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I ran the command (for m6A all context)
$dorado basecaller [email protected] c6_r1/pod5/ --modified-bases-models [email protected]_m6A@v1/ --device cuda:all > c6_r1_sup_m6A.bam
and then pileup using modkit
i found out that the m6A sites predicted were >1.6 million per sample, which is not desirable result.
maybe we need a stringent threshold or a site to be called methylated.
instead of running the dorado basecalling again, is there any parameter in modkit which can filter the predicted results to get a more stringent set of results?
Thanks
The text was updated successfully, but these errors were encountered:
If I'm understanding you correctly, the 1.6M m6A sites is too many based on your understanding of the biology - correct? You could use a higher threshold for m6A by passing --mod-threshold a:0.98 (docs describing how per-mod thresholds work)or similar to modkit pileup. You may also look at modkit sample-probs --histto help inform the value to pick.
You may try and re-basecall the reads with [email protected]_inosine_m6A@v1 and then either --ignore 17596 or --combine-mods. The v0.5.1 models have better performance in terms of basecalling accuracy and modification calling accuracy due to adding more modified strands in the basecaller training. There is a great intro here.
Hello,
I am working with plant DRS dataset
I ran the command (for m6A all context)
$dorado basecaller [email protected] c6_r1/pod5/ --modified-bases-models
[email protected]_m6A@v1/ --device cuda:all > c6_r1_sup_m6A.bam
and then pileup using modkit
i found out that the m6A sites predicted were >1.6 million per sample, which is not desirable result.
maybe we need a stringent threshold or a site to be called methylated.
instead of running the dorado basecalling again, is there any parameter in modkit which can filter the predicted results to get a more stringent set of results?
Thanks
The text was updated successfully, but these errors were encountered: