Screen scoring method:
The data was firstly log transformed (log base 2), in order to obtain a normal distribution. Next, normalization was performed using ratio of raw measurement to the mean of the negative control (non-targeting siCtrl). After normalization, for each one of 4 replicates, its distance to the mean of the other 3 replicates was calculated and compared with the standard deviation of the other 3 replicates. An outlier was identified when the distance was 3 times bigger than the standard deviation. Outliers were removed before the hits identification. For hits identification, a two tailed t-test was used to compare each condition (4 replicates) with the negative control and genes were ranked on P-value. 136 genes were identified as hits and were grouped into 4 phenotypic classes based on unsupervised hierarchical clustering which was carried out on the normalized values where normalized values are the average values of 4 replicates with outliers removed.
