Dictionary learning for integrative, multimodal and scalable single-cell analysis

Hao, Yuhan; Stuart, T.A.; Kowalski, Madeline H.; Choudhary, Saket; Hoffman, Paul; Hartman, Austin; Srivastava, Avi; Molla, Gesmira; Madad, Shaista; Fernandez‐Granda, Carlos; Satija, Rahul

doi:10.1038/s41587-023-01767-y

Cited by 862 publications

(311 citation statements)

References 119 publications

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“…To achieve this, we applied a linear mixed model, considering the enrichment scores for each TRD at different developmental stages (pcw16, pcw20, pcw21, pcw24). The model was formulated as follows: (enrichment scores ∼ cell type + (1|sample ID)), where enrichment scores were obtained from the AddModuleScore R function( 51 ). The cell type was coded as “cell type “ for cells in a given cluster and “non_celltype” for cells in other clusters, and sample ID represented the individual ID of cortical samples.…”

Section: Methodsmentioning

confidence: 99%

The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development

Girdhar,

Bendl,

Baumgartner

et al. 2023

Preprint

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Non-coding variants increase risk of neuropsychiatric disease. However, our understanding of the cell-type specific role of the non-coding genome in disease is incomplete. We performed population scale (N=1,393) chromatin accessibility profiling of neurons and non-neurons from two neocortical brain regions: the anterior cingulate cortex and dorsolateral prefrontal cortex. Across both regions, we observed notable differences in neuronal chromatin accessibility between schizophrenia cases and controls. A per-sample disease pseudotime was positively associated with genetic liability for schizophrenia. Organizing chromatin intocis- andtrans-regulatory domains, identified a prominent neuronaltrans-regulatory domain (TRD1) active in immature glutamatergic neurons during fetal development. Polygenic risk score analysis using genetic variants within chromatin accessibility of TRD1 successfully predicted susceptibility to schizophrenia in the Million Veteran Program cohort. Overall, we present the most extensive resource to date of chromatin accessibility in the human cortex, yielding insights into the cell-type specific etiology of schizophrenia.

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Section: Methodsmentioning

confidence: 99%

The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development

Girdhar,

Bendl,

Baumgartner

et al. 2023

Preprint

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“…RPCA was applied to the first 30 PCs of the 3,000 variable genes to find the anchors before integration by SCTransform. The resulting three integrated Seurat objects were then integrated together using the atomic sketch integration method 99 by selecting and storing 50,000 representative cells (“atoms”) from each dataset in the sampling step. We applied the same workflow as above for dimensionality deduction, clustering, and cell type annotation.…”

Section: Methodsmentioning

confidence: 99%

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer’s disease

Wang,

Antone,

Alsop

et al. 2023

Preprint

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The emergence of technologies that can support high-throughput profiling of single cell transcriptomes offers to revolutionize the study of brain tissue from persons with and without Alzheimer's disease (AD). Integration of these data with additional complementary multiomics data such as genetics, proteomics and clinical data provides powerful opportunities to link observed cell subpopulations and molecular network features within a broader disease-relevant context. We report here single nucleus RNA sequencing (snRNA-seq) profiles generated from superior frontal gyrus cortical tissue samples from 101 exceptionally well characterized, aged subjects from the Banner Brain and Body Donation Program in combination with whole genome sequences. We report findings that link common AD risk variants with CR1 expression in oligodendrocytes as well as alterations in peripheral hematological lab parameters, with these observations replicated in an independent, prospective cohort study of ageing and dementia. We also observed an AD-associated CD83(+) microglial subtype with unique molecular networks that encompass many known regulators of AD-relevant microglial biology, and which are associated with immunoglobulin IgG4 production in the transverse colon. These findings illustrate the power of multi-tissue molecular profiling to contextualize snRNA-seq brain transcriptomics and reveal novel disease biology. The transcriptomic, genetic, phenotypic, and network data resources described within this study are available for access and utilization by the scientific community.

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“…Here, we provide a nonexhaustive, entry-point, bioinformatics preprocessing guide for single-cell multiomics analysis, from raw reads to count matrix, removal of low-quality cells, doublets detection, data normalization, batch effect correction, cell clustering, visualization, and annotation (Table 1), following best practice guides [60 ▪▪ ,61] and benchmarking studies [62,63 ▪▪ ,64,65,66 ▪▪ ,67 ▪▪ ,68–70,71 ▪ ,72–83,84 ▪▪ ,85,86 ▪▪ ] in the single-cell field.…”

Section: Bioinformatic Practices For Single-cell Multiomics In the Co...mentioning

confidence: 99%

“…Integration of multimodal data can be achieved by Weighted Nearest Neighbors (WNN) in Seurat v4 [67 ▪▪ ], bridge interrogation in Seurat v5 [84 ▪▪ ], or a sequential integration approach in StabMap [86 ▪▪ ].…”

Section: Bioinformatic Practices For Single-cell Multiomics In the Co...mentioning

confidence: 99%

Single-cell multiomic understanding of HIV-1 reservoir at epigenetic, transcriptional, and protein levels

Wong

Wei

2023

Current Opinion in HIV and AIDS

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Purpose of review The success of HIV-1 eradication strategies relies on in-depth understanding of HIV-1-infected cells. However, HIV-1-infected cells are extremely heterogeneous and rare. Single-cell multiomic approaches resolve the heterogeneity and rarity of HIV-1-infected cells. Recent findings Advancement in single-cell multiomic approaches enabled HIV-1 reservoir profiling across the epigenetic (ATAC-seq), transcriptional (RNA-seq), and protein levels (CITE-seq). Using HIV-1 RNA as a surrogate, ECCITE-seq identified enrichment of HIV-1-infected cells in clonally expanded cytotoxic CD4+ T cells. Using HIV-1 DNA PCR-activated microfluidic sorting, FIND-seq captured the bulk transcriptome of HIV-1 DNA+ cells. Using targeted HIV-1 DNA amplification, PheP-seq identified surface protein expression of intact versus defective HIV-1-infected cells. Using ATAC-seq to identify HIV-1 DNA, ASAP-seq captured transcription factor activity and surface protein expression of HIV-1 DNA+ cells. Combining HIV-1 mapping by ATAC-seq and HIV-1 RNA mapping by RNA-seq, DOGMA-seq captured the epigenetic, transcriptional, and surface protein expression of latent and transcriptionally active HIV-1-infected cells. To identify reproducible biological insights and authentic HIV-1-infected cells and avoid false-positive discovery of artifacts, we reviewed current practices of single-cell multiomic experimental design and bioinformatic analysis. Summary Single-cell multiomic approaches may identify innovative mechanisms of HIV-1 persistence, nominate therapeutic strategies, and accelerate discoveries.

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Dictionary learning for integrative, multimodal and scalable single-cell analysis

Cited by 862 publications

References 119 publications

The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development

The neuronal chromatin landscape in adult schizophrenia brains is linked to early fetal development

A public resource of single cell transcriptomes and multiscale networks from persons with and without Alzheimer’s disease

Single-cell multiomic understanding of HIV-1 reservoir at epigenetic, transcriptional, and protein levels

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