swh:1:snp:0da231f3ffdb3226650880f1b61d5d5cdcbd749b
Tip revision: 964ced3cd3d12094e43abbc2a54b55baa597292b authored by David Collins on 14 March 2024, 20:47:25 UTC
Merge pull request #907 from satijalab/fix/misc_tests
Merge pull request #907 from satijalab/fix/misc_tests
Tip revision: 964ced3
vignettes_v5_new.yaml
- category: Introduction
vignettes:
- title: Guided tutorial --- 2,700 PBMCs
name: pbmc3k_tutorial
summary: |
A basic overview of Seurat that includes an introduction to common analytical workflows.
image: pbmc3k_umap.jpg
- title: Multimodal analysis
name: multimodal_vignette
summary: |
An introduction to working with multi-modal datasets in Seurat.
image: citeseq_plot.jpg
- title: Visualization
name: visualization_vignette
summary: |
An overview of the visualization capabilities within Seurat.
image: visualization_vignette.jpg
- title: SCTransform
name: sctransform_vignette
summary: |
Examples of how to perform normalization, feature selection, integration, and differential expression with an updated version of sctransform.
image: assets/sctransform_v2_new.png
- title: Essential Commands Cheat Sheet
name: essential_commands
summary: |
Reference list of commonly used commands to store, access, explore, and analyze datasets.
image: commands.png
- category: scRNA-seq Data Integration
vignettes:
- title: Introduction to scRNA-seq integration
name: integration_introduction
summary: |
An introduction to integrating scRNA-seq datasets in order to identify and compare shared cell types across experiments.
image: pbmc_alignment.jpg
- title: scRNA-seq Integration
name: seurat5_integration
summary: |
Integrate scRNA-seq datasets using a variety of computational methods.
image: integration_seurat5.jpg
- title: Mapping and annotating query datasets
name: integration_mapping
summary: |
Learn how to map a query scRNA-seq dataset onto a reference in order to automate the annotation and visualization of query cells.
image: assets/anchorsb_2018.png
- category: Multi-assay data
vignettes:
- title: Cross-modality Bridge Integration
name: seurat5_integration_bridge
summary: |
Map scATAC-seq onto an scRNA-seq reference using a multi-omic bridge dataset in Seurat v5.
image: bridge_integration.png
- title: Weighted Nearest Neighbor Analysis
name: weighted_nearest_neighbor_analysis
summary: |
Analyze multimodal single-cell data with weighted nearest neighbor analysis in Seurat v4.
image: weighted_nearest_neighbor_analysis.jpg
- title: Integrating scRNA-seq and scATAC-seq data
name: atacseq_integration_vignette
summary: |
Annotate, visualize, and interpret an scATAC-seq experiment using scRNA-seq data from the same biological system in Seurat v3.
image: atacseq_integration_vignette.jpg
- title: Reference Mapping for Multimodal Data
name: multimodal_reference_mapping
summary: |
Analyze query data in the context of multimodal reference atlases.
image: multimodal_reference_mapping.jpg
- title: Mixscape
name: mixscape_vignette
summary: |
Explore new methods to analyze pooled single-celled perturbation screens.
image: mixscape_vignette.jpg
- category: Flexible analysis of massively scalable datasets
vignettes:
- title: Unsupervised clustering of 1.3M neurons
name: seurat5_sketch_analysis
summary: |
Analyze a 1.3 million cell mouse brain dataset using on-disk capabilities powered by BPCells.
image: sketch_1p3.png
- title: Integrating/comparing healthy and diabetic samples
name: ParseBio_sketch_integration
summary: |
Perform sketch integration on a large dataset from Parse Biosciences.
image: sketch.png
- title: Supervised mapping of 1.5M immune cells
name: COVID_SCTMapping
summary: |
Map PBMC datasets from COVID-19 patients to a healthy PBMC reference.
image: COVID_SCTMapping.png
- title: BPCells Interaction
name: seurat5_bpcells_interaction_vignette
summary: |
Load and save large on-disk matrices using BPCells.
image: bpcells.png
- category: Spatial analysis
vignettes:
- title: Analysis of spatial datasets (Imaging-based)
name: seurat5_spatial_vignette_2
summary: |
Learn to explore spatially-resolved data from multiplexed imaging technologies, including MERSCOPE, Xenium, CosMx SMI, and CODEX.
image: spatial_vignette_2.jpg
- title: Analysis of spatial datasets (Sequencing-based)
name: spatial_vignette
summary: |
Learn to explore spatially-resolved transcriptomic data with examples from 10x Visium and Slide-seq v2.
image: spatial_vignette_ttr.jpg
- category: Other
vignettes:
- title: Cell Cycle Regression
name: cell_cycle_vignette
summary: |
Mitigate the effects of cell cycle heterogeneity by computing cell cycle phase scores based on marker genes.
image: cell_cycle_vignette.jpg
- title: Differential Expression Testing
name: de_vignette
summary: |
Perform differential expression (DE) testing in Seurat using a number of frameworks.
