Olig Analysis

Last updated: 2019-10-29

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Knit directory: fgf_alldata/

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library(GEOquery)

Loading required package: Biobase

Loading required package: BiocGenerics

Loading required package: parallel


Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    anyDuplicated, append, as.data.frame, basename, cbind,
    colMeans, colnames, colSums, dirname, do.call, duplicated,
    eval, evalq, Filter, Find, get, grep, grepl, intersect,
    is.unsorted, lapply, lengths, Map, mapply, match, mget, order,
    paste, pmax, pmax.int, pmin, pmin.int, Position, rank, rbind,
    Reduce, rowMeans, rownames, rowSums, sapply, setdiff, sort,
    table, tapply, union, unique, unsplit, which, which.max,
    which.min

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.

Setting options('download.file.method.GEOquery'='auto')

Setting options('GEOquery.inmemory.gpl'=FALSE)

library(here)

here() starts at /nfsdata/projects/dylan/fgf_alldata

library(Seurat)
library(tidyverse)

── Attaching packages ────────────────────────────────── tidyverse 1.2.1 ──

✔ ggplot2 3.2.1          ✔ purrr   0.3.2     
✔ tibble  2.1.3          ✔ dplyr   0.8.3     
✔ tidyr   0.8.3          ✔ stringr 1.4.0     
✔ readr   1.3.1.9000     ✔ forcats 0.4.0

── Conflicts ───────────────────────────────────── tidyverse_conflicts() ──
✖ dplyr::combine()    masks Biobase::combine(), BiocGenerics::combine()
✖ dplyr::filter()     masks stats::filter()
✖ dplyr::lag()        masks stats::lag()
✖ ggplot2::Position() masks BiocGenerics::Position(), base::Position()

library(future)
library(data.table)


Attaching package: 'data.table'

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    transpose

library(rstatix)


Attaching package: 'rstatix'

The following object is masked from 'package:stats':

    filter

plan(multiprocess, workers=30)
options(future.globals.maxSize = 8000 * 1024^2)

gse<-getGEO("GSE75330", GSEMatrix=T)
counts<-fread("/projects/dylan/fgf1/oligodendrocyte_figure/GSE75330_Marques_et_al_mol_counts2.tab")
counts<-as.data.frame(counts)
rownames(counts)<-counts[,1]
counts<-counts[,-1]
cellid<-pData(phenoData(gse[[1]]))[c(1,44)]
names(cellid)<-c("cell","label")
cellid<-data.frame(sapply(cellid, function(x) as.character(x)), stringsAsFactors = F)
counts<-counts[,colnames(counts)%in%cellid$cell]
cellid<-cellid[cellid$cell%in%colnames(counts),]
cellid<-cellid[match(colnames(counts),cellid$cell),]

CreateSeuratObject(counts=counts) %>% 
  SCTransform(verbose = F, return.only.var.genes = F) %>% 
  RunPCA(verbose=T) %>% RunUMAP(dims=1:10) -> branco

Warning: Feature names cannot have underscores ('_'), replacing with dashes
('-')

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Warning: The default method for RunUMAP has changed from calling Python UMAP via reticulate to the R-native UWOT using the cosine metric
To use Python UMAP via reticulate, set umap.method to 'umap-learn' and metric to 'correlation'
This message will be shown once per session

branco$label<-cellid$label
Idents(branco)<-"label"
branco_sub<-subset(branco, cells=WhichCells(branco, idents=c("PPR"), invert=T))
branco_sub<-RenameIdents(branco_sub, "MOL2"="MOL1")
branco_sub<-RenameIdents(branco_sub, "MOL3"="MOL1")
branco_sub<-RenameIdents(branco_sub, "MOL4"="MOL1")
branco_sub<-RenameIdents(branco_sub, "MOL5"="MOL1")
branco_sub<-RenameIdents(branco_sub, "MOL6"="MOL1")
branco_sub<-RenameIdents(branco_sub, "NFOL1"="NFOL")
branco_sub<-RenameIdents(branco_sub, "NFOL2"="NFOL")
branco_sub<-RenameIdents(branco_sub, "MFOL1"="MFOL")
branco_sub<-RenameIdents(branco_sub, "MFOL2"="MFOL")

