Using genomics, bioinformatics and statistics, herein we demonstrate the effect of statewide and nationwide quarantine on the introduction of SARS-CoV-2 variants of concern (VOC) in Hawai’i. To define the origins of introduced VOC, we analyzed 260 VOC sequences from Hawai’i, and 301,646 VOC sequences worldwide, deposited in the GenBank and global initiative on sharing all influenza data (GISAID), and constructed phylogenetic trees. The trees define the most recent common ancestor as the origin. Further, the multiple sequence alignment used to generate the phylogenetic trees identified the consensus single nucleotide polymorphisms in the VOC genomes. These consensus sequences allow for VOC comparison and identification of mutations of interest in relation to viral immune evasion and host immune activation. Of note is the P71L substitution within the E protein, the protein sensed by TLR2 to produce cytokines, found in the B.1.351 VOC may diminish the efficacy of some vaccines. Based on the phylogenetic trees, the B.1.1.7, B.1.351, B.1.427, and B.1.429 VOC have been introduced in Hawai’i multiple times since December 2020 from several definable geographic regions. From the first worldwide report of VOC in GenBank and GISAID, to the first arrival of VOC in Hawai’i, averages 320 days with quarantine, and 132 days without quarantine. As such, the effect of quarantine is shown to significantly affect the time to arrival of VOC in Hawai’i. Further, the collective 2020 quarantine of 43-states in the United States demonstrates a profound impact in delaying the arrival of VOC in states that did not practice quarantine, such as Utah. Our data demonstrates that at least 76% of all definable SARS-CoV-2 VOC have entered Hawai’i from California, with the B.1.351 variant in Hawai’i originating exclusively from the United Kingdom. These data provide a foundation for policy-makers and public-health officials to apply precision public health genomics to real-world policies such as mandatory screening and quarantine. Hawai’i has experienced unique epidemics within the coronavirus disease 2019 (COVID-19) pandemic, in that Pacific Islanders, which account for 4% of the population, once accounted for nearly 30% of COVID-19 cases Reviewers' comments:Reviewer's Responses to Questions  Comments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?  The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented. Reviewer #1: YesReviewer #2: Yes**********   2. Has the statistical analysis been performed appropriately and rigorously?   Reviewer #1: YesReviewer #2: Yes**********   3. Have the authors made all data underlying the findings in their manuscript fully available?PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.  The Reviewer #1: YesReviewer #2: Yes**********   4. Is the manuscript presented in an intelligible fashion and written in standard English?  PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes**********   5. Review Comments to the Author  Please use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. Reviewer #1: This paper focuses on analyzing the VOCs that have been found in Hawaií and performs an analysis of the VOC variants to determine their point of origin. The authors also analyze the case numbers during quarantine and post quarantine in an attempt to demonstrate the efficacy of quarantine in delaying the entry of VOC to Hawaií, which was, (unsurprisingly) confirmed through analysis and comparison with Utah.The strength of the paper is the thoroughness of the analysis of the genomic data available for the VOCs in Hawaii and the comparison to the VOCs worldwide from banked genomic data. The methods and the analysis of the genomic data is very well presented and explained.What I feel the authors could improve is the background information to help the general reader better understand the significance and impact of the data presented. In particular, I would suggest that the authors rewrite the introduction to describe the general epidemiological trends of COVID infection in Hawaií, and also provide more details of what is meant by ‘quarantine’ as this has different guidelines in different countries. This would then provide the readers with a better background heading into the core findings and be able to better appreciate the findings. In the intro line 52 to 63 reads like content better suited to the discussion than the introduction?I would also suggest that in terms of the discussion there are a few other points the authors may wish to briefly mention in the writing and discussion – it is of course of great epidemiological significance to identify the source of infection to understand the pattern of infection and global spread, however I would argue that the authors assertions (line 467) that the source of infection must be ascertained before steps can be taken may be overstating the case as by that time the case is already in, and it may be more appropriate to argue that understanding the origin of cases  may be a reason to look at the processes in that country or in the infection control measures in place in that country for review? With regard to line 367 where the authors have highlighted that the highest number came from California I would suggest inferring some suggestions as to why – did California have different regulations on COVID control? Or was it because more people entering Hawaií were from California? Ideas about this then provide more guidance to public health measures at appropriate points in the chain of transmission. In addition, while limiting case numbers is of paramount concern, economic and social considerations also are a factor in deciding on the measure to implement - meaning the data and statistics here are a key consideration, but they are not the only ones.Reviewer #2: dear author,this paper is much appreciable and it gives the origin and spread of variants of SARS Cov-2 in different areas.methods should have been simplified with flowchart or something. then it would be easy to reproduce by some other .**********   6. 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Unfortunately, at this time, it appears that the package usmap uses the GPL license, which is not compatible with our CC-BY 4.0 license. As such, please note the below prompts:A. Was the usmap package used for both Figure 2 and Figure 3?http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf):B. For any Figure that used the usmap package, we will require specific consent from the copyright holder to publish these images in PLOS ONE, under the CC BY 4.0 license. To seek permission from the copyright owner to publish your map figures under the specific Creative Commons Attribution License (CCAL), CC BY 4.0, please contact them with the following text and PLOS ONE Request for Permission form (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. 