Configuration Settings for the Workflow
species | tissue | metadata | genesets | genetype | min_umi_per_cell | max_mt_percent | min_genes_per_cell | min_cell | scr_th | seu_nrmlz_method | seu_scale_factor | seu_n_hvg | seu_n_dim | seu_k_param | seu_cluster_res | harmony | tsne | spr_n_dim | mrk_logfc | mrk_min_pct | mrk_only_pos | mrk_test | mrk_top_n | adt | trajectory | traj_var_gene | traj_top_n | pipe_version |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
hs | colon | cell_based | none | none | 750 | 10 | 250 | 3 | 0 | LogNormalize | 1e+06 | 2000 | 30 | 20 | 0.7 | none | FALSE | 30 | 0.25 | 0.5 | TRUE | wilcox | 0 | FALSE | none | 1000 | 50 | 1.0.0 |
sample | sample_id | sample_name | visit | disease | tissue | subject |
---|---|---|---|---|---|---|
GSE116222 | S1 | A1,A2,A3,B1,B2,B3,C1,C2,C3 | 1,2,3 | Healthy,UC_Non_Inflamed,UC_Inflamed | Distal_Colon | 3_Controls_Pool,3_UC_Pool |
sample_id | pre_qc_gene | pre_qc_cell | post_qc_gene | post_qc_cell |
---|---|---|---|---|
S1 | 28,003 | 11,175 | 22,607 | 11,157 |
Vales are post-QC.
sample_id | min | 0% | 25% | 50% | 75% | 100% | max |
---|---|---|---|---|---|---|---|
S1 | 756 | 756 | 1,837 | 2,134 | 2,490 | 3,805 | 3,805 |
Vales are post-QC.
sample_id | min | 0% | 25% | 50% | 75% | 100% | max |
---|---|---|---|---|---|---|---|
S1 | 358 | 358 | 1,065 | 1,472 | 2,216 | 5,753 | 5,753 |
Vales are post-QC.
sample_id | min | 0% | 25% | 50% | 75% | 100% | max |
---|---|---|---|---|---|---|---|
S1 | 0.03 | 0.03 | 1.95 | 2.44 | 3.05 | 8.68 | 8.68 |
Thresholds, represented by dashed lines, were implemented to filter the data and only retain cells of high quality.
Number of barcodes shared between pairs of samples post-QC.
S1 | |
---|---|
S1 | 11157 |
Fraction (%) of barcodes shared between pairs of samples post-QC.
S1 | |
---|---|
S1 | 1 |
diamonds and diamonds refer to before and after QC, respectively.
The error bars represent the standard deviation of the number of UMIs and genes across cells per sample.
min | 0% | 25% | 50% | 75% | 100% | max | |
---|---|---|---|---|---|---|---|
UMI per cell | 756 | 756 | 1,837 | 2,134 | 2,490 | 3,805 | 3,805 |
Gene per cell | 358 | 358 | 1,065 | 1,472 | 2,216 | 5,753 | 5,753 |
Mitochondrial (%) per cell | 0.03 | 0.03 | 1.95 | 2.44 | 3.05 | 8.68 | 8.68 |
Note: Labels may have been removed if they overlap excessively.
Note: QC metrics based on kernel density estimation.
Note: Labels may have been removed if they overlap excessively.
Values at the top of each bar indicate the percentage of cells
This measurement is a proxy to batch effect artifacts. Values adjacent to each point indicate the number of cells.
Note: Labels may have been removed if they overlap excessively.
Values at the top of each bar indicate the percentage of cells
Publication: no referrence
Data Availability: no referrence
This is the output of sessionInfo()
on the computing
system on which this document was compiled
## R version 4.3.2 (2023-10-31)
## Platform: x86_64-pc-linux-gnu (64-bit)
## Running under: Ubuntu 20.04.6 LTS
##
## Matrix products: default
## BLAS: /usr/lib/x86_64-linux-gnu/blas/libblas.so.3.9.0
## LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.9.0
##
## Random number generation:
## RNG: L'Ecuyer-CMRG
## Normal: Inversion
## Sample: Rejection
##
## locale:
## [1] C
##
## time zone: Etc/UTC
## tzcode source: system (glibc)
##
## attached base packages:
## [1] stats4 grid stats graphics grDevices
## [6] utils datasets methods base
##
## other attached packages:
## [1] edgeR_4.0.2 limma_3.58.1
## [3] slingshot_2.10.0 TrajectoryUtils_1.10.0
## [5] SingleCellExperiment_1.24.0 SummarizedExperiment_1.32.0
## [7] Biobase_2.62.0 GenomicRanges_1.54.1
