WeberDivechaLCdata 1.2.0
This package contains data from our paper on the gene expression landscape of the human locus coeruleus (LC).
The dataset consists of spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from the LC in postmortem human brain samples. Data were generated with the 10x Genomics Visium SRT and 10x Genomics Chromium snRNA-seq platforms.
The data are provided as SpatialExperiment and SingleCellExperiment R/Bioconductor objects in this package, and in online web apps (Shiny and iSEE) for interactive exploration (see links in paper).
A preprint of the paper is available from bioRxiv.
The package can be installed from Bioconductor (WeberDivechaLCdata) as follows:
install.packages("BiocManager")
BiocManager::install("WeberDivechaLCdata")The package contains the following objects:
WeberDivechaLCdata_Visium: SRT (Visium) datasetWeberDivechaLCdata_singleNucleus: snRNA-seq datasetThe data objects can be loaded using the dataset names as follows:
library(SpatialExperiment)
library(SingleCellExperiment)
library(WeberDivechaLCdata)## Warning: replacing previous import 'utils::findMatches' by
## 'S4Vectors::findMatches' when loading 'AnnotationDbi'# Load objects using dataset names
spe <- WeberDivechaLCdata_Visium()
sce <- WeberDivechaLCdata_singleNucleus()Alternatively, the data objects can be loaded by accessing the ExperimentHub IDs:
library(ExperimentHub)# create ExperimentHub instance
eh <- ExperimentHub()
# query datasets
my_files <- query(eh, "WeberDivechaLCdata")
my_files## ExperimentHub with 2 records
## # snapshotDate(): 2023-04-24
## # $dataprovider: NA
## # $species: Homo sapiens
## # $rdataclass: SpatialExperiment, SingleCellExperiment
## # additional mcols(): taxonomyid, genome, description,
## # coordinate_1_based, maintainer, rdatadateadded, preparerclass, tags,
## # rdatapath, sourceurl, sourcetype
## # retrieve records with, e.g., 'object[["EH7737"]]'
##
## title
## EH7737 | WeberDivechaLCdata_Visium
## EH7738 | WeberDivechaLCdata_singleNucleus# metadata
md <- as.data.frame(mcols(my_files))# load data using ExperimentHub query
spe <- my_files[[1]]
sce <- my_files[[2]]# load data using ExperimentHub IDs
# spe <- myfiles[["EHXXXX"]]
# sce <- myfiles[["EHYYYY"]]Check that the data have been loaded:
# Visium data (SpatialExperiment format)
spe## class: SpatialExperiment
## dim: 23728 20380
## metadata(0):
## assays(2): counts logcounts
## rownames(23728): ENSG00000238009 ENSG00000241860 ... ENSG00000278817
## ENSG00000277196
## rowData names(6): source type ... gene_name gene_type
## colnames(20380): Br6522_LC_1_round1_AAACAAGTATCTCCCA-1
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 ...
