Test
Thomas Ashhurst
13/03/2021
R Markdown
This is an R Markdown document. Markdown is a simple formatting syntax for authoring HTML, PDF, and MS Word documents. For more details on using R Markdown see http://rmarkdown.rstudio.com.
When you click the Knit button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. You can embed an R code chunk like this:
library(Spectre)
packageVersion('Spectre')
## [1] '0.4.0'
summary(cars)
## speed dist
## Min. : 4.0 Min. : 2.00
## 1st Qu.:12.0 1st Qu.: 26.00
## Median :15.0 Median : 36.00
## Mean :15.4 Mean : 42.98
## 3rd Qu.:19.0 3rd Qu.: 56.00
## Max. :25.0 Max. :120.00
dat <- demo.clustered
dat
## FileName NK11 CD3 CD45 Ly6G CD11b
## 1: CNS_Mock_01.csv 42.3719 40.098700 6885.08 -344.7830 14787.30
## 2: CNS_Mock_01.csv 42.9586 119.014000 1780.29 -429.6650 5665.73
## 3: CNS_Mock_01.csv 59.2366 206.238000 10248.30 -1603.8400 19894.30
## 4: CNS_Mock_01.csv 364.9480 -0.233878 3740.04 -815.9800 9509.43
## 5: CNS_Mock_01.csv 440.2470 40.035200 9191.38 40.5055 5745.82
## ---
## 169000: CNS_WNV_D7_06.csv 910.8890 72.856100 31466.20 -316.5570 28467.80
## 169001: CNS_WNV_D7_06.csv -10.2642 64.188700 45188.00 -540.5140 22734.00
## 169002: CNS_WNV_D7_06.csv -184.2910 -9.445650 11842.60 -97.9383 17237.00
## 169003: CNS_WNV_D7_06.csv 248.3860 229.986000 32288.20 -681.1630 19255.80
## 169004: CNS_WNV_D7_06.csv 738.9810 95.470300 46185.10 -1004.6000 22957.80
## B220 CD8a Ly6C CD4 NK11_asinh CD3_asinh
## 1: -40.2399 83.7175 958.7000 711.0720 0.04235923 0.040087962
## 2: 86.6673 34.7219 448.2590 307.2720 0.04294540 0.118734817
## 3: 427.8310 285.8800 1008.8300 707.0940 0.05920201 0.204803270
## 4: 182.4200 333.6050 440.0710 249.7840 0.35729716 -0.000233878
## 5: -211.6940 149.2200 87.4815 867.5700 0.42713953 0.040024513
## ---
## 169000: -7.7972 -271.8040 12023.7000 1103.0500 0.81693878 0.072791800
## 169001: 202.4110 -936.4920 4188.3300 315.9400 -0.01026402 0.064144703
## 169002: 123.4760 -219.9320 8923.4000 -453.4640 -0.18326344 -0.009445510
## 169003: -656.0540 -201.5880 10365.7000 61.6765 0.24590035 0.228005328
## 169004: -661.6280 72.3356 9704.4700 -31.8532 0.68430866 0.095325863
## CD45_asinh Ly6G_asinh CD11b_asinh B220_asinh CD8a_asinh Ly6C_asinh
## 1: 2.627736 -0.33829345 3.388057 -0.040229048 0.08362002 0.8518665
## 2: 1.340828 -0.41743573 2.435282 0.086559169 0.03471493 0.4344615
## 3: 3.022631 -1.25101677 3.684212 0.415750122 0.28212257 0.8876036
## 4: 2.029655 -0.74509796 2.948184 0.181423123 0.32770787 0.4269784
## 5: 2.914359 0.04049443 2.449108 -0.210143906 0.14867171 0.0873703
## ---
## 169000: 4.142314 -0.31149515 4.042229 -0.007797121 -0.26856390 3.1817517
## 169001: 4.504101 -0.51715205 3.817492 0.201053740 -0.83574631 2.1394053
## 169002: 3.166628 -0.09778240 3.541046 0.123164374 -0.21819650 2.8849492
## 169003: 4.168089 -0.63716643 3.651633 -0.616293228 -0.20024703 3.0339681
## 169004: 4.525922 -0.88462254 3.827279 -0.620947819 0.07227267 2.9683779
## CD4_asinh Sample Group Batch FlowSOM_cluster FlowSOM_metacluster
## 1: 0.66171351 01_Mock_01 Mock A 23 2
## 2: 0.30263135 01_Mock_01 Mock A 55 2
## 3: 0.65846851 01_Mock_01 Mock A 64 2
## 4: 0.24725691 01_Mock_01 Mock A 53 2
## 5: 0.78456678 01_Mock_01 Mock A 110 4
## ---
## 169000: 0.95239703 12_WNV_06 WNV A 72 3
## 169001: 0.31090687 12_WNV_06 WNV A 46 3
## 169002: -0.43920651 12_WNV_06 WNV A 133 3
## 169003: 0.06163746 12_WNV_06 WNV A 133 3
## 169004: -0.03184782 12_WNV_06 WNV A 103 3
## Population UMAP_X UMAP_Y
## 1: Microglia -2.3603757 6.201213
## 2: Microglia 2.7505242 7.119595
## 3: Microglia -2.9486033 4.012670
## 4: Microglia 0.6482904 6.481466
## 5: NK cells -2.3941295 6.975885
## ---
## 169000: Infil Macrophages -2.9640724 -5.058265
## 169001: Infil Macrophages -1.2644785 -3.555824
## 169002: Infil Macrophages -2.3592682 -2.429467
## 169003: Infil Macrophages -1.9531062 -4.049705
## 169004: Infil Macrophages -0.7404098 -4.686928
## Loading required package: ggplot2
## Loading required package: scales
## Loading required package: colorRamps
## Loading required package: ggthemes
## Loading required package: RColorBrewer
## Non-numeric values detected in col.axis -- using col.type = 'factor'
## Loading required package: ggpointdensity