Gridline: automatic grid alignment DNA microarray scans

• Published in: IEEE transactions on image processing Vol. 13; no. 1; pp. 15 - 25
• Main Author: Bajcsy, P.
• Format: Journal Article
• Language: English
• Published: New York, NY IEEE 01.01.2004; Institute of Electrical and Electronics Engineers; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Applied sciences; Artificial intelligence; Automation; Computer science; control theory; systems; Data analysis; Data mining; DNA; Exact sciences and technology; Feature extraction; Image color analysis; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; Image processing; Information Storage and Retrieval - methods; Information, signal and communications theory; Microscopy, Fluorescence - methods; Oligonucleotide Array Sequence Analysis - methods; Pattern Recognition, Automated; Pattern recognition. Digital image processing. Computational geometry; Pins; Quality control; Reproducibility of Results; Robotics - methods; Sensitivity and Specificity; Shape; Signal processing; Signal Processing, Computer-Assisted; Studies; Subtraction Technique; Telecommunications and information theory; Two dimensional displays; DNA microarray; Alignment; Image analysis; Image processing; quality control; DNA; simulation; Feature extraction; spot alignment; Algorithm
• ISSN: 1057-7149; 1941-0042
• DOI: 10.1109/TIP.2003.819941

We present a new automatic grid alignment algorithm for detecting two-dimensional (2-D) arrays of spots in DNA microarray images. Our motivation for this work is the lack of automation in high-throughput microarray data analysis that leads to a) spatial inaccuracy of located spots and hence inaccuracy of extracted information from a spot and b) inconsistency of extracted features due to manual selection of grid alignment parameters. The proposed grid alignment algorithm is novel in the sense that 1) it can detect irregularly row- and column-spaced spots in a 2-D array, 2) it is independent of spot color and size, 3) it is general to localize a grid of other primitive shapes than the spot shapes, 4) it can perform grid alignment on any number of input channels, 5) it reduces the number of free parameters to minimum by data driven optimization of most algorithmic parameters, and 6) it has a built-in speed versus accuracy tradeoff mechanism to accommodate user's requirements on performance time and accuracy of the results. The developed algorithm also automatically identifies multiple blocks of 2-D arrays, as it is the case in microarray images, and compensates for grid rotations in addition to grid translations.