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A) Yes, the usmap package was used for both figure 2 and 3. We have removed all images generated with the usmap package and have replaced the images with those acquired from the recommended Natural Earth (_________________________________________________________________________Editor Comments 3 (07/15/2022):Comment 1:https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols. Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols.If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. 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For more information, see our copyright guidelines: We require you to either (1) present written permission from the copyright holder to publish these figures specifically under the CC BY 4.0 license, or (2) remove the figures from your submission:a. You may seek permission from the original copyright holder of Figure 2 to publish the content specifically under the CC BY 4.0 license. http://journals.plos.org/plosone/s/file?id=7c09/content-permission-form.pdf) and the following text:We recommend that you contact the original copyright holder with the Content Permission Form (http://creativecommons.org/licenses/by/4.0/). Please be aware that this license allows unrestricted use and distribution, even commercially, by third parties. Please reply and provide explicit written permission to publish XXX under a CC BY license and complete the attached form.”“I request permission for the open-access journal PLOS ONE to publish XXX under the Creative Commons Attribution License (CCAL) CC BY 4.0  remove the figure or ii) supply a replacement figure that complies with the CC BY 4.0 license. Please check copyright information on all replacement figures and update the figure caption with source information. If applicable, please specify in the figure caption text when a figure is similar but not identical to the original image and is therefore for illustrative purposes only.The following resources for replacing copyrighted map figures may be helpful:http://viewer.nationalmap.gov/viewer/USGS National Map Viewer (public domain): http://eol.jsc.nasa.gov/sseop/clickmap/The Gateway to Astronaut Photography of Earth (public domain): https://www.cia.gov/library/publications/the-world-factbook/index.html and https://www.cia.gov/library/publications/cia-maps-publications/index.htmlMaps at the CIA (public domain): http://earthobservatory.nasa.gov/NASA Earth Observatory (public domain): http://landsat.visibleearth.nasa.gov/Landsat: http://eros.usgs.gov/#USGS EROS (Earth Resources Observatory and Science (EROS) Center) (public domain): http://www.naturalearthdata.com/Natural Earth (public domain): Response 3:We thank the editor for this comment and recommendations. We have opted to replace the image and have produced the images ourselves using open-source R with usmap and ggplot2 packages._________________________________________________________________________Comment 4:3. Please review your reference list to ensure that it is complete and correct. If you have cited papers that have been retracted, please include the rationale for doing so in the manuscript text, or remove these references and replace them with relevant current references. Any changes to the reference list should be mentioned in the rebuttal letter that accompanies your revised manuscript. If you need to cite a retracted article, indicate the article’s retracted status in the References list and also include a citation and full reference for the retraction notice.Response 4:We thank the editor for this comment. All references have been either confirmed or updated.github.com/cov-lineages/pangolin6. O’Toole Á, Scher E, Underwood A, Jackson B, Hill V, McCrone J, et al. pangolin: lineage assignment in an emerging pandemic as an epidemiological tool. In: PANGO lineages [Internet]. 2021 [cited 11 Mar 2021]. Available: Has been published since our original submission and has been replaced with:6. O’Toole Á, Scher E, Underwood A, Jackson B, Hill V, McCrone JT, et al. Assignment of epidemiological lineages in an emerging pandemic using the pangolin tool. Virus Evolution. 2021;7: veab064. doi:10.1093/ve/veab064https://www.R-project.org/16. R Core Team. R: A language and environment for statistical ## computing. [Internet]. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available from: Has been updated to: https://www.R-project.org/16. R Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2020. Available: 17. Wickham H. ggplot2: Elegant Graphics for Data Analysis. 2nd ed. 2016. Cham: Springer International Publishing : Imprint: Springer; 2016. 1 p. (Use R!).Has been updated to:https://ggplot2.tidyverse.org17. Wickham H. ggplot2: Elegant Graphics for Data Analysis. Springer-Verlag New York; 2016. Available from: 28. Scobie H. Update on Emerging SARS-CoV-2 Variants and Vaccine Considerations. 2021 May 12;30.Has been updated to:https://www.cdc.gov/vaccines/acip/meetings/downloads/slides-2021-05-12/10-COVID-Scobie-508.pdf28. Scobie H. Update on Emerging SARS-CoV-2 Variants and Vaccine Considerations. 2021 May 12. Available from: 33. Jangra S, Ye C, Rathnasinghe R, Stadlbauer D, PVI study group, Krammer F, et al. The E484K mutation in the SARS-CoV-2 spike protein reduces but does not abolish neutralizing activity of human convalescent and post-vaccination sera. Infectious Diseases (except HIV/AIDS); 2021 Jan. doi:10.1101/2021.01.26.21250543Has been published since our original submission and has been replaced with:33. Jangra S, Ye C, Rathnasinghe R, Stadlbauer D, Personalized Virology Initiative study group, Krammer F, et al. SARS-CoV-2 spike E484K mutation reduces antibody neutralisation. Lancet Microbe. 2021;2: e283–e284. doi:10.1016/S2666-5247(21)00068-935. Deng X, Garcia-Knight MA, Khalid MM, Servellita V, Wang C, Morris MK, et al. Transmission, infectivity, and antibody neutralization of an emerging SARS-CoV-2 variant in California carrying a L452R spike protein mutation. medRxiv. 2021; 2021.03.07.21252647. doi:10.1101/2021.03.07.21252647Has been published since our original submission and has been replaced with:35. Deng X, Garcia-Knight MA, Khalid MM, Servellita V, Wang C, Morris MK, et al. Transmission, infectivity, and neutralization of a spike L452R SARS-CoV-2 variant. Cell. 2021;184: 3426-3437.e8. doi:10.1016/j.cell.2021.04.02536. Li Q, Wu J, Nie J, Zhang L, Hao H, Liu S, et al. The Impact of Mutations in SARS-CoV-2 Spike on Viral Infectivity and Antigenicity. Cell (Cambridge). 2020;182: 1284-1294.e9. doi:10.1016/j.cell.2020.07.012Has been updated to:36. Li Q, Wu J, Nie J, Zhang L, Hao H, Liu S, et al. The Impact of Mutations in SARS-CoV-2 Spike on Viral Infectivity and Antigenicity. Cell. 2020;182: 1284-1294.e9. doi:10.1016/j.cell.2020.07.01238. Aragón TJ, Newsom G. California Department of Public Health - Health Alert: Concerns re: the Use of Bamlanivimab Monotherapy in the Setting of SARS-CoV2 Variants. 2021; 4.Has been updated to:http://publichealth.lacounty.gov/eprp/lahan/alerts/CAHANBamlanivimabandSARSCoV2Variants.pdf38. Aragón TJ, Newsom G. California Department of Public Health - Health Alert: Concerns re: the Use of Bamlanivimab Monotherapy in the Setting of SARS-CoV2 Variants. 