Fluorescence bias in in signals from individual SNP arrays can be calibrated using linear models. Given the data, the system of equations is very large, so a specialized symbolic algorithm was... Show moreFluorescence bias in in signals from individual SNP arrays can be calibrated using linear models. Given the data, the system of equations is very large, so a specialized symbolic algorithm was developed. These models are also used to illustrate that genomic waves do not exist, but are merely an artifact of commonly used methods. Furthermore, a new semi-parametric, single array, approach to SNP genotyping is introduced and shown to be both effective and efficient. A refined algorithm for copy number estimation, using a zero-exponent norm is proposed, which performs well, as is illustrated by thorough comparisons with other methods. Indications that the signal calibration can improve (genotyping) results from lower quality samples are also discussed. A software suite that implements the above is described and illustrated. Show less
