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library(SingleCellExperiment)
Loading required package: SummarizedExperiment
Loading required package: MatrixGenerics
Loading required package: matrixStats
Attaching package: 'MatrixGenerics'
The following objects are masked from 'package:matrixStats':
colAlls, colAnyNAs, colAnys, colAvgsPerRowSet, colCollapse,
colCounts, colCummaxs, colCummins, colCumprods, colCumsums,
colDiffs, colIQRDiffs, colIQRs, colLogSumExps, colMadDiffs,
colMads, colMaxs, colMeans2, colMedians, colMins, colOrderStats,
colProds, colQuantiles, colRanges, colRanks, colSdDiffs, colSds,
colSums2, colTabulates, colVarDiffs, colVars, colWeightedMads,
colWeightedMeans, colWeightedMedians, colWeightedSds,
colWeightedVars, rowAlls, rowAnyNAs, rowAnys, rowAvgsPerColSet,
rowCollapse, rowCounts, rowCummaxs, rowCummins, rowCumprods,
rowCumsums, rowDiffs, rowIQRDiffs, rowIQRs, rowLogSumExps,
rowMadDiffs, rowMads, rowMaxs, rowMeans2, rowMedians, rowMins,
rowOrderStats, rowProds, rowQuantiles, rowRanges, rowRanks,
rowSdDiffs, rowSds, rowSums2, rowTabulates, rowVarDiffs, rowVars,
rowWeightedMads, rowWeightedMeans, rowWeightedMedians,
rowWeightedSds, rowWeightedVars
Loading required package: GenomicRanges
Loading required package: stats4
Loading required package: BiocGenerics
Attaching package: 'BiocGenerics'
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, colnames,
dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
union, unique, unsplit, which.max, which.min
Loading required package: S4Vectors
Attaching package: 'S4Vectors'
The following objects are masked from 'package:base':
expand.grid, I, unname
Loading required package: IRanges
Loading required package: GenomeInfoDb
Loading required package: Biobase
Welcome to Bioconductor
Vignettes contain introductory material; view with
'browseVignettes()'. To cite Bioconductor, see
'citation("Biobase")', and for packages 'citation("pkgname")'.
Attaching package: 'Biobase'
The following object is masked from 'package:MatrixGenerics':
rowMedians
The following objects are masked from 'package:matrixStats':
anyMissing, rowMedians
library(dplyr)
Attaching package: 'dplyr'
The following object is masked from 'package:Biobase':
combine
The following objects are masked from 'package:GenomicRanges':
intersect, setdiff, union
The following object is masked from 'package:GenomeInfoDb':
intersect
The following objects are masked from 'package:IRanges':
collapse, desc, intersect, setdiff, slice, union
The following objects are masked from 'package:S4Vectors':
first, intersect, rename, setdiff, setequal, union
The following objects are masked from 'package:BiocGenerics':
combine, intersect, setdiff, union
The following object is masked from 'package:matrixStats':
count
The following objects are masked from 'package:stats':
filter, lag
The following objects are masked from 'package:base':
intersect, setdiff, setequal, union
library(purrr)
Attaching package: 'purrr'
The following object is masked from 'package:GenomicRanges':
reduce
The following object is masked from 'package:IRanges':
reduce
library(tibble)
library(scater)
Loading required package: scuttle
Loading required package: ggplot2
<- readRDS(here::here("data", "real_data", "astrocyte.rds")) astrocyte
<- readRDS(
scanpy_default ::here("results", "real_data", "astrocyte-scanpy_t_rankby_raw.rds")
here
)
<- readRDS(
seurat_default ::here("results", "real_data", "astrocyte-seurat_wilcox.rds")
here )
Work on Astro_THAL_Lat for now.