2021. Available from: The following has been removed due to being revoked:39. Moruf A. Fact Sheet For Health Care Providers Emergency Use Authorization (Eua) Of Bamlanivimab. 2021; 26._________________________________________________________________________[Note: HTML markup is below. Please do not edit.]Reviewers' comments:Reviewer's Responses to QuestionsComments to the Author1. Is the manuscript technically sound, and do the data support the conclusions?The manuscript must describe a technically sound piece of scientific research with data that supports the conclusions. Experiments must have been conducted rigorously, with appropriate controls, replication, and sample sizes. The conclusions must be drawn appropriately based on the data presented.Reviewer #1: YesReviewer #2: Yes2. Has the statistical analysis been performed appropriately and rigorously?Reviewer #1: YesReviewer #2: Yes3. Have the authors made all data underlying the findings in their manuscript fully available?The PLOS Data policy requires authors to make all data underlying the findings described in their manuscript fully available without restriction, with rare exception (please refer to the Data Availability Statement in the manuscript PDF file). The data should be provided as part of the manuscript or its supporting information, or deposited to a public repository. For example, in addition to summary statistics, the data points behind means, medians and variance measures should be available. If there are restrictions on publicly sharing data—e.g. participant privacy or use of data from a third party—those must be specified.Reviewer #1: YesReviewer #2: Yes4. Is the manuscript presented in an intelligible fashion and written in standard English?PLOS ONE does not copyedit accepted manuscripts, so the language in submitted articles must be clear, correct, and unambiguous. Any typographical or grammatical errors should be corrected at revision, so please note any specific errors here.Reviewer #1: YesReviewer #2: Yes5. Review Comments to the AuthorPlease use the space provided to explain your answers to the questions above. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. _________________________________________________________________________Reviewer 1:Comment 1:Reviewer #1: This paper focuses on analyzing the VOCs that have been found in Hawaií and performs an analysis of the VOC variants to determine their point of origin. The authors also analyze the case numbers during quarantine and post quarantine in an attempt to demonstrate the efficacy of quarantine in delaying the entry of VOC to Hawaií, which was, (unsurprisingly) confirmed through analysis and comparison with Utah.The strength of the paper is the thoroughness of the analysis of the genomic data available for the VOCs in Hawaii and the comparison to the VOCs worldwide from banked genomic data. The methods and the analysis of the genomic data is very well presented and explained.Response 1:We thank the reviewer for these comments._________________________________________________________________________Comment 2:What I feel the authors could improve is the background information to help the general reader better understand the significance and impact of the data presented. In particular, I would suggest that the authors rewrite the introduction to describe the general epidemiological trends of COVID infection in Hawaií, and also provide more details of what is meant by ‘quarantine’ as this has different guidelines in different countries. This would then provide the readers with a better background heading into the core findings and be able to better appreciate the findings. In the intro line 52 to 63 reads like content better suited to the discussion than the introduction?Response 2:We thank the reviewer for these comments. In the revised manuscript, lines 52 to 63 have been moved to the discussion and we have addressed the remaining comments as follows:“Hawaii has experienced unique epidemics within the coronavirus disease 2019 (COVID-19) pandemic, in that Pacific Islanders, which account for 4% of the population, once accounted for nearly 30% of COVID-19 cases.(1) Further, the Japanese population of Hawaii currently accounts for 6% of the population and experiences 15% of COVID-19 cases. White persons, in contrast, account for 37% of the population and 25% of the cases.(2) As such, a heightened need exists to understand SARS-CoV-2 introduction into Hawaii and the effect of public policy measures. Early in the pandemic, in an attempt to control the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), Hawaii, like 42 other states in the United States, implemented a quarantine defined by “Stay-at-Home” orders. State-at-Home orders directed residents to stay inside homes except for essential needs and closed operations of non-essential businesses.(3) In addition to this public policy, more than 22,300 SARS-CoV-2 sequences submitted to GISAID and GenBank originate from Hawaii to facilitate further studies.”_________________________________________________________________________Comment 3:I would also suggest that in terms of the discussion there are a few other points the authors may wish to briefly mention in the writing and discussion – it is of course of great epidemiological significance to identify the source of infection to understand the pattern of infection and global spread, however I would argue that the authors assertions (line 467) that the source of infection must be ascertained before steps can be taken may be overstating the case as by that time the case is already in, and it may be more appropriate to argue that understanding the origin of cases  may be a reason to look at the processes in that country or in the infection control measures in place in that country for review? Response 3:We thank the reviewer for this discussion and argument. We have made the statement less assertive and included the reasoning provided in this comment in the revised manuscript as follows: “Policy-makers should first ascertain the source of the spread before they can control and limit the spread of future VOC. By understanding the source responsible for the highest number of cases, policy-makers can look at interactions between that area and the host area, the policies in that area, identify the reasons for the spread, and address those reasons with appropriate measures both in the present and in future COVID-19 waves.”