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Last updated: 2019-05-13
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Knit directory: 10x-adipocyte-analysis/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 79c83f6 | Pytrik Folkertsma | 2019-05-13 | Monocle feature selection |
| html | 4145fdd | Pytrik Folkertsma | 2019-05-13 | Build site. |
| Rmd | 4556d76 | Pytrik Folkertsma | 2019-05-13 | Monocle feature selection |
| html | 6030229 | Pytrik Folkertsma | 2019-04-03 | Build site. |
| Rmd | 5db5600 | Pytrik Folkertsma | 2019-04-03 | updated with new trajectory plot |
| html | 4d2bbec | Pytrik Folkertsma | 2019-03-29 | Build site. |
| Rmd | ad8fa06 | Pytrik Folkertsma | 2019-03-29 | monocle feature selection notebook |
This notebook shows the results of different feature selection methods of Monocle.
library(monocle)
library(cowplot)Genes with high dispersion
cds_high_disp <- readRDS('output/monocle/180831/monocle_high_dispersion/10x-180831-monocle')
plot_cell_trajectory(cds_high_disp, color_by = 'timepoint')
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
DE genes between T1T2T3 and T4T5
cds_timecombined <- readRDS('output/monocle/180831/monocle_time-combined/10x-180831-monocle')
plot_cell_trajectory(cds_timecombined, color_by='timepoint')
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
DE genes from cluster resolution 1.5
cds_res1.5 <- readRDS('output/monocle/180831/monocle_res1.5/10x-180831-monocle')
plot_cell_trajectory(cds_res1.5, color_by='timepoint')
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
Dataset split into T1+T2+T3 and T4+T5, DE genes from clusters res0.5.
cds_split_res0.5 <- readRDS('output/monocle/180831/monocle_T1T2T3_T4T5_res0.5/10x-180831-noreg-monocle')
plot_cell_trajectory(cds_split_res0.5, color_by='timepoint')
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
Dataset split into T1+T2+T3 and T4+T5, DE genes from clusters res1.5 are used here.
cds <- readRDS('output/monocle/180831/monocle_T1T2T3_T4T5_res1.5/10x-180831-monocle')
plot_cell_trajectory(cds, color_by='timepoint')
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
With doublets removed (used for all further analyses).
cds <- readRDS('output/monocle/180831/10x-180831-monocle-monocle_genelist_T1T2T3_T4T5_res.1.5')
plot_cell_trajectory(cds, color_by='timepoint')
DE genes between brown and white.
cds_type <- readRDS('output/monocle/180831/monocle_type/10x-180831-monocle')
plot_cell_trajectory(cds_type, color_by='timepoint')
| Version | Author | Date |
|---|---|---|
| 6030229 | Pytrik Folkertsma | 2019-04-03 |
DE genes between top10% lowest PC2 score and top10% highest PC2 score.
cds_pc2 <- readRDS('output/monocle/180831/monocle_PC2/10x-180831-monocle')
plot_grid(
plot_cell_trajectory(cds_pc2, color_by='timepoint'),
plot_cell_trajectory(cds_pc2, color_by='State.old') + scale_color_manual(values=c("#f67770", "#964B00", "orange"), name = "State"),
plot_cell_trajectory(cds_pc2, color_by='Pseudotime'),
plot_cell_trajectory(cds_pc2, color_by='State'),
ncol=2
)
| Version | Author | Date |
|---|---|---|
| 4d2bbec | Pytrik Folkertsma | 2019-03-29 |
sessionInfo()R version 3.5.3 (2019-03-11)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Storage
Matrix products: default
BLAS/LAPACK: /usr/lib64/libopenblas-r0.3.3.so
locale:
[1] LC_CTYPE=en_US.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_US.UTF-8 LC_COLLATE=en_US.UTF-8
[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
attached base packages:
[1] splines stats4 parallel stats graphics grDevices utils
[8] datasets methods base
other attached packages:
[1] cowplot_0.9.4 monocle_2.8.0 DDRTree_0.1.5
[4] irlba_2.3.3 VGAM_1.1-1 ggplot2_3.1.0
[7] Biobase_2.42.0 BiocGenerics_0.28.0 Matrix_1.2-17
loaded via a namespace (and not attached):
[1] ggrepel_0.8.0 Rcpp_1.0.1 lattice_0.20-38
[4] FNN_1.1.3 assertthat_0.2.1 rprojroot_1.3-2
[7] digest_0.6.18 slam_0.1-45 R6_2.4.0
[10] plyr_1.8.4 backports_1.1.3 qlcMatrix_0.9.7
[13] sparsesvd_0.1-4 evaluate_0.13 pillar_1.3.1
[16] rlang_0.3.2 lazyeval_0.2.2 whisker_0.3-2
[19] combinat_0.0-8 rmarkdown_1.12 labeling_0.3
[22] Rtsne_0.15 stringr_1.4.0 igraph_1.2.4
[25] pheatmap_1.0.12 munsell_0.5.0 compiler_3.5.3
[28] xfun_0.5 pkgconfig_2.0.2 htmltools_0.3.6
[31] tidyselect_0.2.5 tibble_2.1.1 gridExtra_2.3
[34] RANN_2.6.1 workflowr_1.2.0 matrixStats_0.54.0
[37] viridisLite_0.3.0 crayon_1.3.4 dplyr_0.8.0.1
[40] withr_2.1.2 grid_3.5.3 densityClust_0.3
[43] gtable_0.3.0 git2r_0.25.2 magrittr_1.5
[46] scales_1.0.0 docopt_0.6.1 stringi_1.4.3
[49] reshape2_1.4.3 viridis_0.5.1 fs_1.2.7
[52] limma_3.36.5 fastICA_1.2-1 RColorBrewer_1.1-2
[55] tools_3.5.3 glue_1.3.1 purrr_0.3.2
[58] HSMMSingleCell_0.114.0 yaml_2.2.0 colorspace_1.4-1
[61] cluster_2.0.7-1 knitr_1.22