Changes between Version 16 and Version 17 of SOP/scRNA-seq
- Timestamp:
- 08/05/20 13:13:45 (4 years ago)
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SOP/scRNA-seq
v16 v17 99 99 }}} 100 100 101 * Using Harmony from within Seurat (please see I. Korsunsky ''et al.'' “Fast, sensitive and accurate integration of single-cell data with Harmony”, ''Nature Methods'' '''16''', 1289-1296 (2019) and the documentation for the RunHarmony function):101 * Using Harmony from within Seurat (please see I. Korsunsky ''et al.'' “Fast, sensitive and accurate integration of single-cell data with Harmony”, ''Nature Methods'' '''16''', 1289-1296 (2019), the details of the Harmony algorithm linked below and the documentation for the RunHarmony function): 102 102 {{{ 103 103 library(Seurat) … … 121 121 }}} 122 122 123 * Using LIGER (v 0.4.2.9000) from within Seurat (please see J.D. Welsh ''et al.'' “Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity”, ''Nature Biotechnology'' '''37''', 1873–1887 (2019) andthe documentation for the RunOptimizeALS and RunQuantileAlignSNF functions):123 * Using LIGER (v 0.4.2.9000) from within Seurat (please see J.D. Welsh ''et al.'' “Single-Cell Multi-omic Integration Compares and Contrasts Features of Brain Cell Identity”, ''Nature Biotechnology'' '''37''', 1873–1887 (2019), the LIGER documentation/vignettes the documentation for the RunOptimizeALS and RunQuantileAlignSNF functions): 124 124 {{{ 125 125 library(Seurat) … … 140 140 all <- RunQuantileAlignSNF(all, split.by = "batch") 141 141 142 # When generating UMAP or another embedding, be sure to use the reduction from integrated nonnegative factorization ("iNMF").142 # When generating UMAP or another embedding, be sure to use the reduction from the integrated nonnegative factorization ("iNMF"). 143 143 all <- RunUMAP(all, dims = 1:ncol(all[["iNMF"]]), reduction = "iNMF") 144 145 # The commands above use default values for the default values for the rank, k, of the NMF and the homogeneity parameter, lambda. 146 # Generally, the rank should be chosen to be large enough to capture structure in the data matrix, yet small enough that the factorization 147 # gives reproducible interpretations under multiple non-unique solutions. Increasing the homogeneity parameter places greater emphasis 148 # on the common factors in the integration. The heuristic functions suggestK and suggestLambda can be used to guide the data-set-specific 149 # adjustment of these two parameters. 144 150 }}} 145 151 === Export expression and dimensional analysis data for interactive viewing === … … 176 182 * [https://learn.gencore.bio.nyu.edu/single-cell-rnaseq/ Single cell RNA sequencing, NYU]. 177 183 * [https://github.com/seandavi/awesome-single-cell Awesome-single-cell, Sean Davis] 184 * [http://htmlpreview.github.io/?https://github.com/immunogenomics/harmony/blob/master/docs/advanced.html, Detailed Harmony walkthrough] 185 * [https://macoskolab.github.io/liger/, LIGER instructions and vignettes]
