Stathmin 2 expression
Katharina Hembach
21/01/2021
Last updated: 2021-02-18
Checks: 7 0
Knit directory: neural_scRNAseq/
This reproducible R Markdown analysis was created with workflowr (version 1.6.2). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.
Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.
Great job! The global environment was empty. Objects defined in the global environment can affect the analysis in your R Markdown file in unknown ways. For reproduciblity it's best to always run the code in an empty environment.
The command set.seed(20200522) was run prior to running the code in the R Markdown file. Setting a seed ensures that any results that rely on randomness, e.g. subsampling or permutations, are reproducible.
Great job! Recording the operating system, R version, and package versions is critical for reproducibility.
Nice! There were no cached chunks for this analysis, so you can be confident that you successfully produced the results during this run.
Great job! Using relative paths to the files within your workflowr project makes it easier to run your code on other machines.
Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.
The results in this page were generated with repository version 1755a27. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.
Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated:
Ignored files:
Ignored: .DS_Store
Ignored: .Rhistory
Ignored: .Rproj.user/
Ignored: ._.DS_Store
Ignored: ._Rplots.pdf
Ignored: .__workflowr.yml
Ignored: ._neural_scRNAseq.Rproj
Ignored: analysis/.DS_Store
Ignored: analysis/.Rhistory
Ignored: analysis/._.DS_Store
Ignored: analysis/._01-preprocessing.Rmd
Ignored: analysis/._01-preprocessing.html
Ignored: analysis/._02.1-SampleQC.Rmd
Ignored: analysis/._03-filtering.Rmd
Ignored: analysis/._04-clustering.Rmd
Ignored: analysis/._04-clustering.knit.md
Ignored: analysis/._04.1-cell_cycle.Rmd
Ignored: analysis/._05-annotation.Rmd
Ignored: analysis/._Lam-0-NSC_no_integration.Rmd
Ignored: analysis/._Lam-01-NSC_integration.Rmd
Ignored: analysis/._Lam-02-NSC_annotation.Rmd
Ignored: analysis/._NSC-1-clustering.Rmd
Ignored: analysis/._NSC-2-annotation.Rmd
Ignored: analysis/.__site.yml
Ignored: analysis/._additional_filtering.Rmd
Ignored: analysis/._additional_filtering_clustering.Rmd
Ignored: analysis/._index.Rmd
Ignored: analysis/._organoid-01-1-qualtiy-control.Rmd
Ignored: analysis/._organoid-01-clustering.Rmd
Ignored: analysis/._organoid-02-integration.Rmd
Ignored: analysis/._organoid-03-cluster_analysis.Rmd
Ignored: analysis/._organoid-04-group_integration.Rmd
Ignored: analysis/._organoid-04-stage_integration.Rmd
Ignored: analysis/._organoid-05-group_integration_cluster_analysis.Rmd
Ignored: analysis/._organoid-05-stage_integration_cluster_analysis.Rmd
Ignored: analysis/._organoid-06-1-prepare-sce.Rmd
Ignored: analysis/._organoid-06-conos-analysis-Seurat.Rmd
Ignored: analysis/._organoid-06-conos-analysis-function.Rmd
Ignored: analysis/._organoid-06-conos-analysis.Rmd
Ignored: analysis/._organoid-06-group-integration-conos-analysis.Rmd
Ignored: analysis/._organoid-07-conos-visualization.Rmd
Ignored: analysis/._organoid-07-group-integration-conos-visualization.Rmd
Ignored: analysis/._organoid-08-conos-comparison.Rmd
Ignored: analysis/._organoid-0x-sample_integration.Rmd
Ignored: analysis/01-preprocessing_cache/
