Below is a brief summary of what each of the scripts do.
01_20200415_preprocessingTI: Preprocessing of scRNA-seq data to prepare it for trajectory inference. Includes removal of doublets, temporally asynchronous cells as well as respiratory and microvillous cells.02_20200819_trajectoryInference: Trajectory inference.02Supp_geneExpressionTrajectory: Supplementary script visualizing gene expression of genes along the trajectory or pseudotime. Use this if you'd like to explore gene expression.03_evaluateKHBCRegen: Evaluating the number of knots to use fortradeSeq.04_fitNBGam_differentKnots: FittradeSeqNB-GAM.05_20201001_figure1: Plots of trajectory and marker discovery for each lineage usingtradeSeq. Includes code for generating panels b-e of Figure 1.06_20200916_hbcInjuryTFAnalysis_threshold: Transcription factor peak analysis finding TFs that peak in each lineage. Code for Figure 2.07_network2Core: Extracting the 2-core of the association networks estimated using learn2count.08_20201007_tfCascadeNetworkIntegration_figure2: Relate association network and TF peak analyses. Generation of Figure 3.08Supp_nichenetAnalysis: Supplementary script on NicheNet analysis.09_20200610_scATAC_injury_archr_samples_pairwiseHBC_v3: scATAC-seq data analysis. Identification of cell types, and HBC cell states. Peak calling on HBC scATAC-seq cells. TF motif enrichment in marker peaks for each HBC cell state. Plots for Figure 5.10_20200715_downstreamArchRAnalysis_v2: Differential accessibility analysis ofArchRgene activity scores. Comparing injured vs uninjured cells over all cell states. Assessing injury effect within hybrid cells. Assessing cell state effect within injured and uninjured cells.10Supp_atacHBCMotifs_homer: Homer TF enrichment of DA genes.11_20201012_ATAC_hbcClustering_v3: Integration of 24H PI scRNA-seq HBC cells with scATAC-seq HBC cells. Cell type transfer from scRNA-seq to scATAC-seq. Checking gene expression of scATAC-seq markers as well as contribution of injured versus uninjured cells. Identification of scATAC-seq markers for transferred hybrid1 and hybrid2 labels. Peak calling using transferred labels and TF motif enrichment on marker peaks identified as such. Plots for Figure 6.11Supp_ATACExploration: Identification of marker genes for each of the hybrid transferred labels. Plotting accessibility of key lineage-specific genes from other cell types and lineages. Plotting accessibility of hybrid markers that were identified using scRNA-seq. Use this if you'd like to explore accessibility of genes.11Supp2_atacRNAExploration: Exploring ATAC markers in scRNA-seq data. This includes the current lineage-traced data and also (a subset of) the whole OE data.11Supp3_integratescRNAseq: Integration of lineage-traced with whole OE data. Shows a similarity between regenerated HBCs from lineage-traced data to truly resting cells from whole OE data. Identification of marker genes of hybrid clusters and activated/resting HBCs using scRNA-seq data.12_211022_integrateCascadeMotifs: Supplementary script on linking the results of TF cascade to motif enrichment.
All data can be found in the following DropBox folder: https://www.dropbox.com/sh/qqaz99r64f9odvr/AABXsRGoeKbkaOOst9nORlVna?dl=0
## R version 3.6.2 (2019-12-12)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.5
##
## Matrix products: default
## BLAS: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRblas.0.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
##
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
