The quality control menu
The quality control menu provides methods for calculating the average uracil number for your data and bias correcting.
Additionally you can assess the calculation of probeset quality control scores here directly,
without having to filter the data according to it.
Calculation of Uracil number
In order to use this method you have to first load gene names and sequences for your data. This method calculates
the number of uracils in each sequence and plots it against the logarithm of the ratio of either newly transcribed to
total RNA, pre-existing to total RNA or newly transcribed to pre-existing RNA. Besides a plot displaying the correlation
of these two values you will also be provided with the average number of uracils in all sequences and
the average ratio. You can also save the plotting script.
Correction for bias in capture-rates
R has to be installed to be able to use this method. You can either enter the path to the directory where you have
installed R in the Settings menu or directly after starting this method.
For the calculation of the correlation between number of uracils and ratio you can either load previously saved
plotting information from the calculation of uracil number, or simply reproduce this step when asked.
You can choose between three methods for calculating the correlation: Spearman (default),
Pearson and Kendal. After choosing a method the
correlation coefficient will be calculated.
In a second step the loess regression will be used to calculate the bias and resulting correction factors for each probeset.
You can plot the corrected values against number of uracils, and also repeat normalization and half-life calculation
with these corrected values. If you have not performed half-life calculation previously, you can also enter your
parameters now. There is also the possibility to recreate plots with the corrected values for normalization and for
half-life calculation.
Calculate the probeset quality control scores
You can also assess the distance of your data points to the linear regression line by
calculating the probeset quality control scores. These scores can be used for filtering
(see Filtering menu for details),
for which you can access the calculation directly over the filtering sub-panel, or in
this menu, where you can use the scores to plot a histogram or simply save them to a
file.