This finding suggests that staff at clinics may not assign significant value to the quality of data collection and that the current data system is not used to improve the quality of PMTCT care processes at a local clinic level.
It may also be that staff at clinics do not assign significant value to the quality of data collection as they do not see that data is used to inform health services.
Figure 2 shows for all data sets the distribution of p-values after 10,000 randomizations, and the p-values of the disease genes whereby all were assigned significant p-values.
SSA assigns significant p-values to the expression modules in the first and second clusters scores, presumably reflecting that they are specifically expressed in a small number of tissues.
In all four benchmark data sets, the disease causing genes were ranked in the top 10 (FXS: 1st position, MFS: 5th position, CF: 7th position, BMD: 2nd position) out of lists containing approximately 120 candidate genes (see Supplementary Material), and all were assigned significant p-values.
In total, 22 pathways are assigned significant q-values for at least one dataset (data not shown) and 11 of 22 are significant for at least two datasets (Table 3), while the others are often ranked in the top 50 pathways.
At a mass tolerance of 5 ppm, only protein scores greater than 70 (p<0.05) were assigned significant with an expected value of 10−7.
If the two sides of the junction match two different reference sequences (which may have different coverage-evenness properties), then a p-value is calculated for each one and the junction is assigned the least-significant value.
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