Wick, RR and Holt, KE. 2022. Predictors of assembly quality. [Online]. PLOS Computational Biology. Available from: https://doi.org/10.1371/journal.pcbi.1009802.s018
Wick, RR and Holt, KE. Predictors of assembly quality [Internet]. PLOS Computational Biology; 2022. Available from: https://doi.org/10.1371/journal.pcbi.1009802.s018
Wick, RR and Holt, KE (2022). Predictors of assembly quality. [Data Collection]. PLOS Computational Biology. https://doi.org/10.1371/journal.pcbi.1009802.s018
Description
Predictors of assembly quality, as outlined in a PLOS Computational Biology submission "Polypolish: Short-read polishing of long-read bacterial genome assemblies". For each of the 100 simulated-read genomes, a Kendall-rank correlation test was conducted using all available assemblies between the assembly's known identity and 10 different potential predictors.
| Data capture method | Unknown |
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| Date (Date published in a 3rd party system) | 24 January 2022 |
| Language(s) of written materials | English |
| Data Creators | Wick, RR and Holt, KE |
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| LSHTM Faculty/Department | Faculty of Infectious and Tropical Diseases > Department of Infection Biology |
| Participating Institutions | London School of Hygiene & Tropical Medicine, London, United Kingdom |
| Funders |
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| Date Deposited | 07 Mar 2022 11:47 |
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| Last Modified | 07 Mar 2022 11:47 |
| Publisher | PLOS Computational Biology |
