browse_results
Jovan Tanevski
2021-09-23
Last updated: 2021-09-23
Checks: 7 0
Knit directory: mistyMBC/
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| File | Version | Author | Date | Message |
|---|---|---|---|---|
| Rmd | 02a4d8f | Jovan Tanevski | 2021-09-23 | add metadata and signature pca |
| html | 6a3c444 | Jovan Tanevski | 2021-09-15 | Build site. |
| Rmd | c6d135a | Jovan Tanevski | 2021-09-15 | extend results with celltype analysis |
| html | 6398d1c | Jovan Tanevski | 2021-09-13 | Build site. |
| Rmd | b562161 | Jovan Tanevski | 2021-09-13 | merge codex and merfish results |
| html | c457348 | Jovan Tanevski | 2021-09-09 | Build site. |
| html | aa6ca6b | Jovan Tanevski | 2021-09-09 | Build site. |
| Rmd | 04b30ad | Jovan Tanevski | 2021-09-09 | clean up results, focus on targets with gain |
| html | 2438eb2 | Jovan Tanevski | 2021-09-09 | Build site. |
| Rmd | b124494 | Jovan Tanevski | 2021-09-09 | update codex,merfish; add slideseq cellcom results |
| html | e0c1952 | Jovan Tanevski | 2021-07-22 | Build site. |
| html | 4dd6a02 | Jovan Tanevski | 2021-07-14 | Build site. |
| html | 913535e | Jovan Tanevski | 2021-06-17 | Build site. |
| Rmd | 736d8e3 | Jovan Tanevski | 2021-06-17 | subset merfish results |
| html | 1b68c27 | Jovan Tanevski | 2021-06-15 | Build site. |
| Rmd | 43913a8 | Jovan Tanevski | 2021-06-15 | auto publish date |
| Rmd | 34b1d9e | Jovan Tanevski | 2021-06-15 | explicit codex, merfish and exseq |
| html | e445e6f | Jovan Tanevski | 2021-06-11 | Build site. |
| Rmd | dd0219f | Jovan Tanevski | 2021-06-11 | add result browsing example |
Setup
Load necessary libraries
library(stringr)
library(dplyr)
library(mistyR)
library(ggplot2)
library(future)
plan(multisession) Output collection
Find the location of the results for all samples
outputs <- str_subset(list.dirs("output"), "processed") %>%
str_subset("failed", negate = TRUE)Collect the results for all samples, single modality and all replicates
misty.results.codex <- collect_results(str_subset(outputs, "codex"))
Collecting improvements
Collecting contributions
Collecting importances
Aggregatingmisty.results.merfish <- collect_results(str_subset(outputs, "merfish"))
Collecting improvements
Collecting contributions
Collecting importances
Aggregatingmisty.results.ligrcp <- collect_results(str_subset(outputs, "ligrcp"))
Collecting improvements
Collecting contributions
Collecting importances
Aggregatingmisty.results.ligpath <- collect_results(str_subset(outputs, "ligpath"))
Collecting improvements
Collecting contributions
Collecting importances
AggregatingGet metadata
sample.meta <- read.delim("data/HTAPP_MBC_spatial_annotations.tsv",
na.strings = "")Plot basic results
CODEX
Filter only genes with mean gain in variance explained of 1 or more to plot the gain and view contributions
misty.results.codex %>%
plot_improvement_stats(trim = 1) %>%
plot_view_contributions(trim = 1)
Plot interaction heatmaps
misty.results.codex %>%
plot_interaction_heatmap("intra", cutoff = 3, clean = TRUE) %>%
plot_interaction_heatmap("juxta.15", cutoff = 0.75, clean = TRUE, trim = 1) %>%
plot_interaction_heatmap("para.100", cutoff = 0.75, clean = TRUE, trim = 1)
Plot contrasts
misty.results.codex %>%
plot_contrast_heatmap("intra", "juxta.15", cutoff = 0.75, trim = 1) %>%
plot_contrast_heatmap("intra", "para.100", cutoff = 0.75, trim = 1)
| Version | Author | Date |
|---|---|---|
| 2438eb2 | Jovan Tanevski | 2021-09-09 |
Plot interaction communities
misty.results.codex %>%
plot_interaction_communities("intra", cutoff = 3) %>%
plot_interaction_communities("juxta.15", cutoff = 1) %>%
plot_interaction_communities("para.100", cutoff = 1)
| Version | Author | Date |
|---|---|---|
| 2438eb2 | Jovan Tanevski | 2021-09-09 |
| Version | Author | Date |
|---|---|---|
| 2438eb2 | Jovan Tanevski | 2021-09-09 |
Signatures and clustering
signature.per.codex <- misty.results.codex %>%
extract_signature("performance", trim = 1) %>%
mutate(sample = str_extract(sample, "HTAPP(-[:alnum:]+){3}"))
signature.per.pca <- signature.per.codex %>% select(-sample) %>% prcomp()
signature.per.pca.ann <- left_join(bind_cols(signature.per.codex %>% select(sample),
as.data.frame(signature.per.pca$x)),
sample.meta,
by = c("sample" = "name"))
ggplot(signature.per.pca.ann, aes(x = PC1, y = PC2)) +
geom_point(aes(color = receptors_primary)) +
theme_classic()
MERFISH
Filter only genes with mean gain in variance explained of 1 or more to plot the gain and view contributions
misty.results.merfish %>%
plot_improvement_stats(trim = 1) %>%
plot_view_contributions(trim = 1)
Plot interaction heatmaps
misty.results.merfish %>%
plot_interaction_heatmap("intra", cutoff = 6, clean = TRUE) %>%
plot_interaction_heatmap("juxta.15", cutoff = 2, clean = TRUE, trim = 1) %>%
plot_interaction_heatmap("para.100", cutoff = 1, clean = TRUE, trim = 1)
Plot contrasts
misty.results.merfish %>%
plot_contrast_heatmap("intra", "juxta.15", cutoff = 1.5, trim = 1) %>%
plot_contrast_heatmap("intra", "para.100", cutoff = 1, trim = 1)
Plot interaction communities
misty.results.merfish %>%
plot_interaction_communities("intra", cutoff = 6) %>%
plot_interaction_communities("juxta.15", cutoff = 3) %>%
plot_interaction_communities("para.100", cutoff = 1.5)
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
Signatures and clustering
signature.per.merfish <- misty.results.merfish %>%
extract_signature("performance", trim = 1) %>%
mutate(sample = str_extract(sample, "HTAPP(-[:alnum:]+){3}"))
signature.per.pca <- signature.per.merfish %>% select(-sample) %>% prcomp()
signature.per.pca.ann <- left_join(bind_cols(signature.per.merfish %>% select(sample),
as.data.frame(signature.per.pca$x)),
sample.meta,
by = c("sample" = "name"))
ggplot(signature.per.pca.ann, aes(x = PC1, y = PC2)) +
geom_point(aes(color = receptors_primary)) +
theme_classic()
Merge CODEX and MERFISH results
Filter only genes with mean gain in variance explained of 1 or more to plot the gain and view contributions
misty.results.merged <- collect_results(str_subset(outputs, "codex|merfish"))
Collecting improvements
Collecting contributions
Collecting importances
Aggregatingmisty.results.merged %>% plot_improvement_stats(trim = 1) %>%
plot_view_contributions(trim = 1)
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
Plot interaction heatmaps
misty.results.merged %>%
plot_interaction_heatmap("intra", cutoff = 6, clean = TRUE) %>%
plot_interaction_heatmap("juxta.15", cutoff = 1.5, clean = TRUE, trim = 1) %>%
plot_interaction_heatmap("para.100", cutoff = 1, clean = TRUE, trim = 1)
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
SlideSeq
Filter only ligands then pathways with mean gain in variance explained of 1 or more to plot the gain and view contributions
misty.results.ligrcp %>%
plot_improvement_stats(trim = 0.5) %>%
plot_view_contributions(trim = 0.5)Warning: Removed 1 rows containing missing values (geom_segment).
