Resources
Reference Genomes¶
| Name | Species | Common name | Annotation Version |
|---|---|---|---|
| GRCh38 | Homo sapiens | Human | Genome Reference Consortium Human Build 38 |
| mm10 | Mus musculus | House mouse | Genome Reference Consortium Mouse Build 38 |
Software¶
Data processing¶
| Package name | Version | Usage | Reference |
|---|---|---|---|
| R | 3.6.1 | Primary framework and programming language for data processing | 1 |
| Seurat | 3.1.4 | Primary program for processing single cell data | 2, 3 |
| Routliers | 0.0.0.3 | R package for identifying outliers via median absolute deviation | 4, 5, 6 |
| SCTransform | Included in Seurat v3.1.4 | Used for normalization. This replaces the ScaleData/Normalization from previous versions of Seurat | 7 |
| URD | 1.1.0 | Used to calculate optimal number of principal components through the Marchenko-Pastur law | 8 |
| UMAP | 0.4.6 | 2D and 3D dimensionality reduction projection for visualizing cells and relative similarity | 9, 10 |
| SingleR | 1.0.5 | Cell type annotation based on correlation to cell types within curated databases | 11, 12 |
| DoubletFinder | 2.0.2 | Algorithm to determine likely doublets based on cell distribution and cell type similarity | 13, 14 |
Visualization¶
| Package name | Version | Usage | Reference |
|---|---|---|---|
| ggplot2 | 3.3.0 | Basis for a majority of the visualization, including violin distribution plots and UMAP plots | 15 |
| Rmarkdown | 2.1 | Report writing in html and pdf formats | 16, 17 |
| VennDiagram | 1.6.20 | Generate Venn diagrams | 18 |
| cluster | 2.1.0 | Analyze clustering similarity for optimization via silhouette plots | 19 |
References¶
1 "The R Project for Statistical Computing." https://www.r-project.org/. Version 3.6.1, released 2019-07-05.
2 Stuart, Butler, et al., 2019. "Comprehensive Integration of Single-Cell Data." Cell 177 (7): 1888-1902.e21. doi: 10.1016/j.cell.2019.05.031
3 Butler, Hoffman, et al., 2018. "Integrating single-cell transcriptomic data across different conditions, technologies, and species." Nat. Biotechnol. 36: 411-420. doi: 10.1038/nbt.4096
4 Leys, Ley, et al., 2013. "Detecting outliers: Do not use standard deviation around the mean, use absolute deviation around the median." J. Exp. Soc. Psychol. 49(4): 764-766. doi: 10.1016/j.jesp.2013.03.013
5 Leys, Klein, et al., 2018. "Detecting multivariate outliers: Use a robust variant of the Mahalanobis distance." J. Exp. Soc. Psychol. 74: 150-156. doi: 10.1016/j.jesp.2017.09.011
6 Delecre and Klein. 2019. "Routliers: Robust Outliers Detection." https://CRAN.R-project.org/package=Routliers.
7 Hafemeister and Satija. 2019. "Normalization and variance stabilization of single-cell RNA-seq data using regularized negative binomial regression." Genome Biol. 20: 296. doi: 10.1186/s13059-019-1874-1
8 Farrell, Wang, et al. 2018. "Single-cell reconstruction of developmental trajectories during zebrafish embryogenesis." Science 360: 979. doi: 10.1126/science.aar3131
9 McInnes, L. "UMAP." https://github.com/lmcinnes/umap.
10 McInnes and Healy. 2018. "UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction." ArXiv e-prints. 1802.03426.
11 Aran, Looney, et al. 2019. "Reference-based analysis of lung single-cell sequencing reveals a transitional profibrotic macrophage." Nat. Immunol. 20: 163-172. doi: 10.1038/s41590-018-0276-y.
12 Aran, Lun, et al. "Reference-Based Single-Cell RNA-Seq Annotation." https://bioconductor.org/packages/release/bioc/html/SingleR.html. doi: 10.18129/B9.bioc.SingleR
13 McGinnis, Murrow, and Gartner. 2019. "DoubletFinder: Doublet Detection in Single-Cell RNA Sequencing Data Using Artificial Nearest Neighbors." Cell Systems 8(4): 329-337.e4. doi: 10.1016/j.cels.2019.03.003
14 McGinnis, C. "DoubletFinder." https://github.com/chris-mcginnis-ucsf/DoubletFinder.
15 Wickham, H. 2016. ggplot2: Elegant graphics for data analysis. Springer-Verlag New York. ISBN 978-3-319-24277-4, https://ggplot2.tidyverse.org.
16 Allaire, Xie, et al. 2019. rmarkdown: Dynamic documents for R. R package version 2.1, https://github.com/rstudio/rmarkdown.
17 Xie, Allaire, and Grolemund. 2018. R Markdown: The Definitive Guide. Chapman and Hall/CRC, Boca Raton, FL, USA. ISBN 9781138359338, https://bookdown.org/yihui/rmarkdown.
18 Chen and Boutros. 2018. VennDiagram: Generate high-resolution Venn and Euler plots. R package version 1.6.20, https://cran.r-project.org/web/packages/VennDiagram
19 Maechler, Rouseeuw, et al. 2019. cluster: Cluster Analysis Basics and Extensions. R package version 2.1.0, https://cran.r-project.org/web/packages/cluster/