CRUSTY: a versatile web platform for the rapid analysis and visualization of high-dimensional flow cytometry data

被引:0
|
作者
Simone Puccio
Giorgio Grillo
Giorgia Alvisi
Caterina Scirgolea
Giovanni Galletti
Emilia Maria Cristina Mazza
Arianna Consiglio
Gabriele De Simone
Flavio Licciulli
Enrico Lugli
机构
[1] IRCCS Humanitas Research Hospital,Laboratory of Translational Immunology
[2] UoS Milan,Institute of Genetic and Biomedical Research
[3] National Research Council,Institute for Biomedical Technologies
[4] National Research Council,School of Biological Sciences, Department of Molecular Biology
[5] Flow Cytometry Core,undefined
[6] IRCCS Humanitas Research Hospital,undefined
[7] University of California San Diego,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Flow cytometry (FCM) can investigate dozens of parameters from millions of cells and hundreds of specimens in a short time and at a reasonable cost, but the amount of data that is generated is considerable. Computational approaches are useful to identify novel subpopulations and molecular biomarkers, but generally require deep expertize in bioinformatics and the use of different platforms. To overcome these limitations, we introduce CRUSTY, an interactive, user-friendly webtool incorporating the most popular algorithms for FCM data analysis, and capable of visualizing graphical and tabular results and automatically generating publication-quality figures within minutes. CRUSTY also hosts an interactive interface for the exploration of results in real time. Thus, CRUSTY enables a large number of users to mine complex datasets and reduce the time required for data exploration and interpretation. CRUSTY is accessible at https://crusty.humanitas.it/.
引用
收藏
相关论文
共 50 条
  • [41] Analyzing high-dimensional cytometry data using FlowSOM
    Quintelier, Katrien
    Couckuyt, Artuur
    Emmaneel, Annelies
    Aerts, Joachim
    Saeys, Yvan
    Van Gassen, Sofie
    NATURE PROTOCOLS, 2021, 16 (08) : 3775 - 3801
  • [42] Algorithmic Tools for Mining High-Dimensional Cytometry Data
    Chester, Cariad
    Maecker, Holden T.
    JOURNAL OF IMMUNOLOGY, 2015, 195 (03): : 773 - 779
  • [43] Analyzing high-dimensional cytometry data using FlowSOM
    Katrien Quintelier
    Artuur Couckuyt
    Annelies Emmaneel
    Joachim Aerts
    Yvan Saeys
    Sofie Van Gassen
    Nature Protocols, 2021, 16 : 3775 - 3801
  • [44] Unveiling the power of high-dimensional cytometry data with cyCONDOR
    Kroeger, Charlotte
    Mueller, Sophie
    Leidner, Jacqueline
    Kroeber, Theresa
    Warnat-Herresthal, Stefanie
    Spintge, Jannis B.
    Zajac, Timo
    Frolov, Aleksej
    Carraro, Caterina
    Puccio, Simone
    Schultze, Joachim L.
    Pacht, Tal
    Beyer, Marc
    Bonaguro, Lorenzo
    EUROPEAN JOURNAL OF IMMUNOLOGY, 2024, 54 : 185 - 185
  • [45] High-dimensional data analysis with subspace comparison using matrix visualization
    Wang, Junpeng
    Liu, Xiaotong
    Shen, Han-Wei
    INFORMATION VISUALIZATION, 2019, 18 (01) : 94 - 109
  • [46] EmbedX: A Versatile, Efficient and Scalable Platform to Embed Both Graphs and High-Dimensional Sparse Data
    Zou, Yuanhang
    Ding, Zhihao
    Shi, Jieming
    Guo, Shuting
    Su, Chunchen
    Zhang, Yafei
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2023, 16 (12): : 3543 - 3556
  • [47] ExCYT: A Graphical User Interface for Streamlining Analysis of High-Dimensional Cytometry Data
    Sidhom, John-William
    Theodros, Debebe
    Murter, Benjamin
    Zarif, Jelani C.
    Ganguly, Sudipto
    Pardoll, Drew M.
    Baras, Alexander
    JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, 2019, (143):
  • [48] Visualization and Quantification of High-Dimensional Cytometry Data using Cytofast and the Upstream Clustering Methods FlowSOM and Cytosplore
    Beyrend, Guillaume
    Stam, Koen
    Ossendorp, Ferry
    Arens, Ramon
    JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, 2019, (154):
  • [49] Partial least squares: a versatile tool for the analysis of high-dimensional genomic data
    Boulesteix, Anne-Laure
    Strimmer, Korbinian
    BRIEFINGS IN BIOINFORMATICS, 2007, 8 (01) : 32 - 44
  • [50] Data visualization case studies for high-dimensional data validation
    Williams, Aaron R.
    STAT, 2021, 10 (01):