Abstract: Methods, systems and computer readable media for facilitating analysis of feature extraction outputs across multiple extractions. A feature extraction output of an extraction resulting from feature extraction of an array is inputted, and global statistics and array processing parameters are extracted from the feature extraction output. A table/file is populated with the extracted global statistics and array processing parameters of the extraction. The inputting, extracting and populating steps are repeated for at least one additional feature extraction output of another extraction, so that the table/file includes global statistics that can be readily cross-compared over multiple extractions with reference to a single table or file. Methods, systems and computer readable media are provided for setting threshold values for metrics that global statistics are provided for. An evaluation metric may be set by a user, based upon the threshold values set for the metrics.

Abstract: Methods of reading chemical arrays are provided. Aspects of the methods include reading an array at a first and second detector gain setting to produce linked data sets of an array, where each reading may be made using a different detector gain setting. Aspects of the methods further include extracting features from the linked data sets, where in certain embodiments a merged data set feature extraction protocol is employed. Aspects of the invention further include programming for operating devices, e.g., chemical array readers, as well as readers comprising such programming.

Abstract: Methods, systems and computer readable media for bifurcating automated feature extraction processing of chemical arrays. A plurality of arrays may be image-processed sequentially, and then, outputs resulting from the image processing of at least two of the plurality of the arrays may be post-processed in an automated batch process to obtain processed outputs. In another aspect, a plurality of arrays may be image-processed in an automated batch process, and then outputs resulting from the image processing may be post-processed according to different post-processing protocols with respect to at least two of the plurality of the arrays. In another aspect, an array may be image-processed, and then an output of the image processing may be post-processed in an automated batch process, where at least two different post-processing protocols are assigned to the output of image processing, so that processed outputs are outputted for each of the processing protocols.

Abstract: Systems, methods and computer readable media for extracting data from features on a chemical array, using a feature extraction module including feature extraction algorithms configured to calculate characteristics of array features. A reference table is provided that associates probe names of probes contained on the array with at least one additional identifier. The reference table is accessible by the feature extraction module to convert any one of the at least one additional identifiers to the probe names, and the probe names to at least one of the at least one additional identifiers.

Abstract: Methods, systems and computer readable media for automatically feature extracting array images in batch mode. At least two images to be feature extracted are loaded into a batch project, and the system automatically and sequentially feature extracts the images in the batch project. At least one of the images may be feature extracted based upon a different grid template or protocol than at least one other of the images. Methods, systems and computer readable media are provided to automatically feature extract a single array image having an identifier indicating that it is a multipack, multiple array image. A system provided for feature extracting array images in batch mode includes a user interface with a feature enabling a user to select images to be loaded into a batch project; and based upon the loaded images in the batch project, the system may automatically assign a grid template to each image loaded into the batch project.

Abstract: A method and system for quantify random errors, sequence-dependent trends, and spatial-intensity trends in one or more channels of microarray data sets. The method and system of one embodiment of the present invention is directed to a method for quantifying random errors, sequence-dependent trends, and spatial-intensity trends present in microarray data sets. An additive error equation is employed to quantify background noise present in feature intensities due to random errors, sequence-dependent trends, and spatial-intensity trends.

Abstract: Methods, systems and computer readable media for automatically separating multiple microarray images provided as a single combined image of the multiple microarray images. Methods, systems and computer readable media are provided for providing at least one image containing multiple microarray images thereon, automatically locating the features in the microarray images, automatically determining the boundaries of each microarray image based on the locations of the features, and automatically cropping the image containing multiple microarray images to form a group of single images, each containing only one microarray image cropped from the image containing multiple microarray images. Methods, systems and computer readable media are provided for evaluating separation locations of multiple microarray images in a single combined image of the multiple microarray images, and separating the multiple microarray images along the separation locations, wherein the images are represented in a two-dimensional array.

Abstract: A method and system for quantifying and correcting spatial-intensity trends for each channel of a microarray data set having one or more channels. The method and system of one embodiment of the present invention selects a set of features from each channel of the microarray data set. Based on the selected set of features, a surface is used to determine the intensities for all features in each channel of the microarray data set. Spatial-intensity trends within the microarray data set are quantified, based on the surface to the intensities for each channel of the microarray data set. After the surface has been determined, the spatial-intensity trend can be removed from the microarray data set.

Abstract: A method and system for estimating a global background-signal correction for each channel of a microarray data set. The method and system of one embodiment of the present invention is directed to a method for calculating background corrected signals for a microarray data set by receiving a non-negative constant and selects a set of low-combined-intensity features from the microarray data set. Based on the low-combined-intensity features, a representation that describes a central-trend of the selected set of low-combined-intensity features is determined in signal-intensity space. The method adjusts the microarray data set parallel to the determined representation based on the non-negative constant.