Noise Reduction Method of Nanopore Based on Wavelet and Kalman Filter

Round 1

Reviewer 1 Report

The noise reduction method of nanopore based on wavelet and Kalman filter is shown in this paper. 

Nanopore detection technology is relevant tool for single molecule experiments, but the relatively high background noise affects the data analysis. In this paper nanopore signal noise reduction method based on wavelet transform and Kalman filter is proposed.

In the manuscript was noted that the wavelet mode maxima method effectively improves the estimation accuracy of Kalman filter. The measured data shows that the method proposed in this paper reduces the standard deviation of the background noise, which is better than the traditional Kalman filter. 

Good idea.

References have been well selected the content of the paper, but it would be good to supplement this work by more newer references.

 

Some suggestion follows:

- It would be good to rewrite the conclusions to for better understanding of the text,

- It would be good to supplement this work by wider conclusions to allow easier understanding of the presented problem.

- The references must be completed with more items.

- In Conclusion and disscussion chapter it was wtite: "The above conclusion concludes that the ..." In my opinion, the conclusions should follow from the previous discussion. Thus, the obtained test results should be discussed first.

Author Response

Revisions have been made as requested by the reviewers and details are in the uploaded attachments, thank you!

Author Response File: Author Response.docx

Reviewer 2 Report

Authors introduce noise-reduction-technique based on wavelet and kalman filter for noisy IgG nanopore current  (i.e. noisy current signals generated by molecules passage through nanopores).The manuscript is grammatically well-written and of minimum typos.    Here are my remarks:   1. Novelty The idea of usage wavelet transform together with Kalman filter for denoising is not new, since several papers were already published over last 17 years in wide range of fields. SHAO, Yu; CHANG, Chip-Hong. A Kalman filter based on wavelet filter-bank and psychoacoustic modeling for speech enhancement. In: 2006 IEEE International Symposium on Circuits and Systems. IEEE, 2006. p. 4 pp. WU, Liguo, et al. Study of GPS data de-noising method based on Wavelet and Kalman filtering. In: 2011 Third Pacific-Asia Conference on Circuits, Communications and System (PACCS). IEEE, 2011. p. 1-3. GILDA, Sankalp; SLEPIAN, Zachary. Automatic Kalman-filter-based wavelet shrinkage denoising of 1D stellar spectra. Monthly Notices of the Royal Astronomical Society, 2019, 490.4: 5249-5269. ... The manuscript is of lack of state-of-the-art in this direction (Kalman filter and wavelet transform) and did not discuss signal-processing techniques for noise reduction in nanopores detections. Please address this issue properly.   2. clarity of algorithm description  The every journal paper should be a guide for remaking the experiments or algorithms. - I see the issues in algorithm description (e.g. description of every variable /what is lambda ? /, unsufficient description of algorithm, it it a two-step algorithm ?) - Why decomposition level is 5 and not 4? How were these parameters found out ? - Why authors do not use in the first step other variants of wavelet denoising ?   3. experiment setup and its evaluation - Authors use data from one-time experiment. If the conditions of experiment are different, how the proposed technique will be affected? - Authors should choose a suitable indicator (RMS and SNR are fine) to evaluate wavelet denoising as well as Kalman filtering.     Formal remarks All non-schematic figures should have x and y axes and axis labels that contains a quantities with corresponding units, even dimensionless, e.g. Counts [-] Tables  - Quantities should be given with corresponding units, even dimensionless, e.g. SNR [dB] Legend should not contain chinese letters.

Author Response

Revisions have been made as requested by the reviewers and details are in the uploaded attachments, thank you!

Author Response File: Author Response.docx

Round 2

Reviewer 1 Report

The Authors took into account all comments and made the necessary corrections in the manuscript. 

I believe there is no need for further revisions and the manuscript can be published in present form.

Author Response

Thank you for your attention to this article and I wish you good health, good work and all the best!

Reviewer 2 Report

Authors improved their manuscript greatly, unfortunately some issues should be addressed. I have several mandatory remarks:   - (mandatory) please add your modified explanation (Response 1) at the end of the Introduction section "The main innovation of this paper lies in the combination of wavelet transform and traditional Kalman, but not only in the combination, mainly through the study of the traditional Kalman filtering algorithm for processing nanopore signals found that the noise in the signal has a large impact on the progress of the Kalman estimation data, and may affect the biomolecule characterization, so this paper uses the better wavelet transform method to reduce noise, improve the estimation accuracy of Kalman filtering, and provide a guarantee for the subsequent biomolecule characterization."   - (mandatory) Please add to conclusion your thoughts (Response 3) on "algorithm resistance on external conditions. It is very important for the readers "the external conditions of the experiment will not affect the wide applicability of the algorithm, but for different biomolecule signal processing, the internal algorithm needs to adjust the parameters according to the signal conditions to achieve the optimal noise reduction effect."   - (mandatory) Please add description of all quantities in equations (1-3). What is capital psi, capital phi, n, u ...     - (mandatory) Quantities in tables and in figures (7c 7d) should be given with corresponding units, even dimensionless, e.g. SNR [dB]. This is still missing.

Author Response

Thank you for your attention to this article, the problems you mentioned I have been modified in the original text. I wish you good health, good work and all the best!

Author Response File: Author Response.docx