## Br8153_LC_round3_TTGTTTGTATTACACG-1
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1
## colData names(20): sample_id donor_id ... discard sizeFactor
## reducedDimNames(0):
## mainExpName: NULL
## altExpNames(0):
## spatialCoords names(2) : pxl_col_in_fullres pxl_row_in_fullres
## imgData names(4): sample_id image_id data scaleFactor# dimensions
dim(spe)## [1] 23728 20380# assays
assayNames(spe)## [1] "counts" "logcounts"# row data
rowData(spe)## DataFrame with 23728 rows and 6 columns
## source type gene_id gene_version gene_name
## <factor> <factor> <character> <character> <character>
## ENSG00000238009 HAVANA gene ENSG00000238009 6 AL627309.1
## ENSG00000241860 HAVANA gene ENSG00000241860 7 AL627309.5
## ENSG00000241599 HAVANA gene ENSG00000241599 1 AL627309.4
## ENSG00000237491 HAVANA gene ENSG00000237491 10 LINC01409
## ENSG00000177757 HAVANA gene ENSG00000177757 2 FAM87B
## ... ... ... ... ... ...
## ENSG00000273748 ENSEMBL gene ENSG00000273748 1 AL592183.1
## ENSG00000271254 ENSEMBL gene ENSG00000271254 6 AC240274.1
## ENSG00000276345 ENSEMBL gene ENSG00000276345 1 AC004556.3
## ENSG00000278817 ENSEMBL gene ENSG00000278817 1 AC007325.4
## ENSG00000277196 ENSEMBL gene ENSG00000277196 4 AC007325.2
## gene_type
## <character>
## ENSG00000238009 lncRNA
## ENSG00000241860 lncRNA
## ENSG00000241599 lncRNA
## ENSG00000237491 lncRNA
## ENSG00000177757 lncRNA
## ... ...
## ENSG00000273748 protein_coding
## ENSG00000271254 protein_coding
## ENSG00000276345 protein_coding
## ENSG00000278817 protein_coding
## ENSG00000277196 protein_coding# column data
colData(spe)## DataFrame with 20380 rows and 20 columns
## sample_id donor_id round_id
## <factor> <factor> <factor>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 Br6522_LC_1_round1 Br6522 round1
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 Br6522_LC_1_round1 Br6522 round1
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 Br6522_LC_1_round1 Br6522 round1
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 Br6522_LC_1_round1 Br6522 round1
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 Br6522_LC_1_round1 Br6522 round1
## ... ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 Br8153_LC_round3 Br8153 round3
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 Br8153_LC_round3 Br8153 round3
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 Br8153_LC_round3 Br8153 round3
## Br8153_LC_round3_TTGTTTGTATTACACG-1 Br8153_LC_round3 Br8153 round3
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 Br8153_LC_round3 Br8153 round3
## key_id part_id
## <character> <character>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 Br6522_LC_1_round1_A.. single
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 Br6522_LC_1_round1_A.. single
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 Br6522_LC_1_round1_A.. single
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 Br6522_LC_1_round1_A.. single
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 Br6522_LC_1_round1_A.. single
## ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 Br8153_LC_round3_TTG.. right
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 Br8153_LC_round3_TTG.. right
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 Br8153_LC_round3_TTG.. right
## Br8153_LC_round3_TTGTTTGTATTACACG-1 Br8153_LC_round3_TTG.. right
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 Br8153_LC_round3_TTG.. left
## sample_part_id in_tissue
## <character> <logical>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 Br6522_LC_1_round1_s.. TRUE
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 Br6522_LC_1_round1_s.. TRUE
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 Br6522_LC_1_round1_s.. TRUE
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 Br6522_LC_1_round1_s.. TRUE
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 Br6522_LC_1_round1_s.. TRUE
## ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 Br8153_LC_round3_right TRUE
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 Br8153_LC_round3_right TRUE
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 Br8153_LC_round3_right TRUE