Ignored: analysis/02-1-SampleQC_cache/
Ignored: analysis/02-quality_control_cache/
Ignored: analysis/02.1-SampleQC_cache/
Ignored: analysis/03-filtering_cache/
Ignored: analysis/04-clustering_cache/
Ignored: analysis/04.1-cell_cycle_cache/
Ignored: analysis/05-annotation_cache/
Ignored: analysis/06-clustering-all-timepoints_cache/
Ignored: analysis/07-cluster-analysis-all-timepoints_cache/
Ignored: analysis/Lam-01-NSC_integration_cache/
Ignored: analysis/Lam-02-NSC_annotation_cache/
Ignored: analysis/NSC-1-clustering_cache/
Ignored: analysis/NSC-2-annotation_cache/
Ignored: analysis/TDP-01-preprocessing_cache/
Ignored: analysis/TDP-02-quality_control_cache/
Ignored: analysis/TDP-03-filtering_cache/
Ignored: analysis/TDP-04-clustering_cache/
Ignored: analysis/TDP-05-00-filtering-plasmid-QC_cache/
Ignored: analysis/TDP-05-plasmid_expression_cache/
Ignored: analysis/TDP-06-cluster_analysis_cache/
Ignored: analysis/TDP-07-cluster_12_cache/
Ignored: analysis/TDP-08-00-clustering-HA-D96_cache/
Ignored: analysis/TDP-08-clustering-timeline-HA_cache/
Ignored: analysis/additional_filtering_cache/
Ignored: analysis/additional_filtering_clustering_cache/
Ignored: analysis/organoid-01-1-qualtiy-control_cache/
Ignored: analysis/organoid-01-clustering_cache/
Ignored: analysis/organoid-02-integration_cache/
Ignored: analysis/organoid-03-cluster_analysis_cache/
Ignored: analysis/organoid-04-group_integration_cache/
Ignored: analysis/organoid-04-stage_integration_cache/
Ignored: analysis/organoid-05-group_integration_cluster_analysis_cache/
Ignored: analysis/organoid-05-stage_integration_cluster_analysis_cache/
Ignored: analysis/organoid-06-conos-analysis_cache/
Ignored: analysis/organoid-06-conos-analysis_test_cache/
Ignored: analysis/organoid-06-group-integration-conos-analysis_cache/
Ignored: analysis/organoid-07-conos-visualization_cache/
Ignored: analysis/organoid-07-group-integration-conos-visualization_cache/
Ignored: analysis/organoid-08-conos-comparison_cache/
Ignored: analysis/organoid-0x-sample_integration_cache/
Ignored: analysis/sample5_QC_cache/
Ignored: analysis/timepoints-01-organoid-integration_cache/
Ignored: data/.DS_Store
Ignored: data/._.DS_Store
Ignored: data/._.smbdeleteAAA17ed8b4b
Ignored: data/._Lam_figure2_markers.R
Ignored: data/._Reactive_astrocytes_markers.xlsx
Ignored: data/._known_NSC_markers.R
Ignored: data/._known_cell_type_markers.R
Ignored: data/._metadata.csv
Ignored: data/._virus_cell_tropism_markers.R
Ignored: data/._~$Reactive_astrocytes_markers.xlsx
Ignored: data/data_sushi/
Ignored: data/filtered_feature_matrices/
Ignored: output/.DS_Store
Ignored: output/._.DS_Store
Ignored: output/._NSC_cluster2_marker_genes.txt
Ignored: output/._TDP-06-no_integration_cluster12_marker_genes.txt
Ignored: output/._TDP-06-no_integration_cluster13_marker_genes.txt
Ignored: output/._organoid_integration_cluster1_marker_genes.txt
Ignored: output/Lam-01-clustering.rds
Ignored: output/NSC_1_clustering.rds
Ignored: output/NSC_cluster1_marker_genes.txt
Ignored: output/NSC_cluster2_marker_genes.txt
Ignored: output/NSC_cluster3_marker_genes.txt
Ignored: output/NSC_cluster4_marker_genes.txt
Ignored: output/NSC_cluster5_marker_genes.txt
Ignored: output/NSC_cluster6_marker_genes.txt
