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The mean ranking value for each gene set was calculated across the data sets and finally the gene sets were ranked according to this value.
To fulfill the null-hypothesis an observed mean ranking value should be within 95% interval of the null-distribution.
To test the significance for a given gene set, the observed mean ranking value was compared to the null distribution.
Similar, gene sets with a high mean ranking value indicated low expression in metastasizing tumors compared to non-metastasizing tumors (table 2).
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A null distribution of mean ranking values was generated from these results.
The mean ranking values varied from 4.26 (more important) for mood by nursing assistants to 1.69 (less important) for memory by elderly-care physicians.
To simulate the distribution of mean ranking values across the 8 data sets fulfilling the null-hypothesis, random drawing of 8 ranking values were performed 106 times and the mean value was calculated each time.
In the additional file, an overview of all facilitating and impeding factors per (implementation) phase can be found, including their ranking scores (i.e. mean ranking score and range assigned rankings).
AUC values can be converted to mean rankings by noting that the AUC reports the mean probability that, for a random disease, given a random positive gene and a random negative gene, the positive gene is scored higher than the negative gene.
This means that the ranking value for a given gene set in a given data set is expected to be a random value between 1 and the maximum number of gene sets analyzed.
That means that Verizon gets 8 points (ranking value of 4 points times attribute value of 2), while AT&T and Sprint each get 4 points.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com