Best practices for single-cell analysis across modalities

Nature Reviews Genetics, Год журнала: 2023, Номер 24(8), С. 550 - 572

Опубликована: Март 31, 2023

Язык: Английский

---

The specious art of single-cell genomics

PLoS Computational Biology, Год журнала: 2023, Номер 19(8), С. e1011288 - e1011288

Опубликована: Авг. 17, 2023

Dimensionality reduction is standard practice for filtering noise and identifying relevant features in large-scale data analyses. In biology, single-cell genomics studies typically begin with to 2 or 3 dimensions produce "all-in-one" visuals of the that are amenable human eye, these subsequently used qualitative quantitative exploratory analysis. However, there little theoretical support this practice, we show extreme dimension reduction, from hundreds thousands 2, inevitably induces significant distortion high-dimensional datasets. We therefore examine practical implications low-dimensional embedding find extensive distortions inconsistent practices make such embeddings counter-productive exploratory, biological lieu this, discuss alternative approaches conducting targeted feature exploration enable hypothesis-driven discovery.

Язык: Английский

---

The Specious Art of Single-Cell Genomics

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2021, Номер unknown

Опубликована: Авг. 26, 2021

Abstract Dimensionality reduction is standard practice for filtering noise and identifying relevant features in large-scale data analyses. In biology, single-cell genomics studies typically begin with to two or three dimensions produce ‘all-in-one’ visuals of the that are amenable human eye, these subsequently used qualitative quantitative exploratory analysis. However, there little theoretical support this practice, we show extreme dimension reduction, from hundreds thousands two, inevitably induces significant distortion high-dimensional datasets. We therefore examine practical implications low-dimensional embedding data, find extensive distortions inconsistent practices make such embeddings counter-productive exploratory, biological lieu this, discuss alternative approaches conducting targeted feature exploration, enable hypothesis-driven discovery.

Язык: Английский

---

Time-resolved single-cell transcriptomics defines immune trajectories in glioblastoma

Cell, Год журнала: 2023, Номер 187(1), С. 149 - 165.e23

Опубликована: Дек. 21, 2023

Язык: Английский

---

A relay velocity model infers cell-dependent RNA velocity

Nature Biotechnology, Год журнала: 2023, Номер 42(1), С. 99 - 108

Опубликована: Апрель 3, 2023

Abstract RNA velocity provides an approach for inferring cellular state transitions from single-cell sequencing (scRNA-seq) data. Conventional models infer universal kinetics all cells in scRNA-seq experiment, resulting unpredictable performance experiments with multi-stage and/or multi-lineage transition of cell states where the assumption same kinetic rates no longer holds. Here we present cellDancer, a scalable deep neural network that locally infers each its neighbors and then relays series local velocities to provide resolution inference kinetics. In simulation benchmark, cellDancer shows robust multiple regimes, high dropout ratio datasets sparse datasets. We show overcomes limitations existing modeling erythroid maturation hippocampus development. Moreover, cell-specific predictions transcription, splicing degradation rates, which identify as potential indicators fate mouse pancreas.

Язык: Английский

---

Deep generative modeling of transcriptional dynamics for RNA velocity analysis in single cells

Nature Methods, Год журнала: 2023, Номер 21(1), С. 50 - 59

Опубликована: Сен. 21, 2023

Abstract RNA velocity has been rapidly adopted to guide interpretation of transcriptional dynamics in snapshot single-cell data; however, current approaches for estimating lack effective strategies quantifying uncertainty and determining the overall applicability system interest. Here, we present veloVI (velocity variational inference), a deep generative modeling framework velocity. learns gene-specific dynamical model metabolism provides transcriptome-wide quantification uncertainty. We show that compares favorably previous with respect goodness fit, consistency across transcriptionally similar cells stability preprocessing pipelines abundance. Further, demonstrate veloVI’s posterior can be used assess whether analysis is appropriate given dataset. Finally, highlight as flexible by adapting underlying use time-dependent transcription rates.

Язык: Английский

---

Lineage-specific intolerance to oncogenic drivers restricts histological transformation

Science, Год журнала: 2024, Номер 383(6683)

Опубликована: Фев. 8, 2024

Lung adenocarcinoma (LUAD) and small cell lung cancer (SCLC) are thought to originate from different epithelial types in the lung. Intriguingly, LUAD can histologically transform into SCLC after treatment with targeted therapies. In this study, we designed models follow conversion of found that barrier histological transformation converges on tolerance Myc, which implicate as a lineage-specific driver pulmonary neuroendocrine cell. Histological transformations frequently accompanied by activation Akt pathway. Manipulating pathway permitted Myc an oncogenic driver, producing rare, stem-like cells transcriptionally resemble basal lineage. These findings suggest may require plasticity inherent stem cell, enabling previously incompatible programs.

Язык: Английский

---

CellRank 2: unified fate mapping in multiview single-cell data

Nature Methods, Год журнала: 2024, Номер 21(7), С. 1196 - 1205

Опубликована: Июнь 13, 2024

Abstract Single-cell RNA sequencing allows us to model cellular state dynamics and fate decisions using expression similarity or velocity reconstruct state-change trajectories; however, trajectory inference does not incorporate valuable time point information utilize additional modalities, whereas methods that address these different data views cannot be combined do scale. Here we present CellRank 2, a versatile scalable framework study multiview single-cell of up millions cells in unified fashion. 2 consistently recovers terminal states probabilities across modalities human hematopoiesis endodermal development. Our also combining transitions within experimental points, feature use recover genes promoting medullary thymic epithelial cell formation during pharyngeal endoderm Moreover, enable estimating cell-specific transcription degradation rates from metabolic-labeling data, which apply an intestinal organoid system delineate differentiation trajectories pinpoint regulatory strategies.

Язык: Английский

---

DeepVelo: deep learning extends RNA velocity to multi-lineage systems with cell-specific kinetics

Genome biology, Год журнала: 2024, Номер 25(1)

Опубликована: Янв. 19, 2024

Abstract Existing RNA velocity estimation methods strongly rely on predefined dynamics and cell-agnostic constant transcriptional kinetic rates, assumptions often violated in complex heterogeneous single-cell sequencing (scRNA-seq) data. Using a graph convolution network, DeepVelo overcomes these limitations by generalizing to cell populations containing time-dependent kinetics multiple lineages. infers time-varying cellular rates of transcription, splicing, degradation, recovers each cell’s stage the differentiation process, detects functionally relevant driver genes regulating processes. Application various developmental pathogenic processes demonstrates DeepVelo’s capacity study lineage decision events scRNA-seq

Язык: Английский

---

A cell atlas of the human fallopian tube throughout the menstrual cycle and menopause

Nature Communications, Год журнала: 2025, Номер 16(1)

Опубликована: Янв. 3, 2025

The fallopian tube undergoes extensive molecular changes during the menstrual cycle and menopause. We use single-cell RNA ATAC sequencing to construct a comprehensive cell atlas of healthy human tubes Our scRNA-seq comparison 85,107 pre- 46,111 post-menopausal cells reveals substantial shifts in type frequencies, gene expression, transcription factor activity, cell-to-cell communications menopause cycle. Menstrual dependent hormonal regulate distinct states secretory epithelial cells. Postmenopausal show high chromatin accessibility factors associated with aging such as Jun, Fos, BACH1/2, while hormone receptors were generally downregulated, small proportion had expression ESR2, IGF1R, LEPR. While pre-menopausal cluster is enriched immunoreactive subtype, subset genes expressed enrichment mesenchymal high-grade serous ovarian cancer. cellular aging. Here, Weigert et al. present normal revealing transition throughout

Язык: Английский

---