DNA sequence reading by image processing: a thesis presented in partial fulfilment of the requirements for the degree of Master of Science in computer science at Massey University

The research described in this thesis is the development of the DNA sequence reading system. Macromolecular sequences of DNA are the encoded form of the genetic information of all living organisms. DNA sequencing has therefore played a significant role in the elucidation of biological systems. DNA sequence reading is a part of DNA sequencing. This project is for reading DNA sequences directly from DNA sequencing gel autoradiographs within a general purpose image processing system. The DNA sequence reading software is developed based on the waterfall software development approach combined with exploratory programming. Requirement analysis, software design, detailed design, implementation, system testing and maintenance are the basic development stages. The feedback from implementation and system testing to detailed design is much stronger in image processing than a lot of other software development. After an image is captured from a gel autoradiograph, the background of the image is normalised and the contrast is enhanced. The captured image consists several lane sets of bands. Each of the lane set represents one part of a DNA sequence. The lane sets are separated automatically into subimages to be read individually. The gap lines between the lane sets are detected for separation. The geometric distortions are corrected by finding the boundaries of the lane set in the subimage. The left boundary of the lane set is used to straighten lane set and the right boundary is used to warp the lane set into a standard width. If separation of the lane sets or geometry correction is unsuccessful by automatical processing, manual selection is used. After the band features are enhanced, the individual bands are extracted and the positions of the bands are determined. The band positions are then converted into the order of the DNA sequence. Different part of a sequence from subsequences are merged into a longer sequence. In most of the cases, the individual lane sets in a captured image are able to be separated automatically. Manual processing is necessary to handle the cases where the lane sets are too close. The system may reach an accuracy of 98% if the bands are clear. Manual checking and correcting the detected bands helps to obtain a reliable sequence. If a lane set on the autoradiograph is indistinct or bands are too close it may reduce the accuracy, in extreme cases to the point where it is unreadable. For a 512x512 image captured from a gel autoradiograph, preprocessing takes 90 seconds, processing each subimage takes 40 seconds on a 33Hz 486 PC. If processing a 430x350 mm autoradiograph with 16 lane sets, assuming 6 images are required, it takes about 40 minutes