초록 ▼

The invention provides methods and systems for reconstructing feature intensities from pixel level data. In certain embodiments, the invention uses an empirically determined transfer function to construct a theoretical estimate of pixel level data and then iteratively updates feature intensities bas

The invention provides methods and systems for reconstructing feature intensities from pixel level data. In certain embodiments, the invention uses an empirically determined transfer function to construct a theoretical estimate of pixel level data and then iteratively updates feature intensities based on a minimum multiplicative error between the pixel level data and the theoretical estimate of the pixel level data.

대표청구항 ▼

1. A system for modifying image data from a biological probe array, wherein the system comprises: a computer, wherein the computer comprises a processor, wherein the processor is configured to access a non-transitory computer-readable storage medium, wherein the processor is configured to execute ma

1. A system for modifying image data from a biological probe array, wherein the system comprises: a computer, wherein the computer comprises a processor, wherein the processor is configured to access a non-transitory computer-readable storage medium, wherein the processor is configured to execute machine-readable instructions stored on the non-transitory computer-readable storage medium, and wherein the machine-readable instructions cause the processor to perform the steps of: (a) obtaining image data for a feature of a biological probe array, wherein the image data comprises a set of pixels;(b) determining an observed pixel intensity for each pixel in the set of pixels;(c) determining an initial feature intensity for the feature, wherein the initial feature intensity is based upon the observed pixel intensity;(d) determining a theoretical pixel intensity for each pixel in the set of pixels, wherein the theoretical pixel intensity is based, at least in part, upon the initial feature intensity, wherein determining the theoretical pixel intensity comprises determining an empirically based transfer function, and wherein determining the theoretical pixel intensity comprises multiplying the empirically based transfer function with the initial feature intensity;(e) determining an error for each pixel in the set of pixels, wherein the error is based upon the observed pixel intensity and the theoretical pixel intensity; and(f) determining an adjusted feature intensity, wherein the adjusted feature intensity is based upon the initial feature intensity and the error. 2. The system of claim 1, wherein the empirically based transfer function relates to a shape formed by the set of pixels. 3. The system of claim 1, wherein the empirically based transfer function relates the observed pixel intensity for each pixel with the location of the pixel within the image data. 4. The system of claim 1, wherein the empirically based transfer function comprises an array, and wherein the array comprises dimensions relating to pixel locations and dimensions relating to an address of the feature. 5. The system of claim 1, wherein the empirically based transfer function is based upon representation of a pixel location relative to a center location of the feature. 6. The system of claim 1, wherein determining the theoretical pixel intensity additionally comprises determining a background intensity. 7. The system of claim 1, wherein determining the theoretical pixel intensity is additionally based upon a background intensity. 8. The system of claim 7, wherein the background intensity is added to an initial theoretical pixel intensity to determine the theoretical pixel intensity. 9. The system of claim 1, wherein determining the error comprises calculating a multiplicative error value based upon the observed pixel intensity and the theoretical pixel intensity. 10. The system of claim 9, wherein calculating the multiplicative error value comprises determining an error function based upon the observed pixel intensity and the theoretical pixel intensity. 11. The system of claim 10, wherein the error function is the quotient of dividing the observed pixel intensity by the theoretical pixel intensity. 12. The system of claim 10, wherein the error function is adjusted to remove outlying error values. 13. The system of claim 12, wherein the outlying error values are removed with use of a standard deviation function. 14. The system of claim 12, wherein determining the adjusted feature intensity comprises multiplying the initial feature intensity by an update factor, and wherein the update factor is based upon the error function after adjustment to remove outlying error values. 15. The system of claim 10, wherein the error function is adjusted through comparison to a preselected value. 16. The system of claim 15, wherein the error function is restricted within a preselected range, wherein the preselected range is defined by the preselected value and divided by preselected value. 17. The system of claim 1, wherein determining the adjusted feature intensity comprises multiplying the initial feature intensity by an update factor, and wherein the update factor is based upon the error. 18. The system of claim 17, wherein the update factor is additionally based upon a weight function, wherein each feature comprises a center location, and wherein the weight function assigns a weight to a pixel based upon the pixel's distance from the center location such that pixels are assigned a higher weight as their distance from the center location decreases. 