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Fast and accurate diagnostics from highly multiplexed sequencing assays

Booeshaghi, A. Sina and Lubock, Nathan B. and Cooper, Aaron R. and Simpkins, Scott W. and Bloom, Joshua S. and Gehring, Jase and Luebbert, Laura and Kosuri, Sriram and Pachter, Lior (2020) Fast and accurate diagnostics from highly multiplexed sequencing assays. . (Unpublished) https://resolver.caltech.edu/CaltechAUTHORS:20200601-101849395

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Abstract

Scalable, inexpensive, accurate, and secure testing for SARS-CoV-2 infection is crucial for control of the novel coronavirus pandemic. Recently developed highly multiplexed sequencing assays that rely on high-throughput sequencing (HMSAs) can, in principle, meet these demands, and present promising alternatives to currently used RT-qPCR-based tests. However, the analysis and interpretation of HMSAs requires overcoming several computational and statistical challenges. Using recently acquired experimental data, we present and validate an accurate and fast computational testing workflow based on kallisto and bustools, that utilize robust statistical methods and fast, memory efficient algorithms for processing high-throughput sequencing data. We show that our workflow is effective at processing data from all recently proposed SARS-CoV-2 sequencing based diagnostic tests, and is generally applicable to any diagnostic HMSAs.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
https://doi.org/10.1101/2020.05.13.20100131DOIDiscussion Paper
https://github.com/pachterlab/BLCSBGLKP_2020Related ItemData/Code
ORCID:
AuthorORCID
Booeshaghi, A. Sina0000-0002-6442-4502
Lubock, Nathan B.0000-0001-8064-2465
Simpkins, Scott W.0000-0002-5997-2838
Bloom, Joshua S.0000-0002-7241-1648
Gehring, Jase0000-0002-3894-9495
Luebbert, Laura0000-0003-1379-2927
Kosuri, Sriram0000-0002-4661-0600
Pachter, Lior0000-0002-9164-6231
Additional Information:The copyright holder for this preprint is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY 4.0 International license. Posted May 16, 2020. Competing Interest Statement: ASB, JG, LL, and LP declare no conflicts of interest. SK, NLB, ARC, SWS and JSB are employees of Ocant, which developed SwabSeq. SwabSeq is released under the terms of the Octant Covid License. Funding Statement: None. Author Declarations: All relevant ethical guidelines have been followed; any necessary IRB and/or ethics committee approvals have been obtained and details of the IRB/oversight body are included in the manuscript. Yes. All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived. Yes. I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes. I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes.
Record Number:CaltechAUTHORS:20200601-101849395
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20200601-101849395
Official Citation:Fast and accurate diagnostics from highly multiplexed sequencing assays. A. Sina Booeshaghi, Nathan B. Lubock, Aaron R. Cooper, Scott W. Simpkins, Joshua S. Bloom, Jase Gehring, Laura Luebbert, Sriram Kosuri, Lior Pachter. medRxiv 2020.05.13.20100131; doi: https://doi.org/10.1101/2020.05.13.20100131
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:103585
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:01 Jun 2020 17:29
Last Modified:01 Jun 2020 17:29

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