_________________________________________________________________________Comment 4:With regard to line 367 where the authors have highlighted that the highest number came from California I would suggest inferring some suggestions as to why – did California have different regulations on COVID control? Or was it because more people entering Hawaií were from California? Ideas about this then provide more guidance to public health measures at appropriate points in the chain of transmission. In addition, while limiting case numbers is of paramount concern, economic and social considerations also are a factor in deciding on the measure to implement - meaning the data and statistics here are a key consideration, but they are not the only ones.Response 4:We thank the reviewer for this comment and suggestion. We have addressed this in the revised manuscript as follows:In 2020, 27% of all travelers to Hawai’i originated from California, with 53% coming from the West Coast. Further, Hawai’i residents traveled to the West Coast, specifically Las Vegas, Nevada. However, the following is additional information:“From the analysis of the SARS-CoV-2 sequence data, a policy-maker could reasonably consider focusing on additional screening, contact tracing, and quarantine efforts among visitors and residents arriving from and traveling to the West Coast of the continental United States. There are several possible reasons for this vast majority of SARS-COV-2 influx from the US West Coast. In 2020, 27% of all travelers to Hawaii originated from California, with 53% coming from the West Coast. California's biggest domestic traveling demographic is in-state travel, meaning that the state likely spreads SARS-CoV-2 efficiently and uniformly within California.(44) Second, Hawaii residents traveling to the West Coast and returning home once infected with the virus. The first case of COVID-19 in Hawaii and the first case of the Delta variant were brought to Hawaii by residents (both vaccinated and unvaccinated) returning from travel .(45–47) Additionally, 62% of early cases in Hawaii were in either visitors to Hawaii or returning residents.(47) There are presumably additional factors that participated in the 76% of SARS-CoV-2 VOC attributable to California. Regardless, policymakers must evaluate these possible collective factors and social and economic implications together to determine the appropriate public-policy action.” _________________________________________________________________________Reviewer 2:Reviewer #2: dear author,Comment 1:this paper is much appreciable and it gives the origin and spread of variants of SARS Cov-2 in different areas.Response 1:We thank the reviewer for this comment. _________________________________________________________________________Comment 2:methods should have been simplified with flowchart or something. then it would be easy to reproduce by some other .Response 2:We thank the reviewer for this comment and have added a flowchart as a figure and have uploaded the method to protocols.io. _________________________________________________________________________AttachmentRebuttal_09.26.2022.docxSubmitted filename: Click here for additional data file. 15 Nov 2022Genomic Analysis of SARS-CoV-2 Variants of Concern Circulating in Hawai’i to Facilitate Public-Health PoliciesPONE-D-21-19856R1Dear Dr. Maison,We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements.Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication.http://www.editorialmanager.com/pone/, click the 'Update My Information' link at the top of the page, and double check that your user information is up-to-date. If you have any billing related questions, please contact our Author Billing department directly at authorbilling@plos.org.An invoice for payment will follow shortly after the formal acceptance. To ensure an efficient process, please log into Editorial Manager at onepress@plos.org.If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact Kind regards,Ming ZhangAcademic EditorPLOS ONEAdditional Editor Comments :Reviewers' comments: 21 Nov 2022PONE-D-21-19856R1 Genomic Analysis of SARS-CoV-2 Variants of Concern Circulating in Hawai’i to Facilitate Public-Health Policies Dear Dr. Maison:I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now with our production department. onepress@plos.org.If your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information please contact plosone@plos.org. 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Chromatin loops are an essential factor in the structural organization of the genome; however, their detection in Hi-C interaction matrices is a challenging and compute-intensive task. The approach presented here, integrated into the HiCExplorer software, shows a chromatin loop detection algorithm that applies a strict candidate selection based on continuous negative binomial distributions and performs a Wilcoxon rank-sum test to detect enriched Hi-C interactions.HiCExplorer’s loop detection has a high detection rate and accuracy. It is the fastest available CPU implementation and utilizes all threads offered by modern multicore platforms.in situ Hi-C data contain a large amount of noise; achieving better agreement between loop calling algorithms will require cleaner Hi-C data and therefore future improvements to the experimental methods that generate the data.HiCExplorer’s method to detect loops by using a continuous negative binomial function combined with the donut approach from HiCCUPS leads to reliable and fast computation of loops. All the loop-calling algorithms investigated provide differing results, which intersect by  HiCCUPS is part of the software Juicer,1 and the implementation requires a general-purpose GPU (GPGPU), which imposes a barrier for users without access to Nvidia GPUs. However, an experimental CPU-based implementation has also been released. Algorithms such as iterative correction and eigenvector decomposition (ICE) ; German Federal Ministry of Education and Research [031 L0101C de.NBI-epi awarded to B.G.]. R.B. was supported by the German Research Foundation (DFG) under Germany’s Excellence Strategy (CIBSS–EXC-2189–Project ID 390939984). We acknowledge support by the Open Access Publication Fund of the University of Freiburg for contributing to the publication fees.J.W. designed and implemented the presented algorithm and wrote the manuscript. R.B. contributed to the manuscript. B.G. contributed to the manuscript.giac061_GIGA-D-21-00069_Original_SubmissionClick here for additional data file.giac061_GIGA-D-21-00069_Revision_1Click here for additional data file.giac061_GIGA-D-21-00069_Revision_2Click here for additional data file.giac061_GIGA-D-21-00069_Revision_3Click here for additional data file.giac061_GIGA-D-21-00069_Revision_4Click here for additional data file.giac061_Response_to_Reviewer_Comments_Original_SubmissionClick here for additional data file.giac061_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giac061_Response_to_Reviewer_Comments_Revision_2Click here for additional data file.giac061_Reviewer_1_Report_Original_SubmissionBorbala Mifsud -- 3/22/2021 ReviewedClick here for additional data file.giac061_Reviewer_1_Report_Revision_1Borbala Mifsud -- 7/5/2021 ReviewedClick here for additional data file.giac061_Reviewer_2_Report_Original_SubmissionFeng Yue -- 4/4/2021 ReviewedClick here for additional data file.giac061_Reviewer_2_Report_Revision_1Feng Yue -- 7/19/2021 ReviewedClick here for additional data file.giac061_Reviewer_3_Report_Revision_2Aleksandra PÄ™kowska -- 11/23/2021 ReviewedClick here for additional data file.giac061_Supplemental_FilesClick here for additional data file.


