pseudogp specifications

Information


Unique identifier OMICS_18060
Name pseudogp
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes

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Documentation


Maintainers


  • person_outline kieran.campbell <>
  • person_outline Christopher Yau <>

Additional information


http://kieranrcampbell.github.io/pseudogp/

Publication for pseudogp

pseudogp in publications

 (3)
PMCID: 5766627
PMID: 29330484
DOI: 10.1038/s41598-017-19100-4

[…] process, we infer pseudotime, which represents a measure of cells progression along the differentiation trajectory. first, based on the data in reduced dimension as shown in fig. , we applied pseudogp and obtained the trajectory shown in fig. . the inferred curve showed a pattern of differentiation from jtec to mtechi to mteclo. we then used a diffusion map based non-linear dimension […]

PMCID: 5746494
PMID: 29285690
DOI: 10.1186/s40169-017-0177-y

[…] example, monocle2 is an unsupervised algorithm designed to analyze the heterogeneity among cells and reconstruct the micro-evolution timeline from scrna-seq data []. other tools such as sclvm [], pseudogp [], and spade [] have provided various solutions to analyze heterogeneity with scrna-seq data computationally. with the scrna-seq analysis toolbox expanding rapidly, graphical user interface […]

PMCID: 5575496
PMID: 28524227
DOI: 10.1002/1873-3468.12684

[…] experimental design through priors . there are many implementations of this method. for python, there is gpy and gpflow, and for r there are the delorean (https://github.com/johnreid/delorean) and pseudogp (https://github.com/kieranrcampbell/pseudogp) packages., the ouija method takes a different approach to pseudotime in a couple of ways. firstly, it defines a generative model for gene […]


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pseudogp institution(s)
Department of Physiology, Anatomy and Genetics, University of Oxford, Oxford, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Department of Statistics, University of Oxford, Oxford, UK
pseudogp funding source(s)
Supported by a UK Medical Research Council funded doctoral studentship, a UK Medical Research Council New Investigator Research Grant (Ref. No. MR/ L001411/1), the Wellcome Trust Core Award Grant Number 090532/Z/09/Z, the John Fell Oxford University Press (OUP) Research Fund and the Li Ka Shing Foundation via a Oxford-Stanford Big Data in Human Health Seed Grant.

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