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function_ST_NMKAKI_plots.R
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function_ST_NMKAKI_plots.R
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## ST NMK plotting function ###
## 06/09/2021 ####
## Simon Mo ######
source('/diskmnt/Datasets/Spatial_Transcriptomics/Analysis/NMK/NMK_integration_v5/script/NMK_colorset_v2.R')
source('/diskmnt/Datasets/Spatial_Transcriptomics/Analysis/NMK/NMK_integration_v5/script/function_ST_plot_general_v1.R')
make_nmk_mf_st_plot = function(...){
message('make_nmk_mf_st_plot function is being deprecated. Use STDistPlot_NMK_MF instead')
STDistPlot_NMK_MF(...)
}
###### ST Plotting functions -11022021 #####
# internal
STDistAKIPlots = function(obj, features, ...){
map(features, function(gene) STDistPlot_AKI(obj, feature = gene, show_axis=F,...)) %>% setNames(features)
}
STDistNMKPlots = function(obj, features, ...){
map(features, function(gene) STDistPlot_NMK_MF(obj,
feature = gene,
m_filter_piece = c('NMK0205E165M2U1L','NMK0205E165M2U1R'),
...)) %>% setNames(features)
}
# API
STDistPlots = function(obj, features, mode = c('AKI','NMK'), pt_size=1.8, ...){
mode = match.arg(mode)
pltfxn = switch(mode,
'AKI'=STDistAKIPlots,
'NMK'=STDistNMKPlots)
pltfxn(obj, features, pt_size=pt_size, ...)
}
STDistPlotsBoth = function(st_nmk, st_aki, features, pt_size=1.8, combine=T, ...){
pNMKs = STDistPlots(st_nmk, features, mode = 'NMK', pt_size=pt_size, ...) %>% setNames(features)
pAKIs = STDistPlots(st_aki, features, mode = 'AKI', pt_size=pt_size, ...) %>% setNames(features)
if(combine){
map(features, function(gene)
wrap_plots(N=pNMKs[[gene]], A=pAKIs[[gene]], design = "NNNNNNNNAAA") +
plot_annotation(title = gene, theme = theme(plot.title = element_text(size=20, face='bold')))
) %>% setNames(features)
}else{
list('NMK'=pNMKs, 'AKI'=pAKIs)
}
}
getSTPlotSize = function(type=c('NMK','AKI','Both')){
type = match.arg(type)
switch(type,
'NMK' =c(35,10),
'AKI' =c(9,9),
'Both'=c(40,10)) # plot size
}
PlotSTJupyter = function(p, type=c('NMK','AKI','Both')){
type = match.arg(type)
pdim = getSTPlotSize(type)
options(repr.plot.width=pdim[[1]], repr.plot.height=pdim[[2]])
suppressWarnings(plot(p))
}
PlotSTlistJupyter = function(plist, type){
walk(plist, function(p) PlotSTJupyter(p, type))
}
SaveSTPlots = function(plist, type=c('NMK','AKI','Both'), path){
today_date = Sys.Date() %>% format('%m%d%Y')
type = match.arg(type)
pdim = getSTPlotSize(type)
iwalk(plist, function(p, gene){
ggsave(plot=p, str_glue("{path}/STDist_{gene}_{today_date}.pdf"),
width = pdim[[1]],height = pdim[[2]]) %>% suppressWarnings
})
print(str_glue('Finished output {length(plist)} plots to {path}'))
}
#######
## STExpression value range
getSTExpRange = function(obj, imgs, feature, mode, assay_use){
cells = map(imgs, function(img){obj@images[[img]]@coordinates %>% rownames}) %>% unlist
if(mode %in% c('feature')){
exp_range = range( GetAssayData(obj) %>% .[feature, cells, drop=F] )
}else if(mode =='meta_numeric'){
exp_range = range( [email protected][cells, feature, drop=F])
}else if(mode =='assay'){
exp_range = GetAssay(obj, assay = assay_use) %>% GetAssayData() %>% t %>% .[cells, feature, drop=F] %>% range
}else{
stop("Mode not supported. Please double check")
}
exp_range
}
## AKI version 10062021
STDistPlot_AKI = function(obj, feature, pt_size=1.6, images_m, images_f, xlimits_m, ylimits_m, xlimits_f, ylimits_f,
meta_palette,
assay_use='RCTD_doubletRM_v3',
plot_title, plot_title_size=30, plot_subtitle_size=20, plot_caption_size=15,
plot_subtitle,
plot_caption,
exp_range_mode = 'all',
...
){
if(!missing(images_m)){
print('Warning. Using custom image from AKI object. All other parameters might not work well.')
}else{
images_m = c('NMK0129M3MU1','NMK0129AKID3MU1','NMK0203AKID8MU1')
}
if(!missing(images_f)){
print('Warning. Using custom image from AKI object. All other parameters might not work well.')