## [9] GenomeInfoDb_1.38.1 IRanges_2.36.0
## [11] S4Vectors_0.40.2 BiocGenerics_0.48.1
## [13] MatrixGenerics_1.14.0 matrixStats_1.1.0
## [15] princurve_2.1.6 Nebulosa_1.12.0
## [17] patchwork_1.1.3 data.table_1.14.10
## [19] ComplexHeatmap_2.18.0 visNetwork_2.1.2
## [21] plotly_4.10.3 data.tree_1.1.0
## [23] DT_0.30 readxl_1.4.3
## [25] gtools_3.9.5 gplots_3.1.3
## [27] gridtext_0.1.5 igraph_1.5.1
## [29] sargent_1.0.1 SignacX_2.2.5
## [31] harmony_1.2.0 Rcpp_1.0.11
## [33] kableExtra_1.3.4 purrr_1.0.2
## [35] reticulate_1.34.0 RColorBrewer_1.1-3
## [37] cowplot_1.1.1 gridExtra_2.3
## [39] pheatmap_1.0.12 ggrepel_0.9.4
## [41] ggplot2_3.4.4 Seurat_5.0.1
## [43] SeuratObject_5.0.1 sp_2.1-2
## [45] dplyr_1.1.4 optparse_1.7.3
##
## loaded via a namespace (and not attached):
## [1] spatstat.sparse_3.0-3 bitops_1.0-7
## [3] httr_1.4.7 webshot_0.5.5
## [5] doParallel_1.0.17 tools_4.3.2
## [7] sctransform_0.4.1 utf8_1.2.4
## [9] R6_2.5.1 lazyeval_0.2.2
## [11] uwot_0.1.16 ggdist_3.3.1
## [13] GetoptLong_1.0.5 withr_2.5.2
## [15] progressr_0.14.0 cli_3.6.1
## [17] spatstat.explore_3.2-5 fastDummies_1.7.3
## [19] labeling_0.4.3 sass_0.4.8
## [21] mvtnorm_1.2-4 spatstat.data_3.0-3
## [23] proxy_0.4-27 ggridges_0.5.4
## [25] pbapply_1.7-2 commonmark_1.9.0
## [27] systemfonts_1.0.5 R.utils_2.12.3
## [29] svglite_2.1.2 parallelly_1.36.0
## [31] rstudioapi_0.15.0 generics_0.1.3
## [33] shape_1.4.6 crosstalk_1.2.1
## [35] ica_1.0-3 spatstat.random_3.2-2
## [37] distributional_0.3.2 Matrix_1.6-4
## [39] fansi_1.0.6 DescTools_0.99.52
## [41] abind_1.4-5 R.methodsS3_1.8.2
## [43] lifecycle_1.0.4 yaml_2.3.7
## [45] SparseArray_1.2.2 Rtsne_0.17
## [47] promises_1.2.1 crayon_1.5.2
## [49] miniUI_0.1.1.1 lattice_0.22-5
## [51] pillar_1.9.0 knitr_1.45
## [53] rjson_0.2.21 boot_1.3-28.1
## [55] gld_2.6.6 future.apply_1.11.0
## [57] codetools_0.2-19 leiden_0.4.3.1
## [59] glue_1.6.2 vctrs_0.6.5
## [61] png_0.1-8 spam_2.10-0
## [63] neuralnet_1.44.2 cellranger_1.1.0
## [65] gtable_0.3.4 cachem_1.0.8
## [67] ks_1.14.1 xfun_0.41
## [69] S4Arrays_1.2.0 mime_0.12
## [71] pracma_2.4.4 survival_3.5-7
## [73] pbmcapply_1.5.1 iterators_1.0.14
## [75] statmod_1.5.0 ellipsis_0.3.2
## [77] fitdistrplus_1.1-11 ROCR_1.0-11
## [79] nlme_3.1-164 RcppAnnoy_0.0.21
## [81] bslib_0.6.1 irlba_2.3.5.1
## [83] KernSmooth_2.23-22 colorspace_2.1-0
## [85] Exact_3.2 tidyselect_1.2.0
## [87] compiler_4.3.2 rvest_1.0.3
## [89] expm_0.999-8 xml2_1.3.6
## [91] DelayedArray_0.28.0 scales_1.3.0
## [93] caTools_1.18.2 lmtest_0.9-40
## [95] stringr_1.5.1 digest_0.6.33
## [97] goftest_1.2-3 spatstat.utils_3.0-4
## [99] rmarkdown_2.25 XVector_0.42.0
## [101] htmltools_0.5.7 pkgconfig_2.0.3
## [103] highr_0.10 fastmap_1.1.1
## [105] rlang_1.1.2 GlobalOptions_0.1.2
## [107] htmlwidgets_1.6.4 shiny_1.8.0
## [109] jquerylib_0.1.4 farver_2.1.1
## [111] zoo_1.8-12 jsonlite_1.8.8
## [113] mclust_6.0.1 R.oo_1.25.0
## [115] RCurl_1.98-1.13 magrittr_2.0.3
## [117] GenomeInfoDbData_1.2.11 dotCall64_1.1-1
## [119] munsell_0.5.0 stringi_1.8.2
## [121] rootSolve_1.8.2.4 zlibbioc_1.48.0
## [123] MASS_7.3-60 plyr_1.8.9
## [125] parallel_4.3.2 listenv_0.9.0
## [127] lmom_3.0 deldir_2.0-2
## [129] splines_4.3.2 tensor_1.5
## [131] circlize_0.4.15 locfit_1.5-9.8
## [133] spatstat.geom_3.2-7 markdown_1.12
## [135] RcppHNSW_0.5.0 reshape2_1.4.4
## [137] evaluate_0.23 foreach_1.5.2
## [139] httpuv_1.6.13 RANN_2.6.1
## [141] tidyr_1.3.0 getopt_1.20.4
## [143] polyclip_1.10-6 future_1.33.0
## [145] clue_0.3-65 scattermore_1.2
## [147] xtable_1.8-4 e1071_1.7-14
## [149] RSpectra_0.16-1 later_1.3.2
## [151] viridisLite_0.4.2 class_7.3-22
## [153] tibble_3.2.1 cluster_2.1.6
## [155] globals_0.16.2