##
## attached base packages:
## [1] grid parallel stats4 stats graphics grDevices utils
## [8] datasets methods base
##
## other attached packages:
## [1] chromVARmotifs_0.2.0 motifmatchr_1.8.0
## [3] circlize_0.4.8 ComplexHeatmap_2.3.1
## [5] presto_1.0.0 nabor_0.5.0
## [7] BSgenome.Mmusculus.UCSC.mm10_1.4.0 BSgenome_1.54.0
## [9] rtracklayer_1.46.0 Biostrings_2.54.0
## [11] XVector_0.26.0 ggalluvial_0.12.0
## [13] ArchR_0.9.5 magrittr_1.5
## [15] rhdf5_2.30.1 data.table_1.12.8
## [17] patchwork_1.0.0 Seurat_3.1.5
## [19] Signac_0.2.5 harmony_1.0
## [21] Rcpp_1.0.6 scater_1.14.6
## [23] uwot_0.1.5 scran_1.14.5
## [25] forcats_0.4.0 stringr_1.4.0
## [27] dplyr_1.0.3 purrr_0.3.3
## [29] readr_1.3.1 tidyr_1.0.2
## [31] tibble_2.1.3 tidyverse_1.3.0
## [33] irlba_2.3.3 Matrix_1.3-2
## [35] gridExtra_2.3 wesanderson_0.3.6
## [37] pheatmap_1.0.12 ggplot2_3.3.2
## [39] RColorBrewer_1.1-2 clusterExperiment_2.6.1
## [41] bigmemory_4.5.36 rgl_0.100.30
## [43] cowplot_1.0.0 SingleCellExperiment_1.8.0
## [45] SummarizedExperiment_1.16.1 DelayedArray_0.12.2
## [47] BiocParallel_1.20.1 matrixStats_0.56.0
## [49] Biobase_2.46.0 GenomicRanges_1.38.0
## [51] GenomeInfoDb_1.22.0 IRanges_2.20.2
## [53] S4Vectors_0.24.3 BiocGenerics_0.32.0
## [55] slingshot_1.4.0 princurve_2.1.4
##
## loaded via a namespace (and not attached):
## [1] R.methodsS3_1.7.1 pkgmaker_0.31
## [3] bit64_0.9-7 knitr_1.28
## [5] R.utils_2.9.2 KEGGREST_1.26.1
## [7] TFBSTools_1.22.0 RCurl_1.98-1.1
## [9] doParallel_1.0.15 generics_0.0.2
## [11] RSQLite_2.2.0 VGAM_1.1-2
## [13] RANN_2.6.1 future_1.16.0
## [15] ggfittext_0.9.0 bit_1.1-15.2
## [17] phylobase_0.8.6 webshot_0.5.2
## [19] xml2_1.3.2 lubridate_1.7.4
## [21] httpuv_1.5.2 assertthat_0.2.1
## [23] DirichletMultinomial_1.26.0 viridis_0.5.1
## [25] xfun_0.12 hms_0.5.3
## [27] evaluate_0.14 promises_1.1.0
## [29] fansi_0.4.1 progress_1.2.2
## [31] caTools_1.18.0 dbplyr_1.4.2
## [33] readxl_1.3.1 igraph_1.2.4.2
## [35] DBI_1.1.0 htmlwidgets_1.5.1
## [37] ellipsis_0.3.0 gggenes_0.4.0
## [39] RSpectra_0.16-0 crosstalk_1.0.0
## [41] backports_1.1.5 annotate_1.64.0
## [43] gridBase_0.4-7 locfdr_1.1-8
## [45] RcppParallel_4.4.4 vctrs_0.3.6
## [47] Cairo_1.5-10 here_0.1
## [49] ROCR_1.0-7 withr_2.1.2
## [51] sctransform_0.3.2 GenomicAlignments_1.22.1
## [53] prettyunits_1.1.1 softImpute_1.4
## [55] cluster_2.1.0 seqLogo_1.50.0
## [57] ape_5.3 lazyeval_0.2.2
## [59] crayon_1.3.4 genefilter_1.68.0
## [61] labeling_0.3 edgeR_3.28.0
## [63] pkgconfig_2.0.3 nlme_3.1-142
## [65] vipor_0.4.5 rlang_0.4.10
## [67] globals_0.12.5 lifecycle_0.2.0
## [69] miniUI_0.1.1.1 registry_0.5-1
## [71] bigmemory.sri_0.1.3 modelr_0.1.5
## [73] rsvd_1.0.2 cellranger_1.1.0
## [75] rprojroot_1.3-2 lmtest_0.9-37
## [77] rngtools_1.5 ggseqlogo_0.1
## [79] Rhdf5lib_1.8.0 zoo_1.8-7
## [81] reprex_0.3.0 beeswarm_0.2.3
## [83] GlobalOptions_0.1.1 ggridges_0.5.2
## [85] rjson_0.2.20 png_0.1-7
## [87] viridisLite_0.3.0 bitops_1.0-6
## [89] R.oo_1.23.0 rncl_0.8.3
## [91] KernSmooth_2.23-16 blob_1.2.1
## [93] DelayedMatrixStats_1.8.0 shape_1.4.4
## [95] manipulateWidget_0.10.0 zinbwave_1.11.6
## [97] CNEr_1.20.0 scales_1.1.0
## [99] memoise_1.1.0 plyr_1.8.5
## [101] ica_1.0-2 howmany_0.3-1
## [103] gplots_3.0.1.2 bibtex_0.4.2.2
## [105] gdata_2.18.0 zlibbioc_1.32.0
## [107] compiler_3.6.2 lsei_1.2-0
## [109] dqrng_0.2.1 clue_0.3-57
## [111] fitdistrplus_1.0-14 Rsamtools_2.2.1
## [113] cli_2.0.1 ade4_1.7-13
## [115] listenv_0.8.0 pbapply_1.4-2
## [117] MASS_7.3-51.4 tidyselect_1.1.0
## [119] stringi_1.4.5 yaml_2.2.1
## [121] BiocSingular_1.2.1 locfit_1.5-9.1
## [123] ggrepel_0.8.1 tools_3.6.2
## [125] future.apply_1.4.0 rstudioapi_0.11
## [127] uuid_0.1-2 TFMPvalue_0.0.8
## [129] foreach_1.4.7 RNeXML_2.4.2
## [131] farver_2.0.3 Rtsne_0.15
## [133] digest_0.6.27 FNN_1.1.3
## [135] shiny_1.4.0 broom_0.5.4
## [137] later_1.0.0 RcppAnnoy_0.0.16
## [139] httr_1.4.1 AnnotationDbi_1.48.0
## [141] npsurv_0.4-0 kernlab_0.9-29
## [143] colorspace_1.4-1 rvest_0.3.5
## [145] XML_3.99-0.3 fs_1.3.1
## [147] reticulate_1.14 splines_3.6.2
## [149] statmod_1.4.33 plotly_4.9.1
## [151] xtable_1.8-4 poweRlaw_0.70.2
## [153] jsonlite_1.6.1 R6_2.4.1
## [155] pillar_1.4.3 htmltools_0.5.1.1
## [157] mime_0.9 NMF_0.21.0
## [159] glue_1.4.2 fastmap_1.0.1
## [161] BiocNeighbors_1.4.1 codetools_0.2-16
## [163] tsne_0.1-3 lattice_0.20-38
## [165] ggbeeswarm_0.6.0 leiden_0.3.4
## [167] gtools_3.8.1 GO.db_3.10.0
## [169] survival_3.1-8 limma_3.42.1
## [171] rmarkdown_2.1 munsell_0.5.0
## [173] GetoptLong_0.1.8 GenomeInfoDbData_1.2.2
## [175] iterators_1.0.12 HDF5Array_1.14.1
## [177] haven_2.2.0 reshape2_1.4.3
## [179] gtable_0.3.0