19. The system of claim 1, wherein the machine-readable instructions additionally cause the processor to perform the steps of: (g) repeating steps (d)-(f) until the adjusted feature intensity has converged, wherein repeated steps (d)-(f) utilize the adjusted feature intensity in place of the initial feature intensity. 20. A system for modifying image data from a biological probe array, wherein the system comprises: a computer, wherein the computer comprises a processor, wherein the processor is configured to access a non-transitory computer-readable storage medium, wherein the processor is configured to execute machine-readable instructions stored on the non-transitory computer-readable storage medium, and wherein the machine-readable instructions cause the processor to perform the steps of: (a) obtaining image data for a feature of a biological probe array, wherein the image data comprises a set of pixels;(b) determining an observed pixel intensity for each pixel in the set of pixels;(c) determining an initial feature intensity for the feature, wherein the initial feature intensity is based upon the observed pixel intensity;(d) determining a theoretical pixel intensity for each pixel in the set of pixels;(e) determining an error for each pixel in the set of pixels, wherein the error is based upon the observed pixel intensity and the theoretical pixel intensity, wherein determining the error comprises calculating a multiplicative error value based upon the observed pixel intensity and the theoretical pixel intensity; and(f) determining an adjusted feature intensity, wherein the adjusted feature intensity is based upon the initial feature intensity and the error. 21. The system of claim 20, wherein determining the theoretical pixel intensity comprises determining an empirically based transfer function. 22. The system of claim 21, wherein the empirically based transfer function relates to a shape formed by the set of pixels. 23. The system of claim 21, wherein the empirically based transfer function relates the observed pixel intensity for each pixel with the location of the pixel within the image data. 24. The system of claim 21, wherein the empirically based transfer function comprises an array, and wherein the array comprises dimensions relating to pixel locations and dimensions relating to an address of the feature. 25. The system of claim 21, wherein the empirically based transfer function is based upon representation of a pixel location relative to a center location of the feature. 26. The system of claim 20, wherein determining the theoretical pixel intensity additionally comprises determining a background intensity. 27. The system of claim 21, wherein determining the theoretical pixel intensity is additionally based upon the initial feature intensity. 28. The system of claim 27, wherein determining the theoretical pixel intensity multiplies the empirically based transfer function with the initial feature intensity. 29. The system of claim 27, wherein determining the theoretical pixel intensity is additionally based upon a background intensity. 30. The system of claim 29, wherein the background intensity is added to an initial theoretical pixel intensity to determine the theoretical pixel intensity. 31. The system of claim 20, wherein calculating the multiplicative error value comprises determining an error function based upon the observed pixel intensity and the theoretical pixel intensity. 32. The system of claim 31, wherein the error function is the quotient of dividing the observed pixel intensity by the theoretical pixel intensity. 33. The system of claim 31, wherein the error function is adjusted to remove outlying error values. 34. The system of claim 33, wherein the outlying error values are removed with use of a standard deviation function. 35. The system of claim 33, wherein determining the adjusted feature intensity comprises multiplying the initial feature intensity by an update factor, and wherein the update factor is based upon the error function after adjustment to remove outlying error values. 36. The system of claim 31, wherein the error function is adjusted through comparison to a preselected value. 37. The system of claim 36, wherein the error function is restricted within a preselected range, wherein the preselected range is defined by the preselected value and divided by preselected value. 38. The system of claim 20, wherein determining the adjusted feature intensity comprises multiplying the initial feature intensity by an update factor, and wherein the update factor is based upon the error. 39. The system of claim 38, wherein the update factor is additionally based upon a weight function, wherein each feature comprises a center location, and wherein the weight function assigns a weight to a pixel based upon the pixel's distance from the center location such that pixels are assigned a higher weight as their distance from the center location decreases. 40. The system of claim 20, wherein the machine-readable instructions additionally cause the processor to perform the steps of: (g) repeating steps (d)-(f) until the adjusted feature intensity has converged, wherein repeated steps (d)-(f) utilize the adjusted feature intensity in place of the initial feature intensity.