<i>destiny</i>: diffusion maps for large-scale single-cell data in R

Angerer, Philipp; Haghverdi, Laleh; Büttner, Maren; Theis, Fabian J.; Marr, Carsten; Buettner, Florian

doi:10.1093/bioinformatics/btv715

Cited by 569 publications

(424 citation statements)

References 6 publications

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“…http://dx.doi.org/10.1101/363051 doi: bioRxiv preprint first posted online Jul. 7, 2018; maps 18 (Fig. 3d) or t-Distributed Stochastic Neighbor Embedding 19 (tSNE; Fig.…”

Section: Putative Transitions Between Myeloid Cell Clusters Suggest Pmentioning

confidence: 99%

“…We therefore approached this question looking at indirect evidence, and in particular the existence of intermediate states between the identified B cell subsets. Projecting the gene expression data of the B cells onto 2 dimensions using diffusion maps 18 , we found that the naïve (CB2a) and . CC-BY-NC-ND 4.0 International license It is made available under a was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity.…”

Section: Indirect Evidence For B Cell Activation and Differentiation mentioning

confidence: 99%

“…Trajectory analysis was performed based on dimensionality reduction using diffusion maps, as implemented in the Destiny software package (v2.6.2) 18 . In each case, only the cells relevant to the question at hand were analyzed.…”

Section: Trajectory Analysismentioning

confidence: 99%

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The immune cell landscape in kidneys of lupus nephritis patients

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Rao

Berthier

et al. 2018

Preprint

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Lupus nephritis is a potentially fatal autoimmune disease, whose current treatment is ineffective and often toxic. To gain insights into disease mechanisms, we analyzed kidney samples from lupus nephritis patients and healthy controls using single-cell RNA-seq. Our analysis revealed 21 subsets of leukocytes active in disease, including multiple populations of myeloid, T, NK and B cells, demonstrating both pro-inflammatory and resolving responses. We found evidence of local activation of B cells correlated with an age-associated B cell signature, and of progressive stages of monocyte differentiation within the kidney. A clear interferon response was observed in most cells. Two chemokine receptors, CXCR4 and CX3CR1, were broadly expressed, pointing to potential therapeutic targets. Gene expression of immune cells in urine and kidney was highly correlated, suggesting urine may be a surrogate for kidney biopsies. Our results provide a first comprehensive view of the complex network of leukocytes active in lupus nephritis kidneys.

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“…http://dx.doi.org/10.1101/363051 doi: bioRxiv preprint first posted online Jul. 7, 2018; maps 18 (Fig. 3d) or t-Distributed Stochastic Neighbor Embedding 19 (tSNE; Fig.…”

Section: Putative Transitions Between Myeloid Cell Clusters Suggest Pmentioning

confidence: 99%

Section: Indirect Evidence For B Cell Activation and Differentiation mentioning

confidence: 99%

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The immune cell landscape in kidneys of lupus nephritis patients

Arazi

Rao

Berthier

et al. 2018

Preprint

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“…To date, several computational methods have been reported that profile developmental processes, such as Monocle (Trapnell et al 2014), Wanderlust (Bendall et al 2014), Wishbone (Setty et al 2016), SLICER (Welch et al 2016), Diffusion Pseudotime , Destiny (Angerer et al 2016), and SCUBA (Marco et al 2014). These methods attempt to order cells into smooth continuous spatiotemporal trajectories to model development.…”

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confidence: 99%

Single-cell gene expression analysis reveals regulators of distinct cell subpopulations among developing human neurons

et al. 2017

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The stochastic dynamics and regulatory mechanisms that govern differentiation of individual human neural precursor cells (NPC) into mature neurons are currently not fully understood. Here, we used single-cell RNA-sequencing (scRNA-seq) of developing neurons to dissect/identify NPC subtypes and critical developmental stages of alternative lineage specifications. This study comprises an unsupervised, high-resolution strategy for identifying cell developmental bifurcations, tracking the stochastic transcript kinetics of the subpopulations, elucidating regulatory networks, and finding key regulators. Our data revealed the bifurcation and developmental tracks of the two NPC subpopulations, and we captured an early (24 h) transition phase that leads to alternative neuronal specifications. The consequent up-regulation and down-regulation of stageand subpopulation-specific gene groups during the course of maturation revealed biological insights with regard to key regulatory transcription factors and lincRNAs that control cellular programs in the identified neuronal subpopulations.

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“…(Pierson and Yau, 2015) or weighted gene co-expression network analysis (Langfelder and Horvath, 2008) are first used to project highdimensional data into a smaller number of dimensions to ease visual evaluation and interpretation. Clusters of similar cells can be identified using generally applicable methods, such as Gaussian mixture modeling (Fraley and Raftery, 2002) or K-means clustering, or methods devised specifically for single cell data, such as StemID (Grün et al, 2016), SCUBA, SNN-Cliq (Xu and Su, 2015), Destiny (Angerer et al, 2015) or BackSpin (Zeisel et al, 2015). Clusters can then be annotated based on domain-specific knowledge of the expression of a few genes, or automatically based on gene set enrichment.…”

Section: The Basics Of Scrna-seq Analysismentioning

confidence: 99%

Understanding development and stem cells using single cell-based analyses of gene expression

2017

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In recent years, genome-wide profiling approaches have begun to uncover the molecular programs that drive developmental processes. In particular, technical advances that enable genome-wide profiling of thousands of individual cells have provided the tantalizing prospect of cataloging cell type diversity and developmental dynamics in a quantitative and comprehensive manner. Here, we review how singlecell RNA sequencing has provided key insights into mammalian developmental and stem cell biology, emphasizing the analytical approaches that are specific to studying gene expression in single cells.

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destiny: diffusion maps for large-scale single-cell data in R

Abstract: Supplementary data are available at Bioinformatics online.

Cited by 569 publications

References 6 publications

The immune cell landscape in kidneys of lupus nephritis patients

The immune cell landscape in kidneys of lupus nephritis patients

Single-cell gene expression analysis reveals regulators of distinct cell subpopulations among developing human neurons

Understanding development and stem cells using single cell-based analyses of gene expression

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