Method and system for dynamic, automated detection of outlying feature and feature background regions during processing of data scanned from a chemical array

A method of dynamically tuning a variance model to an instance of a hybridized chemical array, said method comprising the steps of:

• inputting signal intensity values produced from scanning a region of the hybridized array;
• defining a variance model as a sum of factors multiplied by multiplicative coefficients, wherein the multiplicative coefficients for the respective factors are each a composite of a scanner-dependent multiplier and an array-dependent multiplier;
• dynamically calculating the array-dependent multipliers;
• determining a variance of measured signals within the region;
• determining whether or not the region contains a non-uniform measured signal distribution by comparing the determined variance of measured signals within the region to the variance model;
• and
• displaying results indicating whether or not the region contains a non-uniform measure signal distribution.

A system for identifying a non-uniform measured signal distribution in a region of a scanned image of a chemical array, the system comprising:

• a digital representation of the measured signals in the region of the scanned image of the chemical array stored within a memory component;
• an automatic, dynamically adjustable variance model for measured signal distributions within regions of the chemical array stored within a memory component;
• and
• a computational processing engine that calculates a variance of measured signals within the region and compares the calculated variance with the variance model to determine whether or not the region contains a non-uniform measured signal distribution by comparing the determined variance of measured signals within the region to the variance model.