

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