oliglist <- list(branco=branco_sub, olig=olig)
olig.features <- SelectIntegrationFeatures(object.list = oliglist, nfeatures = 3000)
oliglist <- PrepSCTIntegration(object.list = oliglist, anchor.features = olig.features, 
    verbose = FALSE)
olig.anchors <- FindTransferAnchors(reference = oliglist[["branco"]], 
                                    query = oliglist[["olig"]], normalization.method = "SCT", 
                                    features = olig.features)
predictions <- TransferData(anchorset = olig.anchors, refdata = branco_sub@active.ident, 
    dims = 1:30)
hist(predictions$prediction.score.max)

Version	Author	Date
3b5cbe7	Full Name	2019-10-28

olig <- AddMetaData(object = olig, metadata = predictions)
table(olig$predicted.id)


 COP MFOL MOL1 NFOL  OPC 
1004 2172 8049  760 3761

DimPlot(olig, group.by = "predicted.id")

Version	Author	Date
3b5cbe7	Full Name	2019-10-28

olig_sub<-subset(olig, subset=prediction.score.max>0.5)

olig_sub %>% 
  ScaleData(verbose = F, vars.to.regress = c("percent.mito","percent.ribo")) %>% 
  RunPCA(verbose=T) %>% FindNeighbors(dims = 1:20) %>% RunUMAP(dims = 1:20) %>% 
  FindClusters(resolution = 0.2) -> olig_sub

Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 15274
Number of edges: 509268

Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9281
Number of communities: 8
Elapsed time: 2 seconds

DimPlot(olig_sub, label = T)

Warning: Using `as.character()` on a quosure is deprecated as of rlang 0.3.0.
Please use `as_label()` or `as_name()` instead.
This warning is displayed once per session.

Version	Author	Date
3b5cbe7	Full Name	2019-10-28

olig_sub <- subset(olig_sub, ident=c(3,4,6), invert=T)
olig_sub %>% 
  ScaleData(verbose = F, vars.to.regress = c("percent.mito","percent.ribo")) %>% 
  RunPCA(verbose=T) %>% FindNeighbors(dims = 1:20) %>% RunUMAP(dims = 1:20) %>% 
  FindClusters(resolution = 0.2) -> olig_sub

Warning in PrepDR(object = object, features = features, verbose = verbose):
The following 1 features requested have zero variance (running reduction
without them): 9130410C08Rik

Modularity Optimizer version 1.3.0 by Ludo Waltman and Nees Jan van Eck

Number of nodes: 13543
Number of edges: 432866

Running Louvain algorithm...
Maximum modularity in 10 random starts: 0.9161
Number of communities: 5
Elapsed time: 2 seconds

Idents(olig_sub)<-"predicted.id"
DimPlot(olig_sub, label = T)

Version	Author	Date
3b5cbe7	Full Name	2019-10-28

saveRDS(olig_sub, here("data/glia/olig_labeled.RDS"))

sessionInfo()

R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Storage

Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.3.so

locale:
 [1] LC_CTYPE=en_DK.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_DK.UTF-8        LC_COLLATE=en_DK.UTF-8    
 [5] LC_MONETARY=en_DK.UTF-8    LC_MESSAGES=en_DK.UTF-8   
 [7] LC_PAPER=en_DK.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats     graphics  grDevices utils     datasets  methods  
[8] base     