## Br8153_LC_round3_TTGTTTGTATTACACG-1 Br8153_LC_round3_right TRUE
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 Br8153_LC_round3_left TRUE
## array_row array_col annot_region
## <integer> <integer> <logical>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 50 102 FALSE
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 59 19 FALSE
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 14 94 FALSE
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 43 9 FALSE
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 61 97 FALSE
## ... ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 76 30 FALSE
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 58 42 FALSE
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 60 30 FALSE
## Br8153_LC_round3_TTGTTTGTATTACACG-1 73 41 FALSE
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 7 51 FALSE
## annot_spot sum detected
## <logical> <numeric> <integer>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 FALSE 227 162
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 FALSE 3268 1585
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 FALSE 112 86
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 FALSE 8796 3524
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 FALSE 465 319
## ... ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 FALSE 202 141
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 FALSE 610 436
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 FALSE 405 300
## Br8153_LC_round3_TTGTTTGTATTACACG-1 FALSE 36 30
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 FALSE 343 244
## subsets_mito_sum subsets_mito_detected
## <numeric> <integer>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 40 8
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 666 13
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 25 10
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 751 12
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 84 13
## ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 49 9
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 107 11
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 86 10
## Br8153_LC_round3_TTGTTTGTATTACACG-1 11 5
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 62 10
## subsets_mito_percent low_lib_size
## <numeric> <logical>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 17.62115 FALSE
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 20.37944 FALSE
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 22.32143 FALSE
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 8.53797 FALSE
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 18.06452 FALSE
## ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 24.2574 FALSE
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 17.5410 FALSE
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 21.2346 FALSE
## Br8153_LC_round3_TTGTTTGTATTACACG-1 30.5556 FALSE
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 18.0758 FALSE
## low_n_features discard sizeFactor
## <logical> <logical> <numeric>
## Br6522_LC_1_round1_AAACAAGTATCTCCCA-1 FALSE FALSE 0.222823
## Br6522_LC_1_round1_AAACACCAATAACTGC-1 FALSE FALSE 3.207867
## Br6522_LC_1_round1_AAACAGAGCGACTCCT-1 FALSE FALSE 0.109939
## Br6522_LC_1_round1_AAACAGCTTTCAGAAG-1 FALSE FALSE 8.634150
## Br6522_LC_1_round1_AAACATTTCCCGGATT-1 FALSE FALSE 0.456444
## ... ... ... ...
## Br8153_LC_round3_TTGTTGGCAATGACTG-1 FALSE FALSE 0.1982831
## Br8153_LC_round3_TTGTTTCACATCCAGG-1 FALSE FALSE 0.5987757
## Br8153_LC_round3_TTGTTTCATTAGTCTA-1 FALSE FALSE 0.3975478
## Br8153_LC_round3_TTGTTTGTATTACACG-1 FALSE FALSE 0.0353376
## Br8153_LC_round3_TTGTTTGTGTAAATTC-1 FALSE FALSE 0.3366886# spatial coordinates
head(spatialCoords(spe))## pxl_col_in_fullres pxl_row_in_fullres
## AAACAAGTATCTCCCA-1 21121 7033
## AAACACCAATAACTGC-1 24501 23844
## AAACAGAGCGACTCCT-1 8424 8808
## AAACAGCTTTCAGAAG-1 18873 25942
## AAACATTTCCCGGATT-1 25019 8002
## AAACCGGGTAGGTACC-1 18474 22089# image data
imgData(spe)## DataFrame with 16 rows and 4 columns
## sample_id image_id data scaleFactor
## <factor> <character> <list> <numeric>
## 1 Br6522_LC_1_round1 hires #### 0.0575473
## 2 Br6522_LC_1_round1 lowres #### 0.0172642
## 3 Br6522_LC_2_round1 hires #### 0.0575473
## 4 Br6522_LC_2_round1 lowres #### 0.0172642
## 5 Br8153_LC_round2 hires #### 0.0666422
## ... ... ... ... ...
## 12 Br8079_LC_round3 lowres #### 0.0184434
## 13 Br2701_LC_round3 hires #### 0.0614779
## 14 Br2701_LC_round3 lowres #### 0.0184434
## 15 Br8153_LC_round3 hires #### 0.0614779
## 16 Br8153_LC_round3 lowres #### 0.0184434# snRNA-seq data (SingleCellExperiment format)
sce## class: SingleCellExperiment
## dim: 33352 20191
## metadata(1): Samples
## assays(2): counts logcounts
## rownames(33352): ENSG00000186092 ENSG00000238009 ... ENSG00000278817
## ENSG00000277196
## rowData names(6): source type ... gene_name gene_type
## colnames(20191): Br6522_LC_AAACCCAAGCCATTTG-1
## Br6522_LC_AAACGAACATCGATAC-1 ... Br2701_LC_TTTGTTGTCGCTTGCT-1
## Br2701_LC_TTTGTTGTCTGACAGT-1
## colData names(16): Sample Barcode ... unsupervised_5HT supervised_NE
## reducedDimNames(2): PCA UMAP
## mainExpName: NULL
## altExpNames(0):# dimensions
dim(sce)## [1] 33352 20191# assays
assayNames(sce)## [1] "counts" "logcounts"# row data
rowData(sce)## DataFrame with 33352 rows and 6 columns
## source type gene_id gene_version gene_name
## <factor> <factor> <character> <character> <character>
## ENSG00000186092 HAVANA gene ENSG00000186092 6 OR4F5
## ENSG00000238009 HAVANA gene ENSG00000238009 6 AL627309.1
## ENSG00000239945 HAVANA gene ENSG00000239945 1 AL627309.3
## ENSG00000239906 HAVANA gene ENSG00000239906 1 AL627309.2
## ENSG00000241860 HAVANA gene ENSG00000241860 7 AL627309.5
## ... ... ... ... ... ...
## ENSG00000273554 ENSEMBL gene ENSG00000273554 4 AC136616.1
## ENSG00000278633 ENSEMBL gene ENSG00000278633 1 AC023491.2
## ENSG00000276017 ENSEMBL gene ENSG00000276017 1 AC007325.1
## ENSG00000278817 ENSEMBL gene ENSG00000278817 1 AC007325.4
## ENSG00000277196 ENSEMBL gene ENSG00000277196 4 AC007325.2
## gene_type
## <character>
## ENSG00000186092 protein_coding
## ENSG00000238009 lncRNA
## ENSG00000239945 lncRNA
## ENSG00000239906 lncRNA
## ENSG00000241860 lncRNA
## ... ...
## ENSG00000273554 protein_coding
## ENSG00000278633 protein_coding
## ENSG00000276017 protein_coding
## ENSG00000278817 protein_coding
## ENSG00000277196 protein_coding# column data
colData(sce)## DataFrame with 20191 rows and 16 columns
