Rapid QC-MS – Interactive Dashboard for Synchronous Mass Spectrometry Data Acquisition Quality Control Article Swipe
Wasim Sandhu
,
Ira J. Gray
,
Sarah Lin
,
Joshua E. Elias
,
Brian C. DeFelice
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.01.30.578059
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1101/2024.01.30.578059
Consistently collecting high quality liquid chromatography-coupled tandem mass spectrometry (LC-MS/MS) data is a time consuming hurdle for untargeted workflows. Analytical controls such as internal and biological standards are commonly included in high throughput workflows, helping researchers recognize low integrity specimens regardless of their biological source. However, evaluating these standards as data are collected has remained a considerable bottleneck – in both person hours and accuracy. Here we present Rapid QC-MS, an automated, interactive dashboard for assessing LC-MS/MS data quality. Minutes after a new data file is written, a browser-viewable dashboard is updated with quality control results spanning multiple performance dimensions such as instrument sensitivity, in-run retention time shifts, and mass accuracy drift. Rapid QC-MS provides interactive visualizations that help users recognize acute deviations in these performance metrics, as well as gradual drifts over periods of hours, days, months, or years. Rapid QC-MS is open-source, simple to install, and highly configurable. By integrating open source python libraries and widely used MS analysis software, it can adapt to any LC-MS/MS workflow. Rapid QC-MS runs locally and offers optional remote quality control by syncing with Google Drive. Furthermore, Rapid QC-MS can operate in a semiautonomous fashion, alerting users to specimens with potentially poor analytical integrity via frequently used messaging applications. Rapid QC-MS offers a fast, straightforward approach to help users collect high quality untargeted LC-MS/MS data by eliminating many of the most time consuming steps in manual data curation. Download for free: https://github.com/czbiohub-sf/Rapid-QC-MS
Related Topics
Concepts
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1101/2024.01.30.578059
- https://www.biorxiv.org/content/biorxiv/early/2024/02/01/2024.01.30.578059.full.pdf
- OA Status
- green
- Cited By
- 4
- References
- 23
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4391425972
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4391425972Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1101/2024.01.30.578059Digital Object Identifier
- Title
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Rapid QC-MS – Interactive Dashboard for Synchronous Mass Spectrometry Data Acquisition Quality ControlWork title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-01-31Full publication date if available
- Authors
-
Wasim Sandhu, Ira J. Gray, Sarah Lin, Joshua E. Elias, Brian C. DeFeliceList of authors in order
- Landing page
-
https://doi.org/10.1101/2024.01.30.578059Publisher landing page
- PDF URL
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https://www.biorxiv.org/content/biorxiv/early/2024/02/01/2024.01.30.578059.full.pdfDirect link to full text PDF
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YesWhether a free full text is available
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greenOpen access status per OpenAlex
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https://www.biorxiv.org/content/biorxiv/early/2024/02/01/2024.01.30.578059.full.pdfDirect OA link when available
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Workflow, Computer science, Python (programming language), Bottleneck, Dashboard, Open source, Software, Database, Operating system, Embedded systemTop concepts (fields/topics) attached by OpenAlex
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4Total citation count in OpenAlex
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2024: 4Per-year citation counts (last 5 years)
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.open | 152 |
| abstract_inverted_index.over | 132 |
| abstract_inverted_index.poor | 199 |
| abstract_inverted_index.runs | 171 |
| abstract_inverted_index.such | 21, 100 |
| abstract_inverted_index.that | 117 |
| abstract_inverted_index.time | 13, 106, 229 |
| abstract_inverted_index.used | 158, 204 |
| abstract_inverted_index.well | 128 |
| abstract_inverted_index.with | 92, 181, 197 |
| abstract_inverted_index.QC-MS | 113, 141, 170, 186, 208 |
| abstract_inverted_index.Rapid | 68, 112, 140, 169, 185, 207 |
| abstract_inverted_index.acute | 121 |
| abstract_inverted_index.adapt | 164 |
| abstract_inverted_index.after | 80 |
| abstract_inverted_index.days, | 136 |
| abstract_inverted_index.fast, | 211 |
| abstract_inverted_index.free: | 238 |
| abstract_inverted_index.hours | 62 |
| abstract_inverted_index.steps | 231 |
| abstract_inverted_index.their | 42 |
| abstract_inverted_index.these | 47, 124 |
| abstract_inverted_index.users | 119, 194, 216 |
| abstract_inverted_index.Drive. | 183 |
| abstract_inverted_index.Google | 182 |