| Version | Author | Date |
|---|---|---|
| 6398d1c | Jovan Tanevski | 2021-09-13 |
misty.results.ligpath %>%
plot_improvement_stats(trim = 1) %>%
plot_view_contributions(trim = 1)
| Version | Author | Date |
|---|---|---|
| 6a3c444 | Jovan Tanevski | 2021-09-15 |
Plot interaction heatmaps
misty.results.ligrcp %>%
plot_interaction_heatmap("intra", cutoff = 5, clean = TRUE) %>%
plot_interaction_heatmap("juxta.15", cutoff = 2, clean = TRUE, trim = 0.5) %>%
plot_interaction_heatmap("para.100", cutoff = 2, clean = TRUE, trim = 0.5)
| Version | Author | Date |
|---|---|---|
| 6a3c444 | Jovan Tanevski | 2021-09-15 |
| Version | Author | Date |
|---|---|---|
| 6a3c444 | Jovan Tanevski | 2021-09-15 |
misty.results.ligpath %>%
plot_interaction_heatmap("intra", cutoff = 1, clean = TRUE) %>%
plot_interaction_heatmap("juxta.15", cutoff = 1.5, clean = TRUE, trim = 1) %>%
plot_interaction_heatmap("para.100", cutoff = 1.5, clean = TRUE, trim = 1)
Plot intrinsic pathway communities
misty.results.ligpath %>% plot_interaction_communities("intra", cutoff = 1)
Cell-type based analysis
We are interested in predicting the probability of a cell being of a cell-type of interest, by looking at the distribution of cell types in the neighborhood of 100 cells.
More conservative trimming of above 10% variance explained since the intraview is bypassed.
misty.results.ctype <- collect_results(str_subset(outputs, "ctype"))
Collecting improvements
Collecting contributions
Collecting importances
Aggregatingmisty.results.ctype %>%
plot_improvement_stats(trim = 10)
Plot neighborhood interactions
misty.results.ctype %>%
plot_interaction_heatmap("juxta.15", trim = 10, cutoff = 0.5) %>%
plot_interaction_heatmap("para.100", trim = 10, cutoff = 0.5)
Plot contrasts
misty.results.ctype %>%
plot_contrast_heatmap("para.100", "juxta.15", trim = 10, cutoff = 0.5) %>%
plot_contrast_heatmap("juxta.15", "para.100", trim = 10, cutoff = 0.5)
Plot communities
misty.results.ctype %>%
plot_interaction_communities("juxta.15", cutoff = 1) %>%
plot_interaction_communities("para.100", cutoff = 1)
sessionInfo()R version 4.1.1 (2021-08-10)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Big Sur 10.16
Matrix products: default
BLAS: /Library/Frameworks/R.framework/Versions/4.1/Resources/lib/libRblas.0.dylib
LAPACK: /Library/Frameworks/R.framework/Versions/4.1/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] stats graphics grDevices utils datasets methods base
other attached packages:
[1] future_1.22.1 ggplot2_3.3.5 mistyR_1.1.9 dplyr_1.0.7
[5] stringr_1.4.0 workflowr_1.6.2
loaded via a namespace (and not attached):
[1] tidyselect_1.1.1 xfun_0.26 bslib_0.3.0 purrr_0.3.4
[5] listenv_0.8.0 colorspace_2.0-2 vctrs_0.3.8 generics_0.1.0
[9] htmltools_0.5.2 yaml_2.2.1 utf8_1.2.2 rlang_0.4.11
[13] R.oo_1.24.0 jquerylib_0.1.4 later_1.3.0 pillar_1.6.2
[17] glue_1.4.2 withr_2.4.2 DBI_1.1.1 R.utils_2.10.1
[21] RColorBrewer_1.1-2 lifecycle_1.0.0 munsell_0.5.0 gtable_0.3.0
[25] R.methodsS3_1.8.1 codetools_0.2-18 evaluate_0.14 labeling_0.4.2
[29] knitr_1.34 fastmap_1.1.0 httpuv_1.6.3 parallel_4.1.1
[33] fansi_0.5.0 highr_0.9 furrr_0.2.3 Rcpp_1.0.7
[37] promises_1.2.0.1 scales_1.1.1 jsonlite_1.7.2 farver_2.1.0
[41] parallelly_1.28.1 fs_1.5.0 digest_0.6.27 stringi_1.7.4
[45] rprojroot_2.0.2 grid_4.1.1 tools_4.1.1 magrittr_2.0.1
[49] sass_0.4.0 tibble_3.1.4 tidyr_1.1.3 crayon_1.4.1
[53] whisker_0.4 pkgconfig_2.0.3 ellipsis_0.3.2 assertthat_0.2.1
[57] rmarkdown_2.11 R6_2.5.1 globals_0.14.0 igraph_1.2.6
[61] git2r_0.28.0 compiler_4.1.1