BatchQC 2.1.1
This data set is from protein expression data captured for 39 proteins. It has two batches and two conditions corresponding to case and control.
library(BatchQC)
data(protein_data)
data(protein_sample_info)
se_object <- BatchQC::summarized_experiment(protein_data, protein_sample_info)This data set is from signature data captured when activating different growth pathway genes in human mammary epithelial cells (GEO accession: GSE73628). This data consists of three batches and ten different conditions corresponding to control and nine different pathways
data(signature_data)
data(batch_indicator)
se_object <- BatchQC::summarized_experiment(signature_data, batch_indicator)This data set is from bladder cancer data. This dataset has 57 bladder samples with 5 batches and 3 covariate levels (cancer, biopsy, control). Batch 1 contains only cancer, 2 has cancer and controls, 3 has only controls, 4 contains only biopsy, and 5 contains cancer and biopsy. This data set is from the bladderbatch package which must be installed to use this data example set (Leek JT (2023). bladderbatch: Bladder gene expression data illustrating batch effects. R package version 1.38.0).
se_object <- BatchQC::bladder_data_upload()## R version 4.4.0 RC (2024-04-16 r86468)
## Platform: x86_64-pc-linux-gnu
## Running under: Ubuntu 22.04.4 LTS
##
## Matrix products: default
## BLAS: /home/biocbuild/bbs-3.20-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] stats graphics grDevices utils datasets methods base
##
## other attached packages:
## [1] BatchQC_2.1.1 BiocStyle_2.33.0
##
## loaded via a namespace (and not attached):
## [1] RColorBrewer_1.1-3 ggdendro_0.2.0
## [3] jsonlite_1.8.8 magrittr_2.0.3
## [5] magick_2.8.3 NCmisc_1.2.0
## [7] farver_2.1.1 rmarkdown_2.26
## [9] zlibbioc_1.51.0 vctrs_0.6.5
## [11] memoise_2.0.1 DelayedMatrixStats_1.27.0
## [13] EBSeq_2.3.0 tinytex_0.51
## [15] htmltools_0.5.8.1 S4Arrays_1.5.0
## [17] BiocNeighbors_1.23.0 SparseArray_1.5.3
## [19] sass_0.4.9 KernSmooth_2.23-22
## [21] bslib_0.7.0 htmlwidgets_1.6.4
## [23] plyr_1.8.9 testthat_3.2.1.1
## [25] plotly_4.10.4 cachem_1.0.8
## [27] igraph_2.0.3 mime_0.12
## [29] lifecycle_1.0.4 pkgconfig_2.0.3
## [31] rsvd_1.0.5 Matrix_1.7-0
## [33] R6_2.5.1 fastmap_1.1.1
## [35] GenomeInfoDbData_1.2.12 MatrixGenerics_1.17.0
## [37] shiny_1.8.1.1 digest_0.6.35
## [39] colorspace_2.1-0 ggnewscale_0.4.10
## [41] AnnotationDbi_1.67.0 S4Vectors_0.43.0
## [43] DESeq2_1.45.0 dqrng_0.3.2
## [45] irlba_2.3.5.1 crosstalk_1.2.1
## [47] GenomicRanges_1.57.0 RSQLite_2.3.6
## [49] beachmat_2.21.0 labeling_0.4.3
## [51] fansi_1.0.6 httr_1.4.7
## [53] abind_1.4-5 mgcv_1.9-1
## [55] compiler_4.4.0 withr_3.0.0
## [57] bit64_4.0.5 BiocParallel_1.39.0
## [59] DBI_1.2.2 highr_0.10
## [61] gplots_3.1.3.1 MASS_7.3-60.2
## [63] DelayedArray_0.31.1 bluster_1.15.0
## [65] gtools_3.9.5 caTools_1.18.2
## [67] tools_4.4.0 httpuv_1.6.15
## [69] glue_1.7.0 nlme_3.1-164
## [71] promises_1.3.0 grid_4.4.0
## [73] cluster_2.1.6 reshape2_1.4.4
## [75] generics_0.1.3 sva_3.53.0
## [77] gtable_0.3.5 tidyr_1.3.1
## [79] data.table_1.15.4 BiocSingular_1.21.0
## [81] ScaledMatrix_1.13.0 metapod_1.13.0
## [83] utf8_1.2.4 XVector_0.45.0
## [85] BiocGenerics_0.51.0 pillar_1.9.0
## [87] stringr_1.5.1 limma_3.61.0
## [89] genefilter_1.87.0 later_1.3.2
## [91] splines_4.4.0 dplyr_1.1.4
## [93] lattice_0.22-6 survival_3.6-4
## [95] reader_1.0.6 bit_4.0.5
## [97] annotate_1.83.0 tidyselect_1.2.1
## [99] SingleCellExperiment_1.27.0 locfit_1.5-9.9
## [101] Biostrings_2.73.0 scuttle_1.15.0
## [103] knitr_1.46 bookdown_0.39
## [105] blockmodeling_1.1.5 IRanges_2.39.0
## [107] edgeR_4.3.1 SummarizedExperiment_1.35.0
## [109] stats4_4.4.0 xfun_0.43
## [111] Biobase_2.65.0 statmod_1.5.0
## [113] brio_1.1.5 matrixStats_1.3.0
## [115] pheatmap_1.0.12 stringi_1.8.4
## [117] UCSC.utils_1.1.0 lazyeval_0.2.2
## [119] yaml_2.3.8 evaluate_0.23
## [121] codetools_0.2-20 RcppEigen_0.3.4.0.0
## [123] tibble_3.2.1 BiocManager_1.30.23
## [125] cli_3.6.2 shinythemes_1.2.0
## [127] xtable_1.8-4 munsell_0.5.1
## [129] jquerylib_0.1.4 Rcpp_1.0.12
## [131] GenomeInfoDb_1.41.0 tidyverse_2.0.0
## [133] png_0.1-8 XML_3.99-0.16.1
## [135] parallel_4.4.0 ggplot2_3.5.1
## [137] blob_1.2.4 scran_1.33.0
## [139] sparseMatrixStats_1.17.0 bitops_1.0-7
## [141] viridisLite_0.4.2 scales_1.3.0
## [143] purrr_1.0.2 crayon_1.5.2
## [145] rlang_1.1.3 KEGGREST_1.45.0
## [147] shinyjs_2.1.0