|>
scanpy_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_THAL_lat")
# A tibble: 2,000 × 7
cluster gene scaled_statistic p_value p_value_adj log_fc raw_statistic
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Astro_THAL… Trpm3 39.3 2.72e-206 5.44e-203 2.49 0
2 Astro_THAL… Erbb4 31.9 1.96e-129 1.31e-126 2.72 0
3 Astro_THAL… Kcnd2 31.5 3.79e-134 3.79e-131 2.53 0
4 Astro_THAL… Aldh… 24.5 2.83e- 80 7.07e- 78 3.18 0
5 Astro_THAL… Plcb1 22.2 1.39e- 75 2.54e- 73 1.92 0
6 Astro_THAL… Slc4… 19.0 1.40e- 62 1.65e- 60 1.21 0
7 Astro_THAL… Rgs6 18.5 7.71e- 58 7.01e- 56 1.73 0
8 Astro_THAL… Lrp1b 16.8 1.12e- 50 8.65e- 49 1.30 0
9 Astro_THAL… Nrxn3 16.6 3.83e- 47 2.64e- 45 2.22 0
10 Astro_THAL… Esrrg 15.9 1.66e- 43 1.04e- 41 2.72 0
# … with 1,990 more rows
|>
seurat_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_THAL_lat")
# A tibble: 397 × 7
p_value p_value_adj cluster log_fc gene raw_statistic scaled_statistic
<dbl> <dbl> <fct> <dbl> <chr> <dbl> <dbl>
1 4.54e-119 9.08e-116 Astro_THAL… 2.09 Aldh… 0 0
2 5.66e-103 1.13e- 99 Astro_THAL… 1.47 Trpm3 0 0
3 1.01e- 91 2.02e- 88 Astro_THAL… 1.35 Erbb4 0 0
4 3.05e- 87 6.10e- 84 Astro_THAL… 1.37 Esrrg 0 0
5 7.49e- 77 1.50e- 73 Astro_THAL… 1.27 Kcnd2 0 0
6 6.60e- 75 1.32e- 71 Astro_THAL… -1.61 Slc1… 0 0
7 6.84e- 72 1.37e- 68 Astro_THAL… 1.18 Car10 0 0
8 7.67e- 72 1.53e- 68 Astro_THAL… 1.39 Plcb1 0 0
9 6.22e- 66 1.24e- 62 Astro_THAL… 1.36 Nrxn3 0 0
10 2.77e- 65 5.54e- 62 Astro_THAL… 1.10 Sntg1 0 0
# … with 387 more rows
Only Seurat finds Car10
|>
scanpy_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_THAL_lat") |>
mutate(n = 1:n()) |>
filter(gene == "Car10")
# A tibble: 1 × 8
cluster gene scaled_statistic p_value p_value_adj log_fc raw_statistic n
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <int>
1 Astro_… Car10 12.9 1.52e-31 5.16e-30 2.61 0 20
Astro_STR
Efemp1, Gfra1, Thbs4, Zfhx3
|>
scanpy_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_STR")
# A tibble: 2,000 × 7
cluster gene scaled_statistic p_value p_value_adj log_fc raw_statistic
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Astro_STR Slc1a2 12.4 1.37e-21 9.79e-20 1.21 0
2 Astro_STR Prex2 11.5 2.30e-19 1.48e-17 1.48 0
3 Astro_STR Cst3 10.5 3.49e-17 1.99e-15 1.60 0
4 Astro_STR Malat1 9.21 1.50e-14 7.29e-13 0.495 0
5 Astro_STR Zbtb20 8.05 3.53e-12 1.50e-10 0.764 0
6 Astro_STR Mgat5 7.37 1.11e-10 3.84e- 9 1.72 0
7 Astro_STR Tspan7 7.06 3.77e-10 1.23e- 8 1.21 0
8 Astro_STR Rmst 6.85 1.15e- 9 3.66e- 8 1.59 0
9 Astro_STR Gfra1 6.18 2.42e- 8 6.72e- 7 2.26 0
10 Astro_STR Gnao1 6.17 2.13e- 8 6.09e- 7 1.04 0
# … with 1,990 more rows
|>
seurat_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_STR")
# A tibble: 234 × 7
p_value p_value_adj cluster log_fc gene raw_statistic scaled_statistic
<dbl> <dbl> <fct> <dbl> <chr> <dbl> <dbl>
1 6.16e-21 1.23e-17 Astro_STR -3.05 Kcnd2 0 0
2 4.70e-19 9.40e-16 Astro_STR 0.920 Gfra1 0 0
3 9.43e-18 1.89e-14 Astro_STR 1.28 Cst3 0 0
4 2.42e-16 4.83e-13 Astro_STR 1.01 Prex2 0 0
5 2.57e-16 5.14e-13 Astro_STR -1.41 Lrp1b 0 0
6 5.43e-16 1.09e-12 Astro_STR 1.02 Rcan2 0 0
7 4.72e-15 9.44e-12 Astro_STR 0.798 Slc1a2 0 0
8 9.44e-14 1.89e-10 Astro_STR 1.19 Mgat5 0 0
9 2.06e-13 4.11e-10 Astro_STR 0.430 Malat1 0 0
10 3.42e-13 6.84e-10 Astro_STR -2.30 Erbb4 0 0
# … with 224 more rows
plotExpression(astrocyte, x = "label", "Prex2")
plotExpression(astrocyte, x = "label", "Cst3")
plotExpression(astrocyte, x = "label", "Mgat5")
Kcnd2 down-regulated
|>
scanpy_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_HPC")
# A tibble: 2,000 × 7
cluster gene scaled_statistic p_value p_value_adj log_fc raw_statistic
<chr> <chr> <dbl> <dbl> <dbl> <dbl> <dbl>
1 Astro_HPC Slc1a2 18.2 1.93e-55 5.50e-53 1.08 0
2 Astro_HPC Tspan7 12.4 1.34e-29 1.58e-27 1.17 0