Ignored: output/NSC_cluster7_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster0_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster10_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster11_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster12_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster13_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster14_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster15_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster16_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster17_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster1_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster2_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster3_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster4_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster5_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster6_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster7_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster8_marker_genes.txt
Ignored: output/TDP-06-no_integration_cluster9_marker_genes.txt
Ignored: output/TDP-06_scran_markers.rds
Ignored: output/additional_filtering.rds
Ignored: output/conos/
Ignored: output/conos_organoid-06-conos-analysis.rds
Ignored: output/conos_organoid-06-group-integration-conos-analysis.rds
Ignored: output/figures/
Ignored: output/organoid_integration_cluster10_marker_genes.txt
Ignored: output/organoid_integration_cluster11_marker_genes.txt
Ignored: output/organoid_integration_cluster12_marker_genes.txt
Ignored: output/organoid_integration_cluster13_marker_genes.txt
Ignored: output/organoid_integration_cluster14_marker_genes.txt
Ignored: output/organoid_integration_cluster15_marker_genes.txt
Ignored: output/organoid_integration_cluster16_marker_genes.txt
Ignored: output/organoid_integration_cluster17_marker_genes.txt
Ignored: output/organoid_integration_cluster1_marker_genes.txt
Ignored: output/organoid_integration_cluster2_marker_genes.txt
Ignored: output/organoid_integration_cluster3_marker_genes.txt
Ignored: output/organoid_integration_cluster4_marker_genes.txt
Ignored: output/organoid_integration_cluster5_marker_genes.txt
Ignored: output/organoid_integration_cluster6_marker_genes.txt
Ignored: output/organoid_integration_cluster7_marker_genes.txt
Ignored: output/organoid_integration_cluster8_marker_genes.txt
Ignored: output/organoid_integration_cluster9_marker_genes.txt
Ignored: output/sce_01_preprocessing.rds
Ignored: output/sce_02_quality_control.rds
Ignored: output/sce_03_filtering.rds
Ignored: output/sce_03_filtering_all_genes.rds
Ignored: output/sce_06-1-prepare-sce.rds
Ignored: output/sce_TDP_01_preprocessing.rds
Ignored: output/sce_TDP_02_quality_control.rds
Ignored: output/sce_TDP_03_filtering.rds
Ignored: output/sce_TDP_03_filtering_all_genes.rds
Ignored: output/sce_organoid-01-clustering.rds
Ignored: output/sce_preprocessing.rds
Ignored: output/so_04-group_integration.rds
Ignored: output/so_04-stage_integration.rds
Ignored: output/so_04_1_cell_cycle.rds
Ignored: output/so_04_clustering.rds
Ignored: output/so_06-clustering_all_timepoints.rds
Ignored: output/so_08-00_clustering_HA_D96.rds
Ignored: output/so_08-clustering_timeline_HA.rds
Ignored: output/so_0x-sample_integration.rds
Ignored: output/so_TDP-06-cluster-analysis.rds
Ignored: output/so_TDP_04_clustering.rds
Ignored: output/so_TDP_05_plasmid_expression.rds
Ignored: output/so_additional_filtering_clustering.rds