That is, how many changes and options should a sequence script allow before the more efficient choice is to branch out into multiple scripts.•Efforts in Accessible MRI can use the data, acquired using open-source sequences on major commercial scanners, as a reference point for experiments using the same sequences on new hardware.1See 1.11.1.1In the main folder (developer_main_site/IRSE), the sequence implementation is presented in a Jupyter notebook (write_irse_interleaved_split_grad.ipynb). In addition, a developer PDF form (IRSE_DEV_QUALITATIVE.pdf) includes information on the test experiment including sequence parameters, hardware setup, example image, image quality measures, and safety metrics.x'' and “ky”. Reconstructed images are included as figures .The simulation information (developer_main_site/IRSE/sim) provides phantom models  where the map dimensions are the “x” and “y'' spatial indices and simulated k-space signals  with dimensions “kThe acquisition folder (developer_main_site/IRSE/acq) includes the tested sequence file (irse_pypulseq_colab_256_TI150_neg4.4.seq), the randomized slice order (irse_sl_order.mat), and raw data from two repetitions from the same sequence  where the data dimensions are “samples”, “channels”, and “readouts”, in that order. In addition, the acquisition details are listed in a sheet (irse_acq_info.xlsx).In the reconstruction folder (developer_main_site/IRSE/recon), we include the reconstruction script (reconstruct_images.m) as well as the reconstructed images (images_combined.mat) and montage figure (irse_pulseq_montage.png). Image quality metrics (irse_metrics.mat) and ACR test results (ACR_METRICS_IRSE.xlsx) 1.1.2Similar to 1.1.1, we present in the main folder (developer_main_site/TSE) the sequence implementation (write_tse.ipynb) and the developer PDF form (TSE_DEV_QUALITATIVE.pdf). The simulation folder (developer_main_site/TSE/sim) includes equivalent phantoms , simulated images  and figures . In addition to the sequence file (tse_ms_TR3000ms_TE50ms_4echoes.seq), the raw data , and the acquisition details (tse_acq_info.xlsx), the acquisition folder (developer_main_site/TSE/acq) also includes the multi-echo phase encoding order (tse_pe_info.mat) with dimensions “number of echoes” and “number of excitations”. Lastly, the reconstruction folder (developer_main_site/TSE/recon) covers the equivalent files as in 1.1.1 .1.1.31 map and the acquisition details (irse_t1_acq_info.xlsx). Raw data is provided as ten separate files at different Tis .The sequence implementation (write_irse_interleaved_split_grad.ipynb) and documentation PDF (IRSE_DEV_QUANTITATIVE.pdf) are provided like above. Acquisition data (developer_main_site/IRSE_T1_mapping/acq) includes ten sequence files  with different inversion times see  used to The reconstruction folder (developer_main_site/IRSE_T1_mapping/recon) includes a reconstruction script (reconstruct_T1_mapping_images.m), the original and low-pass filtered reconstructed images , and the montage of all ten filtered images (T1_mapping_images_filtered_montage.png).1 mapping MATLAB code: the function for creating a regression curve following the T1 signal model (createFitT1.m) and the script that takes in filtered images and generates a T1 map (T1Mapping.m). The output map is given in units of seconds in two versions, generated from either the original or the filtered T1 images . The filtered image is shown in a figure after adjusting the display to eliminate the phantom background (T1_map_cleaned.png). Region-Of-Interest (ROI) values for the individual T1 spheres are given in a separate file (t1_by_sphere_filtered.mat).The analysis data (developer_main_site/IRSE_T1_mapping/ana) includes the T1.1.42 mapping (tse_multiecho_NIST_t2_sag.seq), the acquisition details (tse_t2_acq_info.xlsx), and the raw data (T2_mapping_raw_data.mat). In the reconstruction folder, equivalent script, data, and figure are provided of the 23 T2 mapping images, each reconstructed from samples at the same echo number and therefore the same TE . The analysis folder contains analogous mapping scripts , two T2 maps generated from original and filtered data  where the latter uses only the 5th to 23rd echoes to best capture the most T2 values imaged, the cleaned T2 map figure (T2_map_cleaned.png), and the ROI statistics (T2_by_sphere_filtered.mat).Similar documentation (TSE_DEV_QUANTITATIVE.pdf) and sequence notebook (write_tse_t2_mapping.ipynb) are included in the main folder (developer_main_site/TSE_T2_mapping). Acquisition data includes the single multi-echo TSE sequence with 23 echoes for variable TE T1.21.2.1The “IRSE_ACR” folder contains the raw data (raw_data_irse_second_site.mat), the image montage (IRSE_images_second_site.png), and the filled user form documenting the steps performed and user feedback (IRSE_USER_QUALITATIVE.pdf).1.2.2The “TSE_ACR” folder contains the equivalent raw data (raw_data_tse_second_site.mat), image figure (TSE_images_second_site.png), and user form (TSE_USER_QUALITATIVE.pdf). It also provides the phase encoding order (pe_info.mat).1.2.31 map  as well as the user form (IRSE_USER_QUANTITATIVE.pdf) are included.Eight raw data files are provided for the different TIs . The reconstructed images and T1.2.4Similarly, the raw data (TSE_T2mapping_t2sph_second_site.mat) and reconstructed images (T2_mapping_images_second_site.mat) are included, in addition to the map figure (T2map_second_site.png) and the user form (TSE_USER_QUANTITATIVE.pdf).1.3The folder (documentation_templates) contains