Monocle protocols

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chevron_left Clustering Dimensionality reduction Data analysis scRNA-seq data visualization Differential expression detection Cell lineage and pseudotime inference Marker gene detection Expression pattern detection chevron_right
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Monocle specifications


Unique identifier OMICS_07026
Name Monocle
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS
Programming languages R
License Artistic License version 2.0
Computer skills Advanced
Version 2.8.0
Stability Stable
methods, Matrix, Biobase, ggplot2, VGAM, DDRTree
Maintained Yes


  • BEAM
  • Census
  • detectGenes



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  • person_outline Cole Trapnell <>

Additional information

Publications for Monocle

Monocle in pipelines

PMCID: 5871331
PMID: 29580379
DOI: 10.7554/eLife.33105.044

[…] were found to be variable using m3drop () (raw count input, false discovery rate <= 0.01). l-scran expression values for this subset of genes were used to order the cells in pseudotime using monocle 2 (); specifically the reducedimension() and ordercells (num_path = 2) functions were used to derive the ordering of the cells. monocle 2 identified a single cell state and the cells […]

PMCID: 5465230
PMID: 28597408
DOI: 10.1186/s40169-017-0150-9

[…] of marker genes have been developed [, , ]. these methods reconstruct trajectory paths in reduced spaces using several algorithms such as minimum spanning trees (mst), and principal curves. monocle, developed by trapnell et al. [] uses independent component analysis (ica) for dimension reduction and then constructs an mst to find the paths based on euclidean distance. authors achieved […]

PMCID: 5723634
PMID: 29225342
DOI: 10.1038/s41467-017-02001-5

[…] the diffusion map algorithm was robust to the choice of features and down-sampling of cells (supplementary fig. ). the structure of a common origin and the two branches could also be inferred using monocle with standard settings (supplementary fig. ). for inferring the branches and pseudotime ordering, we defined the following three tips, the cell with the largest value for the second […]

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Monocle in publications

PMCID: 5951918
PMID: 29760424
DOI: 10.1038/s41467-018-04215-7

[…] mgc) in the first dimension and germ cells from somatic cells in the second dimension (fig. ). this confirms that germ cells cluster by transcriptional program instead of by developmental age. using monocle, we computed the minimum spanning tree (supplementary fig. ) and ranked the germ cells along a pseudo developmental timeline (fig. ). the list of genes enriched at least tenfold per stage, […]

PMCID: 5916943
PMID: 29695820
DOI: 10.1038/s41598-018-24725-0

[…] seurat). as none of these led to the exclusion of more than 5 cells even at stringent settings, no further filtering of cells was performed., pseudotime analysis was performed using the scater, monocle– and scrat– packages for r., rna half-life was calculated by applying a loess regression to total counts per cell for each sex chromosome and the total of all autosomes divided […]

PMCID: 5852373
PMID: 29545397
DOI: 10.15252/msb.20178041

[…] this logic suggests that we can reconstruct developmental histories from cellular snapshots of many single cells. this has been the underlying logic for many trajectory building algorithms, such as monocle, wanderlust, and wishbone (bendall et al, ; trapnell et al, ; setty et al, ; qiu et al, ). importantly, the assumptions underlying this strategy require that we sufficiently sample […]

PMCID: 5924749
PMID: 29713661
DOI: 10.1016/j.jcmgh.2018.01.023

[…] and their connections approximate the geometric shape of the data cloud when laid out in 2 dimensions. multiple mst algorithms (eg, spanning-tree progression analysis of density-normalized events, monocle1, tools for single cell analysis, waterfall) exist and they differ by their applications on different experimental platforms, and the type and degree of clustering of data that occurs […]

PMCID: 5801402
PMID: 29456488
DOI: 10.3389/fnins.2018.00031

[…] is another important concept in the computational analysis of single-cell transcriptome, which estimates the cells' progress through the transition. the computational tools like tscan (ji and ji, ), monocle (trapnell et al., ), waterfall (shin et al., ), sincell (julia et al., ), oscope (leng et al., ), and wanderlust (bendall et al., ) provide in silico defined pseudotime for each single-cell […]

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Monocle institution(s)
Department of Genome Sciences, University of Washington, Seattle, WA, USA; Molecular and Cellular Biology Program, University of Washington, Seattle, WA, USA; Department of Applied Mathematics, University of Washington, Seattle, WA, USA
Monocle funding source(s)
Supported by US National Institutes of Health (NIH) grant DP2 HD088158, partly supported by a Dale. F. Frey Award for Breakthrough Scientists and an Alfred P. Sloan Foundation Research Fellowship and a National Science Foundation (NSF) Graduate Research Fellowship.

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