Ignored: output/so_integrated_organoid-02-integration.rds
Ignored: output/so_merged_organoid-02-integration.rds
Ignored: output/so_organoid-01-clustering.rds
Ignored: output/so_sample_organoid-01-clustering.rds
Ignored: scripts/.DS_Store
Ignored: scripts/._.DS_Store
Ignored: scripts/._bu_Rcode.R
Ignored: scripts/._plasmid_expression.sh
Untracked files:
Untracked: Rplots.pdf
Untracked: analysis/Lam-0-NSC_no_integration.Rmd
Untracked: analysis/additional_filtering.Rmd
Untracked: analysis/additional_filtering_clustering.Rmd
Untracked: analysis/organoid-01-1-qualtiy-control.Rmd
Untracked: analysis/organoid-06-conos-analysis-Seurat.Rmd
Untracked: analysis/organoid-06-conos-analysis-function.Rmd
Untracked: analysis/organoid-07-conos-visualization.Rmd
Untracked: analysis/organoid-07-group-integration-conos-visualization.Rmd
Untracked: analysis/organoid-08-conos-comparison.Rmd
Untracked: analysis/organoid-0x-sample_integration.Rmd
Untracked: analysis/sample5_QC.Rmd
Untracked: data/Homo_sapiens.GRCh38.98.sorted.gtf
Untracked: data/Kanton_et_al/
Untracked: data/Lam_et_al/
Untracked: data/Sep2020/
Untracked: data/reference/
Untracked: data/virus_cell_tropism_markers.R
Untracked: data/~$Reactive_astrocytes_markers.xlsx
Untracked: scripts/bu_Rcode.R
Untracked: scripts/salmon-latest_linux_x86_64/
Unstaged changes:
Modified: analysis/05-annotation.Rmd
Modified: analysis/Lam-02-NSC_annotation.Rmd
Modified: analysis/TDP-04-clustering.Rmd
Modified: analysis/TDP-06-cluster_analysis.Rmd
Modified: analysis/_site.yml
Modified: analysis/organoid-02-integration.Rmd
Modified: analysis/organoid-04-group_integration.Rmd
Modified: analysis/organoid-06-conos-analysis.Rmd
Modified: analysis/timepoints-01-organoid-integration.Rmd
Note that any generated files, e.g. HTML, png, CSS, etc., are not included in this status report because it is ok for generated content to have uncommitted changes.
These are the previous versions of the repository in which changes were made to the R Markdown (analysis/TDP-07-01-STMN2_expression.Rmd) and HTML (docs/TDP-07-01-STMN2_expression.html) files. If you've configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.
| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 1755a27 | khembach | 2021-02-18 | plot stathmin2 read coverage of cells from cluster 12 |
Load packages
library(Seurat)
library(SingleCellExperiment)
library(dplyr)
library(Gviz)
library(TxDb.Hsapiens.UCSC.hg38.knownGene)
library(Rsamtools)
library(GenomicAlignments)Load data & convert to SCE
# so <- readRDS(file.path("output", "so_TDP-06-cluster-analysis.rds"))
so <- readRDS(file.path("output", "so_TDP_05_plasmid_expression.rds"))
so <- SetIdent(so, value = "RNA_snn_res.0.4")
so@meta.data$cluster_id <- Idents(so)Cells from cluster 12
We want to compare the stathmin2 read coverage of cells expressing TDP-HA (from cluster 12) and other neuronal cells without TDP-HA expression. For this, we randomly select 5 cells from each group and filter the corresponding stathmin2 reads from the BAM file.
clus12 <- subset(so, subset = cluster_id == "12")
## from which sample do the cells come from?
clus12$sample_id %>% table.
TDP2wON TDP4wOFF TDP4wONa TDP4wONb
97 3 88 36 ## what is the range of TDP-HA expression in all cells in cluster 12?
dat_ha <- GetAssayData(object = clus12, slot = "data")["TDP43-HA",]
summary(dat_ha) Min. 1st Qu. Median Mean 3rd Qu. Max.