the empty developer and user forms  for documenting test experiments in the proposed sequence validation framework 22.1Two classic MRI sequences were implemented in the multi-vendor, open-source Pulseq format 2.21/T2 relaxation times, that make up a numerical phantom. When exposed to temporally and spatially varying magnetic fields such as those defined by a pulse sequence program, the isochromat's magnetization vector evolves according to its initial condition, innate parameters, and the external driving fields. A numerical library is used to solve the differential equations. In the end, the detectable signals from the transverse magnetization are added up across all isochromats in a phantom to generate the raw MRI signal.Lower resolution numerical simulation based on the Bloch equations All simulations were performed on a Windows 10 operating system with an Intel(R) Core i7–8650 U CPU. Specific parameters used for the simulation were: FOV = 250 mm, slice thickness = 5 mm; TR = 4500 ms, TI = 200 ms, and TE = 10 ms for IRSE; TR = 4500 ms and TE = 10 ms for TSE.2.31/T2 spheres.Experiment parameters are shown in 2.41: 2: 1/T2 maps, small sphere-wise ROIs were manually selected to ensure only interior voxels are used. For each ROI, the mean and standard deviation of T1/T2 values were computed.For each mapping experiment, the corresponding signal equation  and Structural Similarity Index Measure (SSIM) 2.5The open-source sar4seq library was used to generate predicted time-averaged RF power and Specific Absorption Rate (SAR) for each sequence ,14. At aOur work did not involve human or other animal subjects and adheres to ethics in publishing standards.Gehua Tong: Formal analysis, Investigation, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing. Andreia S. Gaspar: Investigation, Validation, Visualization. Enlin Qian: Methodology, Software. Keerthi Sravan Ravi: Software. John Thomas Vaughan: Writing – review & editing. Rita G. Nunes: Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization. Sairam Geethanath: Conceptualization, Funding acquisition, Methodology, Project administration, Resources, Software, Supervision, Writing – review & editing.The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.


This article provides a pooled cross-sectional sample of Chilean households from 4 survey waves . The data has information on the demographics of the household, labor participation and occupation, savings rates, plus wealth of different sources. The data is available in both Excel and Stata formats. It is an important data for the study of savings, wages, pensions and wealth inequality. The dataset consists of demographics , labor market information , savings rates, and expected wealth components . The dataset includes 33,538 households from the 1997, 2007, 2012 and 2017 waves of the Chilean Family Expenditures Survey. The variables include Household identifier variables and population weights, Demographic variables , Work and income variables, Savings rates and consumption flows variables, Ratios of household wealth as a fraction of permanent household income, Betas for the linear correlation between unemployment risk and income volatility of the different 538 worker types with the aggregate consumption kernel pricing returns and the pension fund returns.Household identifier variables and population weights –hogar “household identifier of each EPF wave”folio_hogar “household identifier for the pooled cross-section of all the EPF waves”year “Year of the EPF Survey wave”factor_all “expansion factor (population weight) of the household in the survey”id “group cluster identifier”Demographic variables  –sexo “Gender of the household head ”edad “age (in years) of the household head”educ “education: elementary, secondary, university”educ_ecf “Education level of the respondent (only 2017 wave)”, with values 1 “Elementary education” 2 “Secondary education” 3 “Technical or Some college” 4 “College education” 5 “Post-graduate education”ocup_female_spouse “female partner of the household is employed”couple_d “household has a couple among its members”d_child “dummy for whether the household has a child”num_sen “dummy for whether the household has a senior citizen (above age 65) among its members”Work and income variables –ILFP “dummy for whether the main income of the household comes from informal employment”dummy_region “dummy for whether the household lives in regions outside of the Metropolitan Capital region”quintile_h “household national income quintile”ytoth “log of the total household permanent income (monthly)”sd_ln_inc_sect “annual standard deviation of the household labor income”unemp_sect “unemployment risk of the household”Savings rates and consumption flows variables –CBeta “fraction of wealth that should be consumed each year in a standard life cycle model”SRate “ratio of the current saving rate in terms of the permanent income”SRatePI “ratio of the permanent saving rate in terms of the permanent income”aggSRate “ratio of the total current saving rate in terms of the permanent income”aggSRatePI “ratio of the total permanent saving rate in terms of the permanent income”Ratios of household wealth as a fraction of permanent household income –Rytoth_c “Household income surprise”R_TotalWI_hh “Discounted total wealth”R_PW2I_hh “Discounted total pension wealth”R_FE_hh “Discounted labor earnings wealth”R_PW2I_hh_NoSy “Discounted contributory pension wealth”R_PW2I_APS “Discounted solidarity pension wealth”R_PWI_hh_past “Discounted current contributory pension wealth”R_PWI_hh_NoSy “Discounted contributory pension wealth”R_FENL_hh “Discounted non labor earnings wealth”R_FErent “Discounted rent wealth”R_FEtransfers “Discounted transfers wealth”R_FEfinassets “Discounted financial income wealth”Betas for the linear correlation between unemployment risk and income volatility of the different 538 worker types with the aggregate consumption kernel pricing returns and the pension fund returns –BetaPF_unemployed “Beta between the occupational unemployment with the Pension Fund real rate of return”BetaPF_sd_ln_ing_tot_ocup3 “Beta between the occupational income volatility with the Pension Fund real rate of return”Beta_unemployed “Beta between the occupational unemployment with the Consumption Pricing Kernel real rate of return”Beta_sd_ln_ing_tot_ocup3 “Beta between the occupational income volatility with the Consumption Pricing Kernel real rate of return”This is the list of variables available in the dataset:2The data consists of demographics, labor earnings and risk  and a simulation of the future contributory pension wealth plus public solidarity benefits for a sample of Chilean households Madeira . The modEncuesta de Presupuestos Familiares, hence on EPF) between 1997 until 2017. The dynamics of labor force participation, formal versus informal work and unemployment are calibrated from the Chilean Employment Survey , according to 538 workers’ types which are obtained from the multivariate vector of the workers’ sex, age, education, industry and region  the raw data of all the EPF and ENE surveys from the website of the Chilean Institute of National Statistics.https://www.ine.cl/estadisticas/sociales/mercado-laboral/ocupacion-y-desocupacion.ENE: https://www.ine.cl/estadisticas/sociales/ingresos-y-gastos/encuesta-de-presupuestos-familiares.EPF:The applied model that was calibrated from the raw data is explained in detail in the online file “Methodology.pdf”. The codes used to create the variables are explained in detail in the file README_JIMF_Codes_Summary.docx and CODES_JIMF.zip includes all the 45 Stata software codes used in the article. These files are publicly available with the data in the repository Mendeley Data.The online file in Mendeley Data CODES_JIMF.zip includes all the software codes with detailed comments on the methods used inside each code. Here I provide a brief summary of those codes. The “M_EPF_analysis.do” do file replicates the analysis of the article, by calling all the algorithms and doing each code in sequenced steps until all the data formatting and analysis is completed.The codes pctile_wgts.do, mean_wgts.do, and linear_reg_impute3.do create conditional group percentiles, mean values and imputations for missing values in the micro survey data.A second set of codes formats the Income and Employment Survey creating unemployment risk and income volatility statistics for 538 worker types for the period 1990 until 2017, with worker types given by gender, education, region, industry of occupation, age, income quintile. These codes include: esi_format.do , panel_esi_allyrs_FLP.do (formats rotating samples between 2 years for the ESI workers in the labor force), panel_esi_ILFP.do , panel_esi_income_growth0.do , layoff_jobfind0.do , income_shock0.do , p_income.do , Consumption_WageVolatility.do : EPF_2017.do, EPF_2017_DurSDurNDur_Tot.do, format_epf_1997.do, format_epf_2007.do, format_epf_2012.do, format_epf_2017.do // It formats the EPF 2017 data with the same variables and formats of other years. The code format_epf_all.do joins all the EPF waves.A fourth set of codes joins the EPF data with the Employment and Income Survey worker type statistics for each of the 538 worker types across survey waves. The codes then estimate past and expected future pension contributions for each worker. This set of codes includes: EPF_labor_risk_vintage.do, EPF_all_LFP_ILFP_FE_PW_PWpast.do, income_potential.do, import_FE_PW_PW_past.do, generate_FE_FENL_PW_PWpast_TW_hh.do, generate_log_Wealth.do, Pension_tope_income.do.A fifth set of codes calibrates the pension system parameters for Chile in previous years, the pension withdrawals , the current policy reforms in 2022, and the counterfactual scenarios for the future reforms. This set of codes includes: Ingreso_bruto.do, Pension_income.do, Pension_PBS.do, Pension_PGU.do, Pension_PBS_2019.do, Pension_PBS_2008.do, Pension_PBS_PASIS.do, Pension_PASIS.do, Pension_Contr_APS_total.do, Pension_Reparto.do, Pension_Future.do, Retiro_AFP.do, PensionReformsFormat.do, predictLS_old_new1.do.The sixth set of codes analyses the data and providing the results in Madeira https://data.mendeley.com/datasets/dyp8yr2sr2/1.All the methods (in Stata do-files), theoretical methodology, and the datasets are published online with the Mendeley Data Madeira : https:/Carlos Madeira: Conceptualization, Methodology, Software, Validation, Formal analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization, Supervision, Project administration, Funding acquisition.The author declares that he has no known competing financial interests or personal relationships which have or could be perceived to have influenced the work reported in this article. I received no funding from any institution besides my employer which is the Central Bank of Chile. Furthermore, there are no patents or impediments to publication, including the timing of publication, with respect to the intellectual property of the article or the associated dataset.