3 Astro_HPC Wdr17 12.2 6.60e-29 6.95e-27 0.882 0
4 Astro_HPC Ptprt 11.4 1.63e-25 1.30e-23 1.12 0
5 Astro_HPC Tcf4 11.1 1.96e-24 1.35e-22 1.09 0
6 Astro_HPC Slc1a3 10.1 1.60e-21 9.14e-20 0.800 0
7 Astro_HPC Lsamp 10.1 5.19e-21 2.88e-19 0.602 0
8 Astro_HPC Gnao1 10.0 6.05e-21 3.27e-19 1.01 0
9 Astro_HPC Cadps 9.86 8.80e-20 3.91e-18 2.84 0
10 Astro_HPC Clmn 9.82 6.06e-20 3.03e-18 1.30 0
# … with 1,990 more rows
|>
seurat_default pluck("result") |>
as_tibble() |>
filter(cluster == "Astro_HPC")
# A tibble: 305 × 7
p_value p_value_adj cluster log_fc gene raw_statistic scaled_statistic
<dbl> <dbl> <fct> <dbl> <chr> <dbl> <dbl>
1 3.47e-59 6.94e-56 Astro_HPC 1.09 Cadps 0 0
2 4.61e-53 9.22e-50 Astro_HPC -2.73 Kcnd2 0 0
3 3.37e-43 6.74e-40 Astro_HPC -2.54 Erbb4 0 0
4 1.61e-42 3.22e-39 Astro_HPC -1.96 Trpm3 0 0
5 2.38e-42 4.75e-39 Astro_HPC -1.57 Fry 0 0
6 1.40e-34 2.80e-31 Astro_HPC -1.48 Gabbr2 0 0
7 2.20e-32 4.40e-29 Astro_HPC 0.674 Slc1a2 0 0
8 5.23e-30 1.05e-26 Astro_HPC -2.22 Gria1 0 0
9 1.05e-28 2.10e-25 Astro_HPC -0.961 Fgf14 0 0
10 8.24e-28 1.65e-24 Astro_HPC 0.859 Tcf4 0 0
# … with 295 more rows
plotExpression(astrocyte, x = "label", "Slc1a2")
plotExpression(astrocyte, x = "label", "Pdgfd")
plotExpression(astrocyte, x = "label", "Cadps")
plotExpression(astrocyte, x = "label", "Kcnd2")
::session_info() devtools
─ Session info ──────────────────────────────────────────────────────────────
hash: flag: Bolivia, woman singer: dark skin tone, headphone
setting value
version R version 4.1.2 (2021-11-01)
os Red Hat Enterprise Linux 9.2 (Plow)
system x86_64, linux-gnu
ui X11
language (EN)
collate en_AU.UTF-8
ctype en_AU.UTF-8
tz Australia/Melbourne
date 2024-01-01
pandoc 2.18 @ /apps/easybuild-2022/easybuild/software/MPI/GCC/11.3.0/OpenMPI/4.1.4/RStudio-Server/2022.07.2+576-Java-11-R-4.1.2/bin/pandoc/ (via rmarkdown)
─ Packages ───────────────────────────────────────────────────────────────────
package * version date (UTC) lib source
assertthat 0.2.1 2019-03-21 [2] CRAN (R 4.1.2)
beachmat 2.10.0 2021-10-26 [1] Bioconductor
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bslib 0.3.1 2021-10-06 [1] CRAN (R 4.1.0)
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callr 3.7.0 2021-04-20 [2] CRAN (R 4.1.2)
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devtools 2.4.2 2021-06-07 [2] CRAN (R 4.1.2)
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fansi 1.0.4 2023-01-22 [1] CRAN (R 4.1.0)
farver 2.1.1 2022-07-06 [1] CRAN (R 4.1.0)
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GenomeInfoDb * 1.30.0 2021-10-26 [1] Bioconductor
GenomeInfoDbData 1.2.7 2021-12-03 [1] Bioconductor
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ggplot2 * 3.3.6 2022-05-03 [1] CRAN (R 4.1.0)
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git2r 0.28.0 2021-01-10 [2] CRAN (R 4.1.2)
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gridExtra 2.3 2017-09-09 [2] CRAN (R 4.1.2)
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here 1.0.1 2020-12-13 [1] CRAN (R 4.1.0)
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later 1.3.0 2021-08-18 [1] CRAN (R 4.1.0)
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viridisLite 0.4.2 2023-05-02 [1] CRAN (R 4.1.0)
whisker 0.4 2019-08-28 [2] CRAN (R 4.1.2)
withr 2.5.0 2022-03-03 [1] CRAN (R 4.1.0)
workflowr 1.7.0 2021-12-21 [1] CRAN (R 4.1.0)
xfun 0.31 2022-05-10 [1] CRAN (R 4.1.0)
XVector 0.34.0 2021-10-26 [1] Bioconductor
yaml 2.3.5 2022-02-21 [1] CRAN (R 4.1.0)
zlibbioc 1.40.0 2021-10-26 [1] Bioconductor
[1] /home/jpullin/R/x86_64-pc-linux-gnu-library/4.1
[2] /apps/easybuild-2022/easybuild/software/MPI/GCC/11.3.0/OpenMPI/4.1.4/R/4.1.2/lib64/R/library
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