Please use this identifier to cite or link to this item: http://repository.i3l.ac.id/jspui/handle/123456789/1273
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dc.contributor.authorAustin, Felicia-
dc.date.accessioned2025-05-08T04:25:28Z-
dc.date.available2025-05-08T04:25:28Z-
dc.date.issued2025-01-31-
dc.identifier.urihttp://repository.i3l.ac.id/jspui/handle/123456789/1273-
dc.description.abstractPolygenic risk scores (PRS) has become one of the most marketable research topics as medicine focused more into personalized healthcare. By using PRS, an individual's gene can guide both the patient and the healthcare professionals in making decisions regarding themself. As such, many different workflows and tools have been developed over the years in an effort to make PRS calculation easier, while still maintaining a good, proper result. Such tools include plink2, prspipe, and PRSice-2. Although those tools have their own documentation, an adaptation to use them with real life data has its own challenges. Many of which were due to data limitation, which eliminates the possibility of it being used in this specific case such as in the case of prspipe and PRSice-2. Meanwhile, plink2 as the most promising tool was also limited due to the small amount of sample which causes a skewed result. Therefore, this report can only be used as a proof of exploration towards the various workflows with limited conclusion.en_US
dc.language.isoenen_US
dc.publisherIndonesia International Institute for Life-Sciencesen_US
dc.relation.ispartofseriesEP BI-010;EP107-
dc.subjectPolygenic Risk Scoreen_US
dc.subjectLinux pipelineen_US
dc.subjectplink2en_US
dc.titleExploring Polygenic Risk Score Calculation Pipelines Using Linux Command Line Interfaceen_US
dc.typeWorking Paperen_US
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