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PhenoGraph specifications

Information


Unique identifier OMICS_29495
Name PhenoGraph
Software type Application/Script
Interface Command line interface
Restrictions to use None
Input data A matrix of N single-cell measurements.
Operating system Unix/Linux, Mac OS, Windows
Programming languages MATLAB, Python
License MIT License
Computer skills Advanced
Version 1.5.2
Stability Stable
Requirements
scikit-learn
Maintained Yes

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Maintainers


  • person_outline Garry Nolan
  • person_outline Dana Pe’er

Publication for PhenoGraph

PhenoGraph citations

 (12)
library_books

High Dimensional Phenotyping Identifies Age Emergent Cells in Human Mammary Epithelia

2018
Cell Rep
PMCID: 5946804
PMID: 29694896
DOI: 10.1016/j.celrep.2018.03.114

[…] cells from HMEC >50 years. In tSNE, each cell is represented as a point in high-dimensional space. Each dimension is one parameter (the expression level of each protein in our case).The unsupervised PhenoGraph algorithm in cyt has been used to group cells that are phenotypically similar and cluster these subpopulations using modularity optimization (). tSNE and PhenoGraph were performed only on s […]

library_books

Association between expression of random gene sets and survival is evident in multiple cancer types and may be explained by sub classification

2018
PLoS Comput Biol
PMCID: 5839591
PMID: 29470520
DOI: 10.1371/journal.pcbi.1006026

[…] To perform clustering of the high dimensional gene-expression data using the least number of parameters, we chose to use phenoGraph []. The algorithm follows several steps. First, using the similarity between all samples it identifies the k-nearest neighbors of each sample. We used Spearman’s correlation as the distance […]

library_books

QFMatch: multidimensional flow and mass cytometry samples alignment

2018
Sci Rep
PMCID: 5818510
PMID: 29459702
DOI: 10.1038/s41598-018-21444-4

[…] . Recently developed cluster matching methods intended for this purpose can be informally divided into two types:Separate clustering and matching. This type of approach, used for example in FLAME and PhenoGraph, identifies cluster locations in each individual sample (e.g., by using mixture models or by constructing a graph and using modularity optimization to cluster it). It then pools these clust […]

library_books

Comparison of CyTOF assays across sites: Results of a six center pilot study

2018
J Immunol Methods
PMCID: 5805584
PMID: 29174717
DOI: 10.1016/j.jim.2017.11.008

[…] http://pengqiu.gatech.edu/software/SPADE/) and Cytofkit (; https://github.com/JinmiaoChenLab/cytofkit), which is an R software package containing components for PCA and tSNE outputs for ClusterX (), Phenograph (), and FlowSOM () algorithms. To explore the effects of prestained vs site-stained samples, the files were run as three sets with each algorithm: the 12 P files only, the 24 AB files only, […]

library_books

Simultaneous Multiplexed Imaging of mRNA and Proteins with Subcellular Resolution in Breast Cancer Tissue Samples by Mass Cytometry

2018
Cell Syst
PMCID: 5791659
PMID: 29289569
DOI: 10.1016/j.cels.2017.12.001

[…] in the RNA channels we observed cells with a mean of 0 counts we set all cells with mean counts lower than 0.005 to a minimum value of 0.005. Quantile normalization (99th percentile) was applied for PhenoGraph clustering (parameter k = 50) as proposed in the original publication (). All correlation based analyses were performed using Spearman correlation, which is invariant to data transformation […]

library_books

Cellular Differentiation of Human Monocytes Is Regulated by Time Dependent Interleukin 4 Signaling and the Transcriptional Regulator NCOR2

2017
Immunity
PMCID: 5772172
PMID: 29262348
DOI: 10.1016/j.immuni.2017.11.024

[…] 06, VSIG4, CD88, CD34, MerTK, CD39, CD26, CD11c, CD11b, CD16). Detailed analysis on the Mo-GM-CSFIL-4 condition was based on 3500 cells from one individual. To define clusters of cell subpopulations, PhenoGraph was used. Points representing individual cells in the t-SNE plots were color-coded to illustrate amount of protein expression or affiliations to clusters, treatment conditions or donors, re […]

Citations

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PhenoGraph institution(s)
Departments of Biological Sciences and Systems Biology, Columbia University, New York, NY, USA; Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, CA, USA; Department of Pathology, Stanford University, Stanford, CA, USA; Department of Pathology, St. Jude Children’s Research Hospital, Memphis, TN, USA
PhenoGraph funding source(s)
Supported by DRCF Fellowships (DRG 2190-14 &DRG-2017-09), NIH 1R00-GM104148, Grants NIH (DP1- HD084071, DP2-OD002414, R01-CA164729 U54-CA121852), Stand Up To Cancer Phillip A. Sharp Award SU2C-AACR-PS04, Packard Fellowship for Science and Engineering, Grants NIH (1R01CA130826, 5U54CA143907, HHSN272200700038C, N01-HV-00242, P01 CA034233, U19 AI057229 and U54CA149145), CIRM (DR1-01477 and RB2-01592), EC (HEALTH.2010.1.2-1), US FDA (HHSF223201210194C),US DOD (W81XWH-12-1-0591), the Entertainment Industry Foundation, and the Rachford and Carlota Harris Endowed Professorship.

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