}else{
images_f = c('NMK0129M3FU1','NMK0129AKID3FU1','NMK1225AKID8FU1')
}
# Choose mode
if(feature %in% rownames(obj)){
message(str_glue('{feature} found in expression table. Use feature mode.')); mode = 'feature'
}else if(feature %in% colnames([email protected])){
if(is.numeric([email protected][[feature]])){
message(str_glue('{feature} found in @meta.data but numeric. Use meta_numeric mode.')); mode = 'meta_numeric'
}else{
message(str_glue('{feature} found in @meta.data. Use meta mode.')); mode = 'meta'
}
}else if(feature %in% rownames(GetAssay(obj, assay = assay_use))){
message(str_glue('{feature} found in assay {assay_use}. Use assay mode')); mode = 'assay'
}else{
stop(str_glue('{feature} not found in expression, meta or assay {assay_use}. please double check.'))
}
# Check if have palette for meta mode
if(mode =='meta' & missing(meta_palette)){
message("Plotting meta but missing meta_palette. Use defualt color")
meta_palette = pals::cols25(n = length(unique([email protected][[feature]]))) %>% setNames(unique([email protected][[feature]]))
}
# Set parameter
if(missing(xlimits_m)) xlimits_m = rep(list(c(-64,64)), length(images_m)) %>% setNames(images_m) # Named list with x limits
if(missing(xlimits_f)) xlimits_f = rep(list(c(-64,64)), length(images_f)) %>% setNames(images_f) # Named list with x limits
if(missing(ylimits_m)) ylimits_m = rep(list(c(-64,64)), length(images_m)) %>% setNames(images_m) # Named list with x limits
if(missing(ylimits_f)) ylimits_f = rep(list(c(-64,64)), length(images_f)) %>% setNames(images_f) # Named list with x limits
## Parameters v1
## 06/09/2021
label_m = c('Control','AKI-Day3','AKI-Day8') %>% setNames(images_m)
label_f = c('Control','AKI-Day3','AKI-Day8') %>% setNames(images_f)
# label_f = rep('',8) %>% setNames(images_f)
rotate_m = c(0,0,0) %>% setNames(images_m)
rotate_f = c(0,0,0) %>% setNames(images_f)
nodge_x_m = c(0,0,0) %>% setNames(images_m)
nodge_y_m = c(0,0,0) %>% setNames(images_m)
nodge_x_f = c(0,0,0) %>% setNames(images_f)
nodge_y_f = c(0,0,0) %>% setNames(images_f)
mirror_m = c('no','no','no') %>% setNames(images_m)
mirror_f = c('no','no','no') %>% setNames(images_f)
## Expresssion Range mode
if(exp_range_mode == 'all'){
message("Exp color range set to All sample")
dist_range_f = getSTExpRange(obj, c(images_m, images_f), feature=feature, mode = mode)
dist_range_m = getSTExpRange(obj, c(images_m, images_f), feature=feature, mode = mode)
}else if(exp_range_mode == 'by_sex'){
message("Exp color range set by Sex")
dist_range_f = getSTExpRange(obj, c(images_f), feature=feature, mode = mode)
dist_range_m = getSTExpRange(obj, c(images_m), feature=feature, mode = mode)
}else{
message("No Exp color range set")
dist_range_f = NULL
dist_range_m = NULL
}
#### Plot gene features #####
if(mode == 'feature'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
xlimits = xlimits_m, ylimits = ylimits_m,
dist_range = dist_range_m, # Pass to SingleSTDistIdentPlot. Expression range
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
xlimits = xlimits_f, ylimits = ylimits_f,
dist_range = dist_range_f, # Pass to SingleSTDistIdentPlot. Expression range
...
)
}else if(mode =='meta'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode, meta_palette = meta_palette,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
xlimits = xlimits_m, ylimits = ylimits_m,
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode, meta_palette = meta_palette,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
xlimits = xlimits_f, ylimits = ylimits_f,
...
)
}else if(mode =='meta_numeric'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
xlimits = xlimits_m, ylimits = ylimits_m,
dist_range = dist_range_m, # Pass to SingleSTDistIdentPlot. Expression range
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
xlimits = xlimits_f, ylimits = ylimits_f,
dist_range = dist_range_f, # Pass to SingleSTDistIdentPlot. Expression range
...
)
}else if(mode == 'assay'){ # 7/27/2021 For cell assay
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
xlimits = xlimits_m, ylimits = ylimits_m,
assay_use = assay_use,
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
xlimits = xlimits_f, ylimits = ylimits_f,
assay_use = assay_use,
...
