[maker-devel] SNAP bootstrap training
Carson Holt
carsonhh at gmail.com
Fri Apr 6 09:40:14 MDT 2018
More than 2 total trading rounds can generate what is known as the overtraining trap. So I rarely do more than one round of bootstrapping with SNAP. To evaluate the models, look at them in a browser. If the raw models are similar to the final hint based models, then SNAP is well trained. If not then SNAP is poorly trained. Don’t use final models directly to evaluate training. Rather look at the raw models. They are what are made direct from the HMM. A well trained predictor will perform similarly even outside if MAKER. If it’s over predicting on its own, you may need to filter or even manually curate a subset of models from the initial training round to get better bootstrap training. Also if you did not build a species specific repeat library, you may be under masking and essentially training SNAP to find transposons with the bootstrapping.
—Carson
Sent from my iPhone
> On Apr 6, 2018, at 7:23 AM, Timo Metz <timo.metz at googlemail.com> wrote:
>
> Hello,
>
> I am using MAKER for a non-model organism, and I am currently trying to do the bootstrap training for SNAP as outlined in the tutorial and the paper for MAKER.
>
> For the training I am using a set of ~300 sequences which are conserved (no golden standard genes available) and have very high quality and stop training after third round of bootstrap training.
>
> However, it seems as training does not work properly, because when checking the AEDs for each round of bootstrap training, they actually get worse each round. Also the performance of snap after training is practically similar as before training and significantly worse than using a training file for a model organism.
>
> Are there any suggestions what could be wrong? Is there anything special to check or look at what is not mentioned in the tutorial?
>
> thanks in advance
>
> kind regards
> Timo Metz
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