0.000 1.226 1.771 1.800 2.454 4.112 ## select cells with high TDP-HA expression
high <- clus12$barcode[which(dat_ha > 3.5)]
high ACCATTTAGGCTCCCA-1.TDP2wON ATAGACCAGCATTTCG-1.TDP2wON
"ACCATTTAGGCTCCCA-1" "ATAGACCAGCATTTCG-1"
CTTCTCTAGCCTATCA-1.TDP2wON GCTGGGTTCCCGAGAC-1.TDP4wONa
"CTTCTCTAGCCTATCA-1" "GCTGGGTTCCCGAGAC-1"
TCACATTAGTCCGTCG-1.TDP4wONa
"TCACATTAGTCCGTCG-1" ## cells with low TDP-HA expression
low <- clus12$barcode[which(dat_ha < 0.5 & dat_ha > 0)]
low ACTATGGAGCCATCCG-1.TDP2wON AGCCACGGTGTACATC-1.TDP2wON
"ACTATGGAGCCATCCG-1" "AGCCACGGTGTACATC-1"
CAACGATTCCCGTGAG-1.TDP2wON AACCCAACATTCTTCA-1.TDP4wOFF
"CAACGATTCCCGTGAG-1" "AACCCAACATTCTTCA-1"
CTAGACAAGATCACCT-1.TDP4wONa GCATCTCGTAGTATAG-1.TDP4wONa
"CTAGACAAGATCACCT-1" "GCATCTCGTAGTATAG-1"
GGAGAACGTAAGATTG-1.TDP4wONa
"GGAGAACGTAAGATTG-1" Get stathmin2 reads of selected cells
We extract the reads covering the stathmin2 genes of the selected cells.
bams <- list(TDP4wOFF = file.path("data", "Sep2020", "CellRangerCount_50076_2020-09-22--15-40-54",
"no1_Neural_cuture_d_96_TDP-43-HA_4w_DOXoff",
"possorted_genome_bam.bam"),
TDP2wON = file.path("data", "Sep2020", "CellRangerCount_50076_2020-09-22--15-40-54",
"no2_Neural_cuture_d_96_TDP-43-HA_2w_DOXON",
"possorted_genome_bam.bam"),
TDP4wONa = file.path("data", "Sep2020", "CellRangerCount_50076_2020-09-22--15-40-54",
"no3_Neural_cuture_d_96_TDP-43-HA_4w_DOXONa",
"possorted_genome_bam.bam"),
TDP4wONb = file.path("data", "Sep2020", "CellRangerCount_50076_2020-09-22--15-40-54",
"no4_Neural_cuture_d_96_TDP-43-HA_4w_DOXONb",
"possorted_genome_bam.bam"))
chr <- "chr8"
region_start <- 79611100
region_end <- 79666200
stmn2 <- GRanges(chr, IRanges(region_start, region_end), "+")
# keep all reads from cells in cluster 12
param <- ScanBamParam(which=stmn2, what = c("qname"), tag = "CB",
tagFilter = list(CB = clus12$barcode))
gals <- lapply(bams, function(x) {
readGAlignments(x, use.names = TRUE, param=param)
})
covs <- lapply(gals, coverage)Ploting with Gviz
Plot the stathmin2 transcripts and the read coverage of all cells from cluster 12.
## gene annotations from UCSC
options(ucscChromosomeNames = FALSE)
eTrack <- GeneRegionTrack(TxDb.Hsapiens.UCSC.hg38.knownGene,
chromosome = chr, start = region_start,
end = region_end, name = "annotation")
# covs[[1]]$chr8[region_start:region_end]
coords <- 79611100:79666201
dat <- matrix(c(as.vector(covs[[1]]$chr8[region_start:region_end]),
as.vector(covs[[2]]$chr8[region_start:region_end]),
as.vector(covs[[3]]$chr8[region_start:region_end]),
as.vector(covs[[4]]$chr8[region_start:region_end])),
nrow = 4, byrow = TRUE)
rownames(dat) <- names(covs)
dtrack <- DataTrack(data = dat,
start = coords[-length(coords)], end = coords[-1], chromosome = chr,
