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icthrm / cwSDTWnano

Here we proposed two novel algorithms, the Direct Subsequence Dynamic Time Warping for nanopore raw signal search (DSDTWnano) and the continuous wavelet Subsequence DTW for nanopore raw signal search (cwSDTWnano), to enable the direct subsequence inquiry and exact mapping in the nanopore raw signal datasets. The proposed algorithms are based on the idea of Subsequence-extended Dynamic Time Warping (SDTW) and directly operates on the raw signals, without any loss of information. DSDTWnano could ensure an output of highly accurate query result and cwSDTWnano is the accelerated version of DSDTWnano, with the help of seeding and multi-scale coarsening of signals that based on continuous wavelet transform (CWT).
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Can this detect strain level differences or only at the species level? #4

Closed harisankarsadasivan closed 3 years ago

harisankarsadasivan commented 3 years ago

For example, what if my reference signal is from ecoli strain 1, does csdtwnano (cwt based) distinguish ecoli strain 2 ?

icthrm commented 3 years ago

Thank you for your email. if there are only several SNPs, we cannot make it (it is a phasing problem). If there are differences with long bps (for example, 40 bp difference), we could make it.

harisankarsadasivan notifications@github.com 于2020年10月9日周五 下午11:36写道：

For example, what if my reference signal is from ecoli strain 1, does csdtwnano (cwt based) distinguish ecoli strain 2 ?

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