library(millefy)
Warning message: “replacing previous import ‘IRanges::shift’ by ‘data.table::shift’ when loading ‘millefy’”Registered S3 method overwritten by 'xts': method from as.zoo.xts zoo Warning message: “replacing previous import ‘IRanges::distance’ by ‘destiny::distance’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::collapse’ by ‘dplyr::collapse’ when loading ‘millefy’”Warning message: “replacing previous import ‘data.table::last’ by ‘dplyr::last’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::union’ by ‘dplyr::union’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::slice’ by ‘dplyr::slice’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::intersect’ by ‘dplyr::intersect’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::setdiff’ by ‘dplyr::setdiff’ when loading ‘millefy’”Warning message: “replacing previous import ‘data.table::first’ by ‘dplyr::first’ when loading ‘millefy’”Warning message: “replacing previous import ‘IRanges::desc’ by ‘dplyr::desc’ when loading ‘millefy’”Warning message: “replacing previous import ‘data.table::between’ by ‘dplyr::between’ when loading ‘millefy’”Warning message: “replacing previous import ‘magrittr::extract’ by ‘tidyr::extract’ when loading ‘millefy’”
# Path to bigWig files
bwfiles = Sys.glob(file.path(system.file("extdata", package="millefy"), "*.bw"))
print(bwfiles)
[1] "/opt/conda/lib/R/library/millefy/extdata/RamDA_00h_A06.bw" [2] "/opt/conda/lib/R/library/millefy/extdata/RamDA_00h_A07.bw" [3] "/opt/conda/lib/R/library/millefy/extdata/RamDA_00h_A08.bw" [4] "/opt/conda/lib/R/library/millefy/extdata/RamDA_12h_A06.bw" [5] "/opt/conda/lib/R/library/millefy/extdata/RamDA_12h_A07.bw" [6] "/opt/conda/lib/R/library/millefy/extdata/RamDA_12h_A08.bw"
# Group labels for bigWig files (same length as bwfiles)
groups = c("00h", "00h", "00h", "12h", "12h", "12h")
# Color labels for bigWig files (A named vector with the same length as the number of kinds of \\code{groups})
color_labels <- colorRampPalette(c("yellow", "red"))(length(unique(groups))+1)[1:length(unique(groups))]
names(color_labels) <- unique(groups)
print(color_labels)
00h 12h "#FFFF00" "#FF7F00"
# Load gene models (It takes a little time)
path_gtf = system.file("extdata", "example.gtf", package="millefy")
dt_gtf_exon <- gtfToDtExon(path_gtf)
# Set tracks
## Single-cell track
max_value = 7000
scTrackBw <- list(path_bam_files = bwfiles, groups = groups, group_colors = color_labels, max_value = max_value, isBw=TRUE)
## Gene annotation track
geneTrack1 <- list(path_gtf = path_gtf, dt_gtf = dt_gtf_exon, label = "GENCODE")
# Prepare arguments for millefyPlot()
## List of tracks
tdlist <- list(scTrackBw, geneTrack1)
## List of track types
tt <- c("sc", "gene")
## List of track hights
heights = c(12, 2)
# Location to visualize
chr = "chr19" # character
start = 5824708 # integer
end = 5845478 # integer
text_main = "mESC 00h, 12h (Neat1)"
When we don't set the sc_sort_destiny parameter (default), the order of single cells is the order of bwfiles.
l <- millefyPlot(track_data=tdlist, track_type=tt, heights=heights,
sc_type = "heatmap",
chr = chr, start = start, end = end,
sc_avg = TRUE, sc_avg_height = 1,
title = text_main)
[1] "Begin millefyPlot: 2019-12-30 02:19:04" [1] "title" "sc" "avg" "gene" "axis" [1] "Importing BigWig: 2019-12-30 02:19:04" [1] "Finished millefyPlot: 2019-12-30 02:19:05"
When we set sc_sort_destiny = 'all', all single cells are reordered by diffusion maps.
millefy_adjust(sc_sort_destiny = 'all')
[1] "Begin millefyPlot: 2019-12-30 02:19:05" [1] "title" "sc" "avg" "gene" "axis"
Warning message in DiffusionMap(as.ExpressionSet(as.data.frame(mat))): “You have 990 genes. Consider passing e.g. n_pcs = 50 to speed up computation.”