genome = "hg38")
plotTracks(c(dtrack, eTrack),
# collapseTranscripts="meta",
type = "histogram", showSampleNames = TRUE,
# chromosome = chr, from = region_start, to = region_end,
shape = "arrow", geneSymbols = TRUE, aggregateGroups=FALSE,
groups = c("TDP4wOFF", "TDP2wON", "TDP4wONa", "TDP4wONb"),
stackedBars = FALSE, cex.legend = 4
)
## one data track per sample
dats <- list("4wOFF" = matrix(as.vector(covs[[1]]$chr8[region_start:region_end]),
nrow = 1, byrow = TRUE),
"2wON" = matrix(as.vector(covs[[2]]$chr8[region_start:region_end]),
nrow = 1, byrow = TRUE),
"4wONa" = matrix(as.vector(covs[[3]]$chr8[region_start:region_end]),
nrow = 1, byrow = TRUE),
"4wONb" = matrix(as.vector(covs[[4]]$chr8[region_start:region_end]),
nrow = 1, byrow = TRUE))
# dats <- lapply(seq_along(dats), function(x) {rownames(dats[[x]]) <- names(dats)[x]; dats[[x]]})
# rownames(dat) <- names(covs)
dtrack_4wOFF <- DataTrack(data = dats[[1]],
start = coords[-length(coords)], end = coords[-1], chromosome = chr,
genome = "hg38", name = "4wOFF")
dtrack_2wON <- DataTrack(data = dats[[2]],
start = coords[-length(coords)], end = coords[-1], chromosome = chr,
genome = "hg38", name = "2wON")
dtrack_4wONa <- DataTrack(data = dats[[3]],
start = coords[-length(coords)], end = coords[-1], chromosome = chr,
genome = "hg38", name = "4wONa")
dtrack_4wONb <- DataTrack(data = dats[[4]],
start = coords[-length(coords)], end = coords[-1], chromosome = chr,
genome = "hg38", name = "4wONb")
plotTracks(c(dtrack_4wOFF, dtrack_2wON, dtrack_4wONa, dtrack_4wONb, eTrack),
# collapseTranscripts="meta",
type = "histogram", showSampleNames = TRUE,
# chromosome = chr, from = region_start, to = region_end,
shape = "arrow", geneSymbols = TRUE, aggregateGroups=FALSE,
# groups = c("TDP4wOFF", "TDP2wON", "TDP4wONa", "TDP4wONb"),
stackedBars = FALSE, cex.legend = 4
)
## zoom into intron 1 that contains the cryptic exon
chr <- "chr8"
region_start <- 79611100
region_end <- 79637000
plotTracks(c(dtrack_4wOFF, dtrack_2wON, dtrack_4wONa, dtrack_4wONb, eTrack),
# collapseTranscripts="meta",
type = "histogram", showSampleNames = TRUE,
chromosome = chr, from = region_start, to = region_end,
shape = "arrow", geneSymbols = TRUE, aggregateGroups=FALSE,
# groups = c("TDP4wOFF", "TDP2wON", "TDP4wONa", "TDP4wONb"),
stackedBars = FALSE, cex.legend = 4
)
sessionInfo()R version 4.0.0 (2020-04-24)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Ubuntu 16.04.6 LTS
Matrix products: default
BLAS: /usr/local/R/R-4.0.0/lib/libRblas.so
LAPACK: /usr/local/R/R-4.0.0/lib/libRlapack.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[5] LC_MONETARY=en_US.UTF-8 LC_MESSAGES=en_US.UTF-8
[7] LC_PAPER=en_US.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C