other attached packages:
 [1] rstatix_0.1.1       data.table_1.12.2   future_1.14.0      
 [4] forcats_0.4.0       stringr_1.4.0       dplyr_0.8.3        
 [7] purrr_0.3.2         readr_1.3.1.9000    tidyr_0.8.3        
[10] tibble_2.1.3        ggplot2_3.2.1       tidyverse_1.2.1    
[13] Seurat_3.0.3.9036   here_0.1            GEOquery_2.50.5    
[16] Biobase_2.42.0      BiocGenerics_0.28.0

loaded via a namespace (and not attached):
  [1] Rtsne_0.15          colorspace_1.4-1    rio_0.5.16         
  [4] ggridges_0.5.1      rprojroot_1.3-2     fs_1.3.1           
  [7] rstudioapi_0.10     leiden_0.3.1        listenv_0.7.0      
 [10] npsurv_0.4-0        ggrepel_0.8.1       RSpectra_0.15-0    
 [13] lubridate_1.7.4     xml2_1.2.0          codetools_0.2-16   
 [16] splines_3.5.3       R.methodsS3_1.7.1   lsei_1.2-0         
 [19] knitr_1.23          zeallot_0.1.0       jsonlite_1.6       
 [22] workflowr_1.4.0     broom_0.5.2         ica_1.0-2          
 [25] cluster_2.1.0       png_0.1-7           R.oo_1.22.0        
 [28] uwot_0.1.3          sctransform_0.2.0   compiler_3.5.3     
 [31] httr_1.4.1          backports_1.1.4     assertthat_0.2.1   
 [34] Matrix_1.2-17       lazyeval_0.2.2      cli_1.1.0          
 [37] limma_3.38.3        htmltools_0.3.6     tools_3.5.3        
 [40] rsvd_1.0.2          igraph_1.2.4.1      gtable_0.3.0       
 [43] glue_1.3.1          RANN_2.6.1          reshape2_1.4.3     
 [46] Rcpp_1.0.2          carData_3.0-2       cellranger_1.1.0   
 [49] vctrs_0.2.0         gdata_2.18.0        ape_5.3            
 [52] nlme_3.1-140        gbRd_0.4-11         lmtest_0.9-37      
 [55] xfun_0.8            globals_0.12.4      openxlsx_4.1.0.1   
 [58] rvest_0.3.4         irlba_2.3.3         gtools_3.8.1       
 [61] MASS_7.3-51.4       zoo_1.8-6           scales_1.0.0       
 [64] hms_0.5.0           RColorBrewer_1.1-2  curl_4.0           
 [67] yaml_2.2.0          reticulate_1.13     pbapply_1.4-1      
 [70] gridExtra_2.3       stringi_1.4.3       highr_0.8          
 [73] caTools_1.17.1.2    zip_2.0.3           bibtex_0.4.2       
 [76] Rdpack_0.11-0       SDMTools_1.1-221.1  rlang_0.4.0        
 [79] pkgconfig_2.0.2     bitops_1.0-6        evaluate_0.14      
 [82] lattice_0.20-38     ROCR_1.0-7          labeling_0.3       
 [85] htmlwidgets_1.3     cowplot_1.0.0       tidyselect_0.2.5   
 [88] RcppAnnoy_0.0.12    plyr_1.8.4          magrittr_1.5       
 [91] R6_2.4.0            gplots_3.0.1.1      generics_0.0.2     
 [94] foreign_0.8-71      withr_2.1.2         haven_2.1.0        
 [97] pillar_1.4.2        whisker_0.3-2       fitdistrplus_1.0-14
[100] abind_1.4-5         survival_2.44-1.1   future.apply_1.3.0 
[103] tsne_0.1-3          car_3.0-3           modelr_0.1.4       
[106] crayon_1.3.4        KernSmooth_2.23-15  plotly_4.9.0       
[109] rmarkdown_1.13      readxl_1.3.1        grid_3.5.3         
[112] git2r_0.25.2        metap_1.1           digest_0.6.20      
[115] R.utils_2.9.0       RcppParallel_4.4.3  munsell_0.5.0      
[118] viridisLite_0.3.0