Mapping and Counting
Your Possible Next Steps
- Identification of differentially expressed genes with DESeq2 (Love, Huber, and Anders 2014, see tutorial) for RNA-seq data
- Identification of sequence variants with GATK (McKenna et al. 2010, see tutorial) for DNA-seq data
- Basic single-cell analysis in Loupe Browser (see tutorial)
- Advanced single-cell analysis in R with Seurat (Hao et al. 2024, see tutorial) or in python with scanpy (Wolf, Angerer, and Theis 2018, see tutorial)
- Basic single-cell analysis in Loupe Browser (see tutorial)
- Advanced single-cell analysis in R with Signac (Stuart et al. 2022, see tutorial) or in python with SnapATAC2 (Zhang et al. 2024, see tutorial)
- Basic single-cell analysis in Loupe Browser (see tutorial)
- Advanced single-cell analysis in R with Seurat and Signac (Hao et al. 2024; Stuart et al. 2022, see tutorial) or in python with muon (Zhang et al. 2024, see tutorial)
- Basic spatial analysis in Loupe Browser (see tutorial and tutorial)
- Advanced spatial analysis in R with Seurat (Hao et al. 2024, see tutorial and tutorial) or in python with squidpy (Palla et al. 2022, see tutorial)
- Advanced spatial analysis in R with Seurat (Hao et al. 2024, see tutorial) or in python with squidpy (Palla et al. 2022, see tutorial)
References
Hao, Yuhan, Tim Stuart, Madeline H Kowalski, Saket Choudhary, Paul Hoffman, Austin Hartman, Avi Srivastava, et al. 2024. “Dictionary Learning for Integrative, Multimodal and Scalable Single-Cell Analysis.” Nat. Biotechnol. 42 (2): 293–304. https://www.nature.com/articles/s41587-023-01767-y.
Love, Michael I, Wolfgang Huber, and Simon Anders. 2014. “Moderated Estimation of Fold Change and Dispersion for RNA-seq Data with DESeq2.” Genome Biol. 15 (12): 550. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-014-0550-8.
McKenna, Aaron, Matthew Hanna, Eric Banks, Andrey Sivachenko, Kristian Cibulskis, Andrew Kernytsky, Kiran Garimella, et al. 2010. “The Genome Analysis Toolkit: A MapReduce Framework for Analyzing Next-Generation DNA Sequencing Data.” Genome Res. 20 (9): 1297–1303. https://genome.cshlp.org/content/20/9/1297.long.
Palla, Giovanni, Hannah Spitzer, Michal Klein, David Fischer, Anna Christina Schaar, Louis Benedikt Kuemmerle, Sergei Rybakov, et al. 2022. “Squidpy: A Scalable Framework for Spatial Omics Analysis.” Nat. Methods 19 (2): 171–78. https://www.nature.com/articles/s41592-021-01358-2.
Stuart, Tim, Avi Srivastava, Shaista Madad, Caleb A Lareau, and Rahul Satija. 2022. “Author Correction: Single-Cell Chromatin State Analysis with Signac.” Nat. Methods 19 (2): 257. https://www.nature.com/articles/s41592-021-01282-5.
Wolf, F Alexander, Philipp Angerer, and Fabian J Theis. 2018. “SCANPY: Large-Scale Single-Cell Gene Expression Data Analysis.” Genome Biol. 19 (1): 15. https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1382-0.
Zhang, Kai, Nathan R Zemke, Ethan J Armand, and Bing Ren. 2024. “A Fast, Scalable and Versatile Tool for Analysis of Single-Cell Omics Data.” Nat. Methods 21 (2): 217–27.