attached base packages:
[1] grid parallel stats4 stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] GenomicAlignments_1.24.0
[2] Rsamtools_2.4.0
[3] Biostrings_2.56.0
[4] XVector_0.28.0
[5] TxDb.Hsapiens.UCSC.hg38.knownGene_3.10.0
[6] GenomicFeatures_1.40.0
[7] AnnotationDbi_1.50.1
[8] Gviz_1.32.0
[9] dplyr_1.0.2
[10] SingleCellExperiment_1.10.1
[11] SummarizedExperiment_1.18.1
[12] DelayedArray_0.14.0
[13] matrixStats_0.56.0
[14] Biobase_2.48.0
[15] GenomicRanges_1.40.0
[16] GenomeInfoDb_1.24.2
[17] IRanges_2.22.2
[18] S4Vectors_0.26.1
[19] BiocGenerics_0.34.0
[20] Seurat_3.1.5
[21] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] backports_1.1.9 Hmisc_4.4-1 BiocFileCache_1.12.0
[4] plyr_1.8.6 igraph_1.2.5 lazyeval_0.2.2
[7] splines_4.0.0 BiocParallel_1.22.0 listenv_0.8.0
[10] ggplot2_3.3.2 digest_0.6.25 ensembldb_2.12.1
[13] htmltools_0.5.0 checkmate_2.0.0 magrittr_1.5
[16] memoise_1.1.0 BSgenome_1.56.0 cluster_2.1.0
[19] ROCR_1.0-11 globals_0.12.5 askpass_1.1
[22] prettyunits_1.1.1 jpeg_0.1-8.1 colorspace_1.4-1
[25] blob_1.2.1 rappdirs_0.3.1 ggrepel_0.8.2
[28] xfun_0.15 crayon_1.3.4 RCurl_1.98-1.2
[31] jsonlite_1.7.0 VariantAnnotation_1.34.0 survival_3.2-3
[34] zoo_1.8-8 ape_5.4 glue_1.4.2
[37] gtable_0.3.0 zlibbioc_1.34.0 leiden_0.3.3
[40] future.apply_1.6.0 scales_1.1.1 DBI_1.1.0
[43] Rcpp_1.0.5 htmlTable_2.0.1 viridisLite_0.3.0
[46] progress_1.2.2 reticulate_1.16 foreign_0.8-80
[49] bit_1.1-15.2 rsvd_1.0.3 Formula_1.2-3
[52] tsne_0.1-3 htmlwidgets_1.5.1 httr_1.4.1
[55] RColorBrewer_1.1-2 ellipsis_0.3.1 ica_1.0-2
[58] pkgconfig_2.0.3 XML_3.99-0.4 nnet_7.3-14
[61] uwot_0.1.8 dbplyr_1.4.4 tidyselect_1.1.0
[64] rlang_0.4.7 reshape2_1.4.4 later_1.1.0.1
[67] munsell_0.5.0 tools_4.0.0 generics_0.0.2
[70] RSQLite_2.2.0 ggridges_0.5.2 evaluate_0.14
[73] stringr_1.4.0 yaml_2.2.1 knitr_1.29
[76] bit64_0.9-7 fs_1.4.2 fitdistrplus_1.1-1
[79] purrr_0.3.4 RANN_2.6.1 AnnotationFilter_1.12.0
[82] pbapply_1.4-2 future_1.17.0 nlme_3.1-148
[85] whisker_0.4 biomaRt_2.44.1 rstudioapi_0.11
[88] compiler_4.0.0 plotly_4.9.2.1 curl_4.3
[91] png_0.1-7 tibble_3.0.3 stringi_1.4.6
[94] lattice_0.20-41 ProtGenerics_1.20.0 Matrix_1.2-18
[97] vctrs_0.3.4 pillar_1.4.6 lifecycle_0.2.0
[100] lmtest_0.9-37 RcppAnnoy_0.0.16 data.table_1.12.8
[103] cowplot_1.0.0 bitops_1.0-6 irlba_2.3.3
[106] httpuv_1.5.4 patchwork_1.0.1 rtracklayer_1.48.0
[109] R6_2.4.1 latticeExtra_0.6-29 promises_1.1.1
[112] KernSmooth_2.23-17 gridExtra_2.3 codetools_0.2-16
[115] dichromat_2.0-0 MASS_7.3-51.6 assertthat_0.2.1
[118] openssl_1.4.2 rprojroot_1.3-2 sctransform_0.2.1
[121] GenomeInfoDbData_1.2.3 hms_0.5.3 rpart_4.1-15
[124] tidyr_1.1.0 rmarkdown_2.3 Rtsne_0.15
[127] biovizBase_1.36.0 git2r_0.27.1 base64enc_0.1-3