| abstract_inverted_index.QC-MS, | 69 |
| abstract_inverted_index.drift. | 111 |
| abstract_inverted_index.drifts | 131 |
| abstract_inverted_index.highly | 148 |
| abstract_inverted_index.hours, | 135 |
| abstract_inverted_index.hurdle | 15 |
| abstract_inverted_index.in-run | 104 |
| abstract_inverted_index.liquid | 4 |
| abstract_inverted_index.manual | 233 |
| abstract_inverted_index.offers | 174, 209 |
| abstract_inverted_index.person | 61 |
| abstract_inverted_index.python | 154 |
| abstract_inverted_index.remote | 176 |
| abstract_inverted_index.simple | 144 |
| abstract_inverted_index.source | 153 |
| abstract_inverted_index.tandem | 6 |
| abstract_inverted_index.widely | 157 |
| abstract_inverted_index.years. | 139 |
| abstract_inverted_index.Minutes | 79 |
| abstract_inverted_index.collect | 217 |
| abstract_inverted_index.control | 94, 178 |
| abstract_inverted_index.gradual | 130 |
| abstract_inverted_index.helping | 34 |
| abstract_inverted_index.locally | 172 |
| abstract_inverted_index.months, | 137 |
| abstract_inverted_index.operate | 188 |
| abstract_inverted_index.periods | 133 |
| abstract_inverted_index.present | 67 |
| abstract_inverted_index.quality | 3, 93, 177, 219 |
| abstract_inverted_index.results | 95 |
| abstract_inverted_index.shifts, | 107 |
| abstract_inverted_index.source. | 44 |
| abstract_inverted_index.syncing | 180 |
| abstract_inverted_index.updated | 91 |
| abstract_inverted_index.Download | 236 |
| abstract_inverted_index.However, | 45 |
| abstract_inverted_index.LC-MS/MS | 76, 167, 221 |
| abstract_inverted_index.accuracy | 110 |
| abstract_inverted_index.alerting | 193 |
| abstract_inverted_index.analysis | 160 |
| abstract_inverted_index.approach | 213 |
| abstract_inverted_index.commonly | 28 |
| abstract_inverted_index.controls | 20 |
| abstract_inverted_index.fashion, | 192 |
| abstract_inverted_index.included | 29 |
| abstract_inverted_index.install, | 146 |
| abstract_inverted_index.internal | 23 |
| abstract_inverted_index.metrics, | 126 |
| abstract_inverted_index.multiple | 97 |
| abstract_inverted_index.optional | 175 |
| abstract_inverted_index.provides | 114 |
| abstract_inverted_index.quality. | 78 |
| abstract_inverted_index.remained | 54 |
| abstract_inverted_index.spanning | 96 |
| abstract_inverted_index.written, | 86 |
| abstract_inverted_index.accuracy. | 64 |
| abstract_inverted_index.assessing | 75 |
| abstract_inverted_index.collected | 52 |
| abstract_inverted_index.consuming | 14, 230 |
| abstract_inverted_index.curation. | 235 |
| abstract_inverted_index.dashboard | 73, 89 |
| abstract_inverted_index.integrity | 38, 201 |
| abstract_inverted_index.libraries | 155 |
| abstract_inverted_index.messaging | 205 |
| abstract_inverted_index.recognize | 36, 120 |
| abstract_inverted_index.retention | 105 |
| abstract_inverted_index.software, | 161 |
| abstract_inverted_index.specimens | 39, 196 |
| abstract_inverted_index.standards | 26, 48 |
| abstract_inverted_index.workflow. | 168 |
| abstract_inverted_index.(LC-MS/MS) | 9 |
| abstract_inverted_index.Analytical | 19 |
| abstract_inverted_index.analytical | 200 |
| abstract_inverted_index.automated, | 71 |
| abstract_inverted_index.biological | 25, 43 |
| abstract_inverted_index.bottleneck | 57 |
| abstract_inverted_index.collecting | 1 |
| abstract_inverted_index.deviations | 122 |
| abstract_inverted_index.dimensions | 99 |
| abstract_inverted_index.evaluating | 46 |
| abstract_inverted_index.frequently | 203 |
| abstract_inverted_index.instrument | 102 |
| abstract_inverted_index.regardless | 40 |
| abstract_inverted_index.throughput | 32 |
| abstract_inverted_index.untargeted | 17, 220 |
| abstract_inverted_index.workflows, | 33 |
| abstract_inverted_index.workflows. | 18 |
| abstract_inverted_index.eliminating | 224 |
| abstract_inverted_index.integrating | 151 |
| abstract_inverted_index.interactive | 72, 115 |
| abstract_inverted_index.performance | 98, 125 |
| abstract_inverted_index.potentially | 198 |
| abstract_inverted_index.researchers | 35 |
| abstract_inverted_index.Consistently | 0 |
| abstract_inverted_index.Furthermore, | 184 |
| abstract_inverted_index.considerable | 56 |
| abstract_inverted_index.open-source, | 143 |
| abstract_inverted_index.sensitivity, | 103 |
| abstract_inverted_index.spectrometry | 8 |
| abstract_inverted_index.applications. | 206 |
| abstract_inverted_index.configurable. | 149 |
| abstract_inverted_index.semiautonomous | 191 |
| abstract_inverted_index.visualizations | 116 |
| abstract_inverted_index.straightforward | 212 |
| abstract_inverted_index.browser-viewable | 88 |
| abstract_inverted_index.chromatography-coupled | 5 |
| abstract_inverted_index.https://github.com/czbiohub-sf/Rapid-QC-MS | 239 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 97 |
| corresponding_author_ids | https://openalex.org/A5014284483 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 5 |
| corresponding_institution_ids | https://openalex.org/I4210121800 |
| citation_normalized_percentile.value | 0.77806808 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |