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It cannot be because of our data that the export of PC I, which is roughly the same size is not affected by either the loss of TANGO1, SLY1 or STX18.
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Continuous data were described by medians and interquartile ranges (IQR), because most of our data did not show a normal distribution.
Because all of our data were collected with the same QMR protocol on the same machine, this bias does not have any effect on the variance among individuals or strains, which is the object of our study.
Because all of our data were acquired at the level of the individual cell, we are able to provide a function that allows the user to download abundance and localization data for single cells.
It is difficult to evaluate the normality because the number of our data is small.
Third, because of limitations of our data we could not adjust for differences in the distribution of age across states.
Because of the nature of our data, it is difficult to verify such claims, as more detailed information (e.g. about the nationalities of athletes) is lacking.
However, we did not employ such model, because the temporal resolution of our data would not have permitted a robust fitting of the decomposition process using a model with many parameters.
The first dataset is our preferred approach for resolving the relationships among clades, because it applies all of our data towards resolving the species tree.
The high-degree nodes naturally represent the highly centralized property of hubs characterizing the specific network organization because the degree distribution of our data was long-tailed.
Although Moore et al. [ 17] recommended using multiple imputation as a more accurate data model, we chose the simple approach of eliminating all patients with missing data because of the size of our data set.
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