Literature DB >> 35796000

flowCut: An R package for automated removal of outlier events and flagging of files based on time versus fluorescence analysis.

Justin Meskas1, Daniel Yokosawa1, Sherrie Wang1,2, Gabriela C Segat1, Ryan Remy Brinkman1,3.   

Abstract

Technical artifacts such as clogging that occur during the data acquisition process of flow cytometry data can cause spurious events and fluorescence intensity shifting that impact the quality of the data and its analysis results. These events should be identified and potentially removed before being passed to the next stage of analysis. flowCut, an R package, automatically detects anomaly events in flow cytometry experiments and flags files for potential review. Its results are on par with manual analysis and it outperforms existing automated approaches.
© 2022 International Society for Advancement of Cytometry.

Entities:  

Keywords:  anomaly detection; bioinformatics; data acquisition; data cleaning; flow cytometry; outlier detection; quality checking

Year:  2022        PMID: 35796000     DOI: 10.1002/cyto.a.24670

Source DB:  PubMed          Journal:  Cytometry A        ISSN: 1552-4922            Impact factor:   4.714


  2 in total

1.  PeacoQC: Peak-based selection of high quality cytometry data.

Authors:  Annelies Emmaneel; Katrien Quintelier; Dorine Sichien; Paulina Rybakowska; Concepción Marañón; Marta E Alarcón-Riquelme; Gert Van Isterdael; Sofie Van Gassen; Yvan Saeys
Journal:  Cytometry A       Date:  2021-10-03       Impact factor: 4.714

2.  Lineage-coupled clonal capture identifies clonal evolution mechanisms and vulnerabilities of BRAFV600E inhibition resistance in melanoma.

Authors:  Ze-Yan Zhang; Yingwen Ding; Ravesanker Ezhilarasan; Tenzin Lhakhang; Qianghu Wang; Jie Yang; Aram S Modrek; Hua Zhang; Aristotelis Tsirigos; Andrew Futreal; Giulio F Draetta; Roel G W Verhaak; Erik P Sulman
Journal:  Cell Discov       Date:  2022-10-06       Impact factor: 38.079

  2 in total

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