)
}
# Combine plots
male_widths = map(xlimits_m, ~abs(.x[[1]]-.x[[2]])) %>% unlist
male_hights = map(ylimits_m, ~abs(.x[[1]]-.x[[2]])) %>% unlist
switch(missing(plot_subtitle), NULL, plot_subtitle)
message('Current version works well with width = ?, height = 10 ')
mstrip = wrap_plots(p_mlist, nrow=1, widths = male_widths, heights =male_hights)
fstrip = wrap_plots(p_flist, nrow=1, widths = male_widths, heights =male_hights)
# Plot annotations
if(missing(plot_title)) plot_title = feature
if(missing(plot_subtitle)) plot_subtitle = ""
if(missing(plot_caption)) plot_caption = ""
((mstrip/fstrip) &
theme(plot.margin = unit(c(0,0,0,0),'lines')) )+ ## Still dont know how to remove space between 2 stirps ....
plot_annotation(
title = plot_title,
subtitle = plot_subtitle,
caption = plot_caption,
theme = theme(plot.title = element_text(face = 'bold', size = plot_title_size),
plot.subtitle = element_text(face = 'bold', size = plot_subtitle_size),
plot.caption = element_text(face = 'bold', size = plot_caption_size))
)
}
STDistPlot_NMK_MF = function(obj, feature, pt_size=1.6, images_m, images_f, xlimits_m, ylimits_m, xlimits_f, ylimits_f,
m_filter_piece = c('NMK0205E165M2U1L','NMK0205E165M2U1R'), # Use on the first image for m
f_filter_piece = c('NMK0318E165F2U1L','NMK0318E165F2U1R'), # Use on the first image for m,
m_filter_group1, f_filter_group1,
meta_palette,
assay_use='RCTD_doubletRM_v3',
plot_title, plot_title_size=30, plot_subtitle_size=20, plot_caption_size=15,
plot_subtitle,
plot_caption,
...
){
if(!missing(images_m)){
print('Warning. Using custom image from NMK object. All other parameters might not work well.')
}else{
images_m = c('NMK0205E165MU1','NMK0117P0FMU1L','NMK0115W1FMU1','NMK0111W2MU1','NMK1201W3MU1','NMK0129W12MU1','NMK1207W52MU1','NMK0226W113MU1')
}
if(!missing(images_f)){
print('Warning. Using custom image from NMK object. All other parameters might not work well.')
}else{
images_f = c('NMK0318E165FU1','NMK0117P0FMU1L','NMK0115W1FMU1','NMK0111W2FU1','NMK1201W3FU2','NMK0129W12FU1','NMK1207W52FU1','NMK0430W113FU1')
}
# Choose mode
if(feature %in% rownames(obj)){
message(str_glue('{feature} found in expression table. Use feature mode.')); mode = 'feature'
}else if(feature %in% colnames([email protected])){
if(is.numeric([email protected][[feature]])){
message(str_glue('{feature} found in @meta.data but numeric. Use meta_numeric mode.')); mode = 'meta_numeric'
}else{
message(str_glue('{feature} found in @meta.data. Use meta mode.')); mode = 'meta'
}
}else if(feature %in% rownames(GetAssay(obj, assay = assay_use))){
message(str_glue('{feature} found in assay {assay_use}. Use assay mode')); mode = 'assay'
}else{
stop(str_glue('{feature} not found in expression, meta or assay {assay_use}. please double check.'))
}
# Check if have palette for meta mode
if(mode =='meta' & missing(meta_palette)){
message("Plotting meta but missing meta_palette. Use defualt color")
meta_palette = paletteer::paletteer_d("ggsci::default_igv", n = length(unique([email protected][[feature]]))) %>% setNames(unique([email protected][[feature]]))
# meta_palette = pals::cols25(n = length(unique([email protected][[feature]]))) %>% setNames(unique([email protected][[feature]]))
}
# xlimts Parameters v06220221
#if(missing(xlimits_m)) xlimits_m = c(list(c(-40,40)), list(c(-22,21)) ,list(c(-35,30)), list(c(-55,64)), rep(list(c(-64,64)), 8-4)) %>% setNames(images_m)
#if(missing(xlimits_f)) xlimits_f = c(list(c(-40,40)), list(c(-22,21)) ,list(c(-35,30)), list(c(-55,64)), rep(list(c(-64,64)), 8-4)) %>% setNames(images_f)
# !!! DEPRECATING filter group become filter piece
if(!missing(m_filter_group1)) {
warning("m_filter_group1 being deprecated. Use m_filter_piece instead")
m_filter_piece = m_filter_group1
}
if(!missing(f_filter_group1)) {
warning("f_filter_group1 being deprecated. Use f_filter_piece instead")
f_filter_piece = f_filter_group1
}
# Set parameter
if(missing(xlimits_m)) xlimits_m = rep(list(c(-64,64)), length(images_m)) %>% setNames(images_m) # Named list with x limits
if(missing(xlimits_f)) xlimits_f = rep(list(c(-64,64)), length(images_f)) %>% setNames(images_f) # Named list with x limits
if(missing(ylimits_m)) ylimits_m = rep(list(c(-64,64)), length(images_m)) %>% setNames(images_m) # Named list with x limits
if(missing(ylimits_f)) ylimits_f = rep(