Running this process for the Illumina_CNV370_Samples_Confidential.txt example generates the Results window shown below. Refer to the Illumina Copy Number Input Engine process description for more information.
Note: For this example, R, X, Y, Log_R_Ratio, LOH_Score, and CNV_Value were specified in theColumns to Include option.
The Results window contains the following elements:
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Intensity Data Set: (Also know as the Copy Number Data Set or the Output Data Set). This data set contains the data from the input file.
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Experimental Design Data Set (EDDS): This data set lists specific information about experimental details for each of the arrays. Refer to Experimental Design Data Set (EDDS) for more information about this data set. Note: There can be more that one EDDS depending on the columns specified in theColumns to Include option. In this example a separate EDDS was generated for analysis of data in the Log_R_Ratio column.
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XY Data Set: This data set contains the intensity data for the individuals in the sample. This data set only contains the X and Y measures (assuming that these measures are present in the text file exported from BeadStudio). This is a tall data set, with SNPs listed in rows, and individuals listed in the columns. There are two rows per SNP; one row lists the intensity value for X (the normalized intensity for the A allele) while the second row lists the intensity value for Y (the normalized intensity for the B allele). An Allele column in this data set identifies the allele whose intensity is listed in each row
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XY EDDS: This data set lists experimental details needed for further analysis of the data contained in the XY Data Set.
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Note: You can view the data in a file or data set by clicking either or (when the data set is very large).
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Basic Copy Number Workflow: Click to launch the Basic Copy Number Workflow process with the output data set, EDDS, and annotation data set specified as input.
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Click to reopen the completed process dialog used to generate this output.
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Click to close all graphics windows and underlying data sets associated with the output.
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