Learning Single‐Cell Distances from Cytometry Data
Sign Up to like & getrecommendations! Published in 2019 at "Cytometry Part A"
DOI: 10.1002/cyto.a.23792
Abstract: Recent years have seen an increased interest in employing data analysis techniques for the automated identification of cell populations in the field of cytometry. These techniques highly depend on the use of a distance metric,… read more here.
Keywords: single cell; cell; distance metric; cytometry data ... See more keywords
PeacoQC: Peak‐based selection of high quality cytometry data
Sign Up to like & getrecommendations! Published in 2021 at "Cytometry Part A"
DOI: 10.1002/cyto.a.24501
Abstract: In cytometry analysis, a large number of markers is measured for thousands or millions of cells, resulting in high‐dimensional datasets. During the measurement of these samples, erroneous events can occur such as clogs, speed changes,… read more here.
Keywords: cytometry data; high quality; cytometry; quality control ... See more keywords
Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.
Sign Up to like & getrecommendations! Published in 2023 at "Proteomics"
DOI: 10.1002/pmic.202200290
Abstract: The evolution of omics and computational competency has accelerated discoveries of the underlying biological processes in an unprecedented way. High throughput methodologies, such as flow cytometry, can reveal deeper insights into cell processes, thereby allowing… read more here.
Keywords: approach; machine learning; cytometry data; biomarker ... See more keywords
Analysis of Mass Cytometry Data.
Sign Up to like & getrecommendations! Published in 2019 at "Methods in molecular biology"
DOI: 10.1007/978-1-4939-9454-0_17
Abstract: The CyTOF system produces single cell protein expression data similar to that from flow cytometry, but with an increased number of features measured. Traditionally, analysis of these data is carried out using manual gating, but… read more here.
Keywords: mass cytometry; data analysis; analysis; analysis mass ... See more keywords
Recent advances in microbial community analysis from machine learning of multiparametric flow cytometry data.
Sign Up to like & getrecommendations! Published in 2022 at "Current opinion in biotechnology"
DOI: 10.1016/j.copbio.2022.102688
Abstract: Dynamic analysis of microbial composition is crucial for understanding community functioning and detecting dysbiosis. Compositional information is mostly obtained through sequencing of taxonomic markers or whole meta-genomes, which may be productively complemented by real-time quantitative… read more here.
Keywords: cytometry data; multiparametric flow; machine; flow cytometry ... See more keywords
Testing for differential abundance in mass cytometry data
Sign Up to like & getrecommendations! Published in 2017 at "Nature methods"
DOI: 10.1038/nmeth.4295
Abstract: When comparing biological conditions using mass cytometry data, a key challenge is to identify cellular populations that change in abundance. Here, we present a computational strategy for detecting 'differentially abundant' populations by assigning cells to… read more here.
Keywords: differential abundance; abundance; cytometry data; mass cytometry ... See more keywords
ShinySOM: graphical SOM-based analysis of single-cell cytometry data
Sign Up to like & getrecommendations! Published in 2020 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaa091
Abstract: Abstract Summary ShinySOM offers a user-friendly interface for reproducible, high-throughput analysis of high-dimensional flow and mass cytometry data guided by self-organizing maps. The software implements a FlowSOM-style workflow, with improvements in performance, visualizations and data… read more here.
Keywords: analysis; cytometry data; som based; shinysom graphical ... See more keywords
GateMeClass: Gate Mining and Classification of cytometry data
Sign Up to like & getrecommendations! Published in 2024 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btae322
Abstract: Abstract Motivation Cytometry comprises powerful techniques for analyzing the cell heterogeneity of a biological sample by examining the expression of protein markers. These technologies impact especially the field of oncoimmunology, where cell identification is essential… read more here.
Keywords: classification; marker table; gatemeclass gate; cytometry data ... See more keywords
ggCyto: next generation open-source visualization software for cytometry
Sign Up to like & getrecommendations! Published in 2018 at "Bioinformatics"
DOI: 10.1093/bioinformatics/bty441
Abstract: Motivation Open source software for computational cytometry has gained in popularity over the past few years. Efforts such as FlowCAP, the Lyoplate and Euroflow projects have highlighted the importance of efforts to standardize both experimental… read more here.
Keywords: open source; bioconductor; cytometry data; cytometry ... See more keywords
ImaCytE: Visual Exploration of Cellular Micro-Environments for Imaging Mass Cytometry Data
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Transactions on Visualization and Computer Graphics"
DOI: 10.1109/tvcg.2019.2931299
Abstract: Tissue functionality is determined by the characteristics of tissue-resident cells and their interactions within their microenvironment. Imaging Mass Cytometry offers the opportunity to distinguish cell types with high precision and link them to their spatial… read more here.
Keywords: cytometry data; mass cytometry; analysis; imaging mass ... See more keywords
Analysis of flow cytometry data from ultrasound‐guided lymph node biopsies with two types of needles
Sign Up to like & getrecommendations! Published in 2024 at "International Journal of Laboratory Hematology"
DOI: 10.1111/ijlh.14306
Abstract: In this study, we combined two techniques, ultrasound‐guided needle biopsy and flow cytometry (FCM), to explore their value in patients with enlarged lymph nodes. read more here.
Keywords: analysis flow; ultrasound guided; data ultrasound; flow cytometry ... See more keywords