image: assets/de_vignette.png
- title: Demultiplex Cell Hashing data
name: hashing_vignette
summary: |
Learn how to work with data produced with Cell Hashing.
image: assets/hashing_vignette.png
- category: Seurat Wrappers
hash: seurat-wrappers
description: |
In order to facilitate the use of community tools with Seurat, we provide the Seurat Wrappers package, which contains code to run other analysis tools on Seurat objects. For the initial release, we provide wrappers for a few packages in the table below but would encourage other package developers interested in interfacing with Seurat to check out our contributor guide [here](https://github.com/satijalab/seurat.wrappers/wiki/Submission-Process). <br><br>
vignettes:
- name: alevin
title: Import alevin counts into Seurat
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/alevin.html
reference: https://doi.org/10.1186/s13059-019-1670-y
citation: Srivastava et. al., Genome Biology 2019
source: https://github.com/k3yavi/alevin-Rtools
- name: ALRA
title: Zero-preserving imputation with ALRA
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/alra.html
reference: https://doi.org/10.1101/397588
citation: Linderman et al, bioRxiv 2018
source: https://github.com/KlugerLab/ALRA
- name: CoGAPS
title: Running CoGAPS on Seurat Objects
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/cogaps.html
reference: https://doi.org/10.1016/j.cels.2019.04.004
citation: Stein-O’Brien et al, Cell Systems 2019
source: https://www.bioconductor.org/packages/release/bioc/html/CoGAPS.html
- name: Conos
title: Integration of datasets using Conos
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/conos.html
reference: https://doi.org/10.1038/s41592-019-0466-z
citation: Barkas et al, Nature Methods 2019
source: https://github.com/hms-dbmi/conos
- name: fastMNN
title: Running fastMNN on Seurat Objects
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/fast_mnn.html
reference: https://doi.org/10.1038/nbt.4091
citation: Haghverdi et al, Nature Biotechnology 2018
source: https://bioconductor.org/packages/release/bioc/html/scran.html
- name: glmpca
title: Running GLM-PCA on a Seurat Object
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/glmpca.html
reference: https://doi.org/10.1186/s13059-019-1861-6
citation: Townes et al, Genome Biology 2019
source: https://github.com/willtownes/glmpca
- name: Harmony
title: Integration of datasets using Harmony
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/harmony.html
reference: https://doi.org/10.1038/s41592-019-0619-0
citation: Korsunsky et al, Nature Methods 2019
source: https://github.com/immunogenomics/harmony
- name: LIGER
title: Integrating Seurat objects using LIGER
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/liger.html
reference: https://doi.org/10.1016/j.cell.2019.05.006
citation: Welch et al, Cell 2019
source: https://github.com/MacoskoLab/liger
- name: Monocle3
title: Calculating Trajectories with Monocle 3 and Seurat
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/monocle3.html
reference: https://doi.org/10.1038/s41586-019-0969-x
citation: Cao et al, Nature 2019
source: https://cole-trapnell-lab.github.io/monocle3
- name: Nebulosa
title: Visualization of gene expression with Nebulosa
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/nebulosa.html
reference: https://github.com/powellgenomicslab/Nebulosa
citation: Jose Alquicira-Hernandez and Joseph E. Powell, Under Review
source: https://github.com/powellgenomicslab/Nebulosa
- name: schex
title: Using schex with Seurat
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/schex.html
reference: https://doi.org/0.1242/dev.173807
citation: Freytag, R package 2019
source: https://github.com/SaskiaFreytag/schex
- name: scVelo
title: Estimating RNA Velocity using Seurat and scVelo
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/scvelo.html
reference: https://doi.org/10.1101/820936
citation: Bergen et al, bioRxiv 2019
source: https://scvelo.readthedocs.io/
- name: Velocity
title: Estimating RNA Velocity using Seurat
link: https://htmlpreview.github.io/?https://github.com/satijalab/seurat.wrappers/blob/master/docs/velocity.html
reference: 10.1038/s41586-018-0414-6
citation: La Manno et al, Nature 2018
source: https://velocyto.org
- name: CIPR
title: Using CIPR with human PBMC data
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/cipr.html
reference: https://doi.org/10.1186/s12859-020-3538-2
citation: Ekiz et. al., BMC Bioinformatics 2020
source: https://github.com/atakanekiz/CIPR-Package
- name: miQC
title: Running miQC on Seurat objects
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/miQC.html
reference: https://www.biorxiv.org/content/10.1101/2021.03.03.433798v1
citation: Hippen et. al., bioRxiv 2021
source: https://github.com/greenelab/miQC
- name: tricycle
title: Running estimate_cycle_position from tricycle on Seurat Objects
link: http://htmlpreview.github.io/?https://github.com/satijalab/seurat-wrappers/blob/master/docs/tricycle.html
reference: https://doi.org/10.1101/2021.04.06.438463
citation: Zheng et. al., bioRxiv 2021
source: https://www.bioconductor.org/packages/release/bioc/html/tricycle.html