Eigenvalue of DC1: 0.274219 [1] "Finished millefyPlot: 2019-12-30 02:19:06"
When we set sc_sort_destiny = 'group', all single cells in each group are reordered by diffusion maps.
millefy_adjust(sc_sort_destiny = 'group')
[1] "Begin millefyPlot: 2019-12-30 02:19:07" [1] "title" "sc" "avg" "gene" "axis"
Warning message in DiffusionMap(as.ExpressionSet(as.data.frame(mat))): “You have 990 genes. Consider passing e.g. n_pcs = 50 to speed up computation.”
Eigenvalue of DC1: 0.274219 [1] "Finished millefyPlot: 2019-12-30 02:19:08"
Using sc_avg_scale
, you can change the scale of the averaged single-cell read coverage tracks
millefy_adjust(sc_avg_scale = 7000)
[1] "Begin millefyPlot: 2019-12-30 02:19:08" [1] "title" "sc" "avg" "gene" "axis" [1] "Finished millefyPlot: 2019-12-30 02:19:08"
sessionInfo()
R version 3.6.1 (2019-07-05) Platform: x86_64-conda_cos6-linux-gnu (64-bit) Running under: Ubuntu 18.04.2 LTS Matrix products: default BLAS/LAPACK: /opt/conda/lib/R/lib/libRblas.so locale: [1] en_US.UTF-8 attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] millefy_0.1.9 loaded via a namespace (and not attached): [1] bitops_1.0-6 matrixStats_0.55.0 [3] destiny_3.0.0 xts_0.11-2 [5] GenomeInfoDb_1.22.0 repr_1.0.1 [7] tools_3.6.1 backports_1.1.5 [9] irlba_2.3.3 R6_2.4.1 [11] BiocGenerics_0.32.0 lazyeval_0.2.2 [13] colorspace_1.4-1 nnet_7.3-12 [15] sp_1.3-2 smoother_1.1 [17] tidyselect_0.2.5 curl_4.2 [19] compiler_3.6.1 Biobase_2.46.0 [21] DelayedArray_0.12.1 rtracklayer_1.46.0 [23] scales_1.1.0 DEoptimR_1.0-8 [25] lmtest_0.9-37 hexbin_1.27.3 [27] robustbase_0.93-5 proxy_0.4-23 [29] stringr_1.4.0 pbdZMQ_0.3-3 [31] digest_0.6.23 Rsamtools_2.2.1 [33] foreign_0.8-74 rio_0.5.16 [35] XVector_0.26.0 base64enc_0.1-3 [37] pkgconfig_2.0.3 htmltools_0.3.6 [39] TTR_0.23-5 ggthemes_4.2.0 [41] rlang_0.4.2 readxl_1.3.1 [43] zoo_1.8-6 jsonlite_1.6 [45] BiocParallel_1.20.1 dplyr_0.8.3 [47] zip_2.0.4 car_3.0-6 [49] RCurl_1.95-4.12 magrittr_1.5 [51] GenomeInfoDbData_1.2.2 Matrix_1.2-17 [53] Rcpp_1.0.3 IRkernel_1.0.2 [55] munsell_0.5.0 S4Vectors_0.24.1 [57] abind_1.4-5 lifecycle_0.1.0 [59] scatterplot3d_0.3-41 stringi_1.4.3 [61] carData_3.0-3 MASS_7.3-51.4 [63] SummarizedExperiment_1.16.1 zlibbioc_1.32.0 [65] grid_3.6.1 parallel_3.6.1 [67] forcats_0.4.0 crayon_1.3.4 [69] lattice_0.20-38 IRdisplay_0.7.0 [71] Biostrings_2.54.0 haven_2.2.0 [73] hms_0.5.2 zeallot_0.1.0 [75] pillar_1.4.3 ranger_0.11.2 [77] GenomicRanges_1.38.0 uuid_0.1-2 [79] boot_1.3-24 RcppHNSW_0.2.0 [81] codetools_0.2-16 stats4_3.6.1 [83] XML_3.98-1.20 glue_1.3.1 [85] evaluate_0.14 pcaMethods_1.78.0 [87] data.table_1.12.8 laeken_0.5.0 [89] vcd_1.4-4 vctrs_0.2.1 [91] VIM_4.8.0 cellranger_1.1.0 [93] tidyr_1.0.0 gtable_0.3.0 [95] purrr_0.3.3 knn.covertree_1.0 [97] assertthat_0.2.1 ggplot2_3.2.1 [99] openxlsx_4.1.4 RcppEigen_0.3.3.7.0 [101] e1071_1.7-3 RSpectra_0.16-0 [103] class_7.3-15 SingleCellExperiment_1.8.0 [105] tibble_2.1.3 GenomicAlignments_1.22.1 [107] IRanges_2.20.1 ggplot.multistats_1.0.0