Visualization, sharing and analysis of large data sets

摘要

Systems and methods for visualization, sharing and analysis of large data sets are described. Systems and methods may include receiving an input data set, wherein the input data set includes data that can be classified in classification dimensions wherein a first classification dimension is a linear ordering of data entries and a second classification dimension represents analysis criteria, traits of the data entries, or aspects of the data entries; obtaining an unabridged data table listing results for each combination of coordinates in the first classification dimension and the second classification dimension; and displaying contents of the unabridged data table as a visual array wherein two axes correspond to the coordinates and a third axis corresponds to a third classification dimension, wherein the third classification dimension represents an actual value of the respective data point for the coordinates. Methods may also assess the visual array, such as by identifying one or more regions of high density of signals.

主权项

1. An automated computerized method for visualization, replication, sharing, or analysis of large data sets, the computerized method comprising the steps of:
receiving an input data set, wherein the input data set comprises data that can be classified in classification dimensions wherein a first classification dimension is a linear ordering of data entries and a second classification dimension; obtaining an unabridged data table listing results for each combination of coordinates in the first classification dimension and the second classification dimension; and displaying contents of the unabridged data table as a visual array wherein two axes correspond to the coordinates and a third axis corresponds to a third dimension, wherein the third dimension represents an actual value of the respective data point for the coordinates, and expanding the display of a result of a genome-wide association study (GWAS) data set for genome-wide variants including real-time replication of candidate or putative genes to limit statistical penalties in the visual array, wherein the visual array is depicted as a three-dimensional image that can be displayed as a moving video mode above a surface wherein two axis in the horizontal plane represent the first classification dimension and the second classification dimension, while height of blocks rising from that plane represent the third dimension.