DNA Microarray Image Processing

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This computer science project topic on DNA Microarray Image Processing discuss about various Microarray technologies, workflow management of micro array data processing, issues associated with Micro array image processing, Micro-array file format and layouts, image processing steps, image processing requirements and existing spot variations. DNA Micro array data processing is used in research and development of

  • Micro array image analysis
  • Data cleaning, perprocessing, semantic integration of distributed biomedical databases
  • Exploration of existing data mining tools for bio-data analysis
  • Development of advanced and scalable data mining methods in bio data analysis

Various image processing steps involved in DNA Micro array Image Processing are

  • Grid alignment
  • Foreground separation
  • Spot quality assessment
  • Data quantification
  • Normalization

Workflow for the same is as shown below

DNA Microarray Image Processing

Microarray image layout is dependent on spots arranged within a 2D grid, and the equipment used in synthesizing the array. Microarray image file format uses TIFF files to store the data. 2 16 bit files are generated when cDNA or oligo micro array are scanned. TIFF files contain info about fluorescence from green and red dyes. Major requirements of image processing are speed and accuracy of images. Laser scanning of a cDNA or oligo microarray slide generates two 16-bit TIFF files which can be saved in 1 bit, 4 bit, 8 bit and 16 bit data. Fluorescence from red and green dyes  will be stored in these files. Based on the dynamic range of fluorescence measurements and sensitivity of laser scanners, 16 bits per pixel is used. The fluorescence values after amplification and analog to digital conversion should be within the interval [0, 2^16-1 = 65,535], otherwise the high values would be truncated to the maximum. In order to prevent spot information loss, and to avoid increased uncertainty of extracted spot statistics lossy compression is not preferred.

For choosing suitable image processing approach, following things should be considered.

  • Variations of input microarray images in terms of the image content including foreground and background morphology (grid layout, shape and size) and intensity information
  • Computer characteristics of input digital images (spot descriptors derived from foreground and background intensities)

Ideal Microarray Image would be characterized by deterministic grid geometry, known background intensity with zero uncertainty, predefined spot shape and constant spot intensity that is different from the background and it is directly proportional to the biological phenomenon and have zero uncertainty for all spots. Simulations of cDNA microarray images can generate data sets for testing multiple microarray processing algorithms since it is difficult to obtain physical ground truth as an image valuation standard because of the image preparation complexity, and large number of replicates of biological samples as a statistically significant standard because of the cost.

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