Using RNA for MotifSeq

[epi-gene]

Would there be a possibility to simulate RNA squiggles and perform motif search ?

[Psy-Fer]

Hello,

yes, just use the following flag
--scrappie_model squiggle_r94_rna

[epi-gene]

Hi. I tried the above but the motifseq is yielding no results. The hit probabilities are 0 for all the reads.

[epi-gene]

Is there a way to calculate them manually ?

[Psy-Fer]

Could you please give me an example of the output?
I'll look into it. I have some RNA data on hand to double check.

[epi-gene]

fast5 | readID | model | start | end | length | distance_score | model_mean | model_stdev | Z-score | p-value | hit_Probability
8e91fa7d-fd33-422b-8dfb-69915b17aa8d.fast5 | 8e91fa7d-fd33-422b-8dfb-69915b17aa8d | last50 | 11839 | 12071 | 232 | 399.438241083274 | 135.4 | 11.465672 | 23.0285883883015 | 1 | 0

[epi-gene]

You did mention

The p-values and hit probabilities provided are based on loose modelling of negative background scores for a number of k-mers. It is currently only modelled on R9.4 model, not R10 or RNA
in the readme.

[epi-gene]

@Psy-Fer Would MotifSeq be able to detect multiple Motif hits within a single read ? Or would it display only the high scoring hit ?

[Psy-Fer]

Currently, only the highest scoring hit.

I plan on allowing it to record more than the the top hit.

A round about way of "hacking" a solution, is to just mask out the region of the best hit, and try again. So, just take the values between the start and stop site, and change them to the mean current, or make them 99999 and they will get filtered out altogether. Obviously that isn't idea, and i'll try fixing this.

[epi-gene]

Ok. Will try that.