Currently the results of outlier analysis can vary from run to run for both the locus and motif based analysis. More specifically, top_case_zscore can vary and this sometimes leads to different numbers of lines being written to the output .tsv.
I believe that this is due to the use of numpy random.choice() without setting numpy random.seed(). It would be great to set a seed so that results can be reproduced exactly.
Currently the results of outlier analysis can vary from run to run for both the locus and motif based analysis. More specifically, top_case_zscore can vary and this sometimes leads to different numbers of lines being written to the output .tsv.
I believe that this is due to the use of numpy random.choice() without setting numpy random.seed(). It would be great to set a seed so that results can be reproduced exactly.