## Sample Barcode sum detected
## <character> <character> <numeric> <integer>
## Br6522_LC_AAACCCAAGCCATTTG-1 Br6522_LC AAACCCAAGCCATTTG-1 1366 999
## Br6522_LC_AAACGAACATCGATAC-1 Br6522_LC AAACGAACATCGATAC-1 29255 6869
## Br6522_LC_AAACGCTCACACGGTC-1 Br6522_LC AAACGCTCACACGGTC-1 69772 10443
## Br6522_LC_AAACGCTCACCTATCC-1 Br6522_LC AAACGCTCACCTATCC-1 598 531
## Br6522_LC_AAACGCTGTAGATTAG-1 Br6522_LC AAACGCTGTAGATTAG-1 40503 9088
## ... ... ... ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 Br2701_LC TTTGTTGGTGTTTACG-1 982 759
## Br2701_LC_TTTGTTGTCACATACG-1 Br2701_LC TTTGTTGTCACATACG-1 41730 8093
## Br2701_LC_TTTGTTGTCCGAGCTG-1 Br2701_LC TTTGTTGTCCGAGCTG-1 2452 1546
## Br2701_LC_TTTGTTGTCGCTTGCT-1 Br2701_LC TTTGTTGTCGCTTGCT-1 9090 3575
## Br2701_LC_TTTGTTGTCTGACAGT-1 Br2701_LC TTTGTTGTCTGACAGT-1 4601 2367
## subsets_Mito_sum subsets_Mito_detected
## <numeric> <integer>
## Br6522_LC_AAACCCAAGCCATTTG-1 79 12
## Br6522_LC_AAACGAACATCGATAC-1 114 11
## Br6522_LC_AAACGCTCACACGGTC-1 764 13
## Br6522_LC_AAACGCTCACCTATCC-1 13 6
## Br6522_LC_AAACGCTGTAGATTAG-1 349 12
## ... ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 51 11
## Br2701_LC_TTTGTTGTCACATACG-1 1657 13
## Br2701_LC_TTTGTTGTCCGAGCTG-1 52 11
## Br2701_LC_TTTGTTGTCGCTTGCT-1 286 11
## Br2701_LC_TTTGTTGTCTGACAGT-1 20 9
## subsets_Mito_percent discard sizeFactor
## <numeric> <logical> <numeric>
## Br6522_LC_AAACCCAAGCCATTTG-1 5.783309 FALSE 0.1440373
## Br6522_LC_AAACGAACATCGATAC-1 0.389677 FALSE 3.0698366
## Br6522_LC_AAACGCTCACACGGTC-1 1.094995 FALSE 8.3284110
## Br6522_LC_AAACGCTCACCTATCC-1 2.173913 FALSE 0.0703227
## Br6522_LC_AAACGCTGTAGATTAG-1 0.861665 FALSE 5.0136522
## ... ... ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 5.193483 FALSE 0.124831
## Br2701_LC_TTTGTTGTCACATACG-1 3.970764 FALSE 4.537642
## Br2701_LC_TTTGTTGTCCGAGCTG-1 2.120718 FALSE 0.256114
## Br2701_LC_TTTGTTGTCGCTTGCT-1 3.146315 FALSE 0.918521
## Br2701_LC_TTTGTTGTCTGACAGT-1 0.434688 FALSE 0.444832
## Key label label_merged
## <character> <factor> <factor>
## Br6522_LC_AAACCCAAGCCATTTG-1 Br6522_LC_AAACCCAAGC.. 12 oligodendrocytes
## Br6522_LC_AAACGAACATCGATAC-1 Br6522_LC_AAACGAACAT.. 24 inhibitory
## Br6522_LC_AAACGCTCACACGGTC-1 Br6522_LC_AAACGCTCAC.. 25 inhibitory
## Br6522_LC_AAACGCTCACCTATCC-1 Br6522_LC_AAACGCTCAC.. 17 inhibitory
## Br6522_LC_AAACGCTGTAGATTAG-1 Br6522_LC_AAACGCTGTA.. 25 inhibitory
## ... ... ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 Br2701_LC_TTTGTTGGTG.. 9 oligodendrocytes
## Br2701_LC_TTTGTTGTCACATACG-1 Br2701_LC_TTTGTTGTCA.. 1 neurons_ambiguous
## Br2701_LC_TTTGTTGTCCGAGCTG-1 Br2701_LC_TTTGTTGTCC.. 1 neurons_ambiguous
## Br2701_LC_TTTGTTGTCGCTTGCT-1 Br2701_LC_TTTGTTGTCG.. 2 neurons_ambiguous
## Br2701_LC_TTTGTTGTCTGACAGT-1 Br2701_LC_TTTGTTGTCT.. 1 neurons_ambiguous
## label_inhibitory unsupervised_NE unsupervised_5HT
## <integer> <logical> <logical>
## Br6522_LC_AAACCCAAGCCATTTG-1 NA FALSE FALSE
## Br6522_LC_AAACGAACATCGATAC-1 5 FALSE FALSE
## Br6522_LC_AAACGCTCACACGGTC-1 2 FALSE FALSE
## Br6522_LC_AAACGCTCACCTATCC-1 3 FALSE FALSE
## Br6522_LC_AAACGCTGTAGATTAG-1 2 FALSE FALSE
## ... ... ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 NA FALSE FALSE
## Br2701_LC_TTTGTTGTCACATACG-1 NA FALSE FALSE
## Br2701_LC_TTTGTTGTCCGAGCTG-1 NA FALSE FALSE
## Br2701_LC_TTTGTTGTCGCTTGCT-1 NA FALSE FALSE
## Br2701_LC_TTTGTTGTCTGACAGT-1 NA FALSE FALSE
## supervised_NE
## <logical>
## Br6522_LC_AAACCCAAGCCATTTG-1 FALSE
## Br6522_LC_AAACGAACATCGATAC-1 FALSE
## Br6522_LC_AAACGCTCACACGGTC-1 FALSE
## Br6522_LC_AAACGCTCACCTATCC-1 FALSE
## Br6522_LC_AAACGCTGTAGATTAG-1 FALSE
## ... ...
## Br2701_LC_TTTGTTGGTGTTTACG-1 FALSE
## Br2701_LC_TTTGTTGTCACATACG-1 FALSE
## Br2701_LC_TTTGTTGTCCGAGCTG-1 FALSE
## Br2701_LC_TTTGTTGTCGCTTGCT-1 FALSE
## Br2701_LC_TTTGTTGTCTGACAGT-1 FALSEsessionInfo()## R version 4.3.0 RC (2023-04-13 r84269)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 22.04.2 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.17-bioc/R/lib/libRblas.so
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.10.0
##
## locale:
## [1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
## [3] LC_TIME=en_GB LC_COLLATE=C
## [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
##
## time zone: America/New_York
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 stats graphics grDevices utils datasets methods
## [8] base
##
## other attached packages:
## [1] WeberDivechaLCdata_1.2.0 ExperimentHub_2.8.0
## [3] AnnotationHub_3.8.0 BiocFileCache_2.8.0
## [5] dbplyr_2.3.2 SpatialExperiment_1.10.0
## [7] SingleCellExperiment_1.22.0 SummarizedExperiment_1.30.0
## [9] Biobase_2.60.0 GenomicRanges_1.52.0
## [11] GenomeInfoDb_1.36.0 IRanges_2.34.0
## [13] S4Vectors_0.38.0 BiocGenerics_0.46.0
## [15] MatrixGenerics_1.12.0 matrixStats_0.63.0
## [17] BiocStyle_2.28.0
##
## loaded via a namespace (and not attached):
## [1] DBI_1.1.3 bitops_1.0-7
## [3] rlang_1.1.0 magrittr_2.0.3
## [5] compiler_4.3.0 RSQLite_2.3.1
## [7] DelayedMatrixStats_1.22.0 png_0.1-8
## [9] vctrs_0.6.2 pkgconfig_2.0.3
## [11] crayon_1.5.2 fastmap_1.1.1
## [13] magick_2.7.4 XVector_0.40.0
## [15] ellipsis_0.3.2 scuttle_1.10.0
## [17] utf8_1.2.3 promises_1.2.0.1
## [19] rmarkdown_2.21 purrr_1.0.1
## [21] bit_4.0.5 xfun_0.39
## [23] zlibbioc_1.46.0 cachem_1.0.7
## [25] beachmat_2.16.0 jsonlite_1.8.4
## [27] blob_1.2.4 later_1.3.0
## [29] rhdf5filters_1.12.0 DelayedArray_0.26.0
## [31] Rhdf5lib_1.22.0 BiocParallel_1.34.0
## [33] interactiveDisplayBase_1.38.0 parallel_4.3.0
## [35] R6_2.5.1 bslib_0.4.2
## [37] limma_3.56.0 jquerylib_0.1.4
## [39] Rcpp_1.0.10 bookdown_0.33
## [41] knitr_1.42 R.utils_2.12.2
## [43] httpuv_1.6.9 Matrix_1.5-4
## [45] tidyselect_1.2.0 yaml_2.3.7
## [47] codetools_0.2-19 curl_5.0.0
## [49] lattice_0.21-8 tibble_3.2.1
## [51] shiny_1.7.4 withr_2.5.0
## [53] KEGGREST_1.40.0 evaluate_0.20
## [55] Biostrings_2.68.0 pillar_1.9.0
## [57] BiocManager_1.30.20 filelock_1.0.2
## [59] generics_0.1.3 RCurl_1.98-1.12
## [61] BiocVersion_3.17.1 sparseMatrixStats_1.12.0
## [63] xtable_1.8-4 glue_1.6.2
## [65] tools_4.3.0 locfit_1.5-9.7
## [67] rhdf5_2.44.0 grid_4.3.0
## [69] DropletUtils_1.20.0 AnnotationDbi_1.62.0
## [71] edgeR_3.42.0 GenomeInfoDbData_1.2.10
## [73] HDF5Array_1.28.0 cli_3.6.1
## [75] rappdirs_0.3.3 fansi_1.0.4
## [77] dplyr_1.1.2 R.methodsS3_1.8.2
## [79] sass_0.4.5 digest_0.6.31
## [81] dqrng_0.3.0 rjson_0.2.21
## [83] memoise_2.0.1 htmltools_0.5.5
## [85] R.oo_1.25.0 lifecycle_1.0.3
## [87] httr_1.4.5 mime_0.12
## [89] bit64_4.0.5