Reproducibility of liquid chromatography separation is limited by retention time drift. As a result, measured signals lack correspondence over replicates of the liquid chromatography–mass spectrometry (LC-MS) experiments. Correction of these errors is named retention time alignment and needs to be performed before further quantitative analysis. Despite the availability of numerous alignment algorithms, their accuracy is limited .We present the Alignstein, an algorithm for LC-MS retention time alignment. It correctly finds correspondence even for swapped signals. To achieve this, we implemented the generalization of the Wasserstein distance to compare multidimensional features without any reduction of the information or dimension of the analyzed data. Moreover, Alignstein by design requires neither a reference sample nor prior signal identification. We validate the algorithm on publicly available benchmark datasets obtaining competitive results. Finally, we show that it can detect the information contained in the tandem mass spectrum by the spatial properties of chromatograms.https://github.com/grzsko/Alignstein.We show that the use of optimal transport effectively overcomes the limitations of existing algorithms for statistical analysis of mass spectrometry datasets. The algorithm’s source code is available at  Advances in liquid chromatography–mass spectrometry (LC-MS) have provided a remarkable insight into the functioning of the organisms, ranging from protein level , throughOne of these challenges is the correction of errors caused by retention time (RT) drift. It limits the reproducibility of LC separation, which is important for experiments usually acquired in many (even hundreds) replicates. RT drift became a significant obstacle with the emergence of high-performance chromatography (HPLC) and ultra-performance chromatography (UPLC) technologies. For example, nanoflow UPLC column separation takes a relatively long time, usually up to several hours. For these experiments, the elution time of peptides may vary up to 5 minutes  or even RT drift can be corrected by the experimental protocol only to a limited extent . It may RT drift requires a correction, usually named the RT alignment. It results in the correspondence of signals across runs . For exaHere, we present a novel alignment algorithm named Alignstein cf. Fig. . It findThis article is organized as follows. First, we characterize Alignstein and analyze how it deals with the swapped signals. Then, we validate the algorithm on publicly available benchmark datasets. Finally, we show the applicability of our approach to detecting corresponding biomarkers in differing samples.RT drift may swap the order of eluting analytes. In the proteomic experiment (cf. Methods), we analyzed that about 3% of all feature pairs are swapped between two chromatograms. Although many of the available algorithms properly align most signals, still they fail to resolve swaps.Most approaches to RT alignment are so-called warping algorithms—for example, OpenMS , MetAligm/z and average RT value, ignoring the information of isotopic envelope or feature span over the RT dimension. Without feature spatial characteristics and information of coeluting ions, elution order swaps are practically undetectable , including replicates of a sample with 0 µg/L BaP. For better readability, outliers over 200 seconds are omitted. Most RT differences are not greater than 10 seconds.Supplementary Fig. S3. Flow network for finding the optimal feature matching between n features of 1 chromatogram denoted by nodes L1, …, nL and m features from the other chromatogram, denoted by nodes R1, …, mR. Nonzero costs are described by edge labels. The cost between features iL and features jR is equal to the GWD between them. Additional node rT (“trash”) gives the possibility to not match the feature with cost c. Every edge has capacity equal to 1, except edge between S (source) and rT and edge between rT and T (sink) with capacities equal to max {0, s − n} and max {0, n − s}, respectively . As a result, we take all matchings .Supplementary Table S1. Detailed results for P1 set in CAAP comparison. P stands for alignment precision, R stands for alignment recall, and F stands for F-score.Supplementary Table S2. Detailed results for P2 set in CAAP comparison. P stands for alignment precision, R stands for alignment recall, and F stands for F-score.m/z: mass-to-charge ratio; RT: retention time; UPLC: ultra-performance liquid chromatography.BaP: benzo[a]pyrene; CAAP: Critical Assessment of Alignment Procedures; C60: fullerene; CID: collision-induced dissociation; DDA: data-dependent acquisition; GWD: generalized Wasserstein distance; HPLC: high-performance liquid chromatography; IR: identification recall; LC-MS: liquid chromatography–mass spectrometry; MS/MS: tandem mass spectrometry; The authors declare that they have no competing interests.G.S. was supported by Polish National Science Center grant number 2019/33/N/ST6/02949. A.G. and B.M. were supported by Polish National Science Center grant number 2018/29/B/ST6/00681.G.S. implemented and verified the algorithm. A.G. conceived the idea of the project and discussed the results. B.M. designed the algorithm and supervised the work. G.S., A.G., and B.M. cowrote the manuscript.giac101_GIGA-D-22-00149_Original_SubmissionClick here for additional data file.giac101_GIGA-D-22-00149_Revision_1Click here for additional data file.giac101_GIGA-D-22-00149_Revision_2Click here for additional data file.giac101_Response_to_Reviewer_Comments_Original_SubmissionClick here for additional data file.giac101_Response_to_Reviewer_Comments_Revision_1Click here for additional data file.giac101_Reviewer_1_Report_Original_SubmissionRobbin Bouwmeester -- 6/24/2022 ReviewedClick here for additional data file.giac101_Reviewer_1_Report_Revision_1Robbin Bouwmeester -- 8/25/2022 ReviewedClick here for additional data file.giac101_Reviewer_2_Report_Original_SubmissionKarl Mechtler -- 7/29/2022 ReviewedClick here for additional data file.giac101_Supplemental_FileClick here for additional data file.