Sample Profile Represents the distribution of the user-input data overall by the sample groups with and without the profile activity. This enables to assess whether or not, on an average, the entire gene set defines the sample groups by the user selected sample profile. Within the “Sample Profile” tab, user also have the option to select a “Gene to Display” from the “Choose Options” drop down menu on the rightmost panel, to see the input data distribution by each sample sorted within each sample profile. This enables the user to identify the gene(s) that are most distinguishing among samples with and without the profile activity. Save Results User can download the results as one excel file by clicking on the “Save” button on the left panel. The download includes table and pdf plots of the results. Citation Please cite the SISPA method as: Kowalski J, Dwivedi B, Newman S, Switchenko JM, Pauly R, Gutman DA, et al. Gene integrated set profile analysis: a context-based approach for inferring biological endpoints. Nucleic Acids Research. 2016;44(7):e69. References Hänzelmann, S., Castelo, R. and Guinney, A. GSVA: gene set variation analysis for microarray and RNA-seq data. 2013;14(7). BMC Bioinformatics
Sample Profile Represents the distribution of the user-input data overall by the sample groups with and without the profile activity. This enables to assess whether or not, on an average, the entire gene set defines the sample groups by the user selected sample profile. Within the “Sample Profile” tab, user also have the option to select a “Gene to Display” from the “Choose Options” drop down menu on the rightmost panel, to see the input data distribution by each sample sorted within each sample profile. This enables the user to identify the gene(s) that are most distinguishing among samples with and without the profile activity. Save Results User can download the results as one excel file by clicking on the “Save” button on the left panel. The download includes table and pdf plots of the results. Citation Please cite the SISPA method as: Kowalski J, Dwivedi B, Newman S, Switchenko JM, Pauly R, Gutman DA, et al. Gene integrated set profile analysis: a context-based approach for inferring biological endpoints. Nucleic Acids Research. 2016;44(7):e69. References Hänzelmann, S., Castelo, R. and Guinney, A. GSVA: gene set variation analysis for microarray and RNA-seq data. BMC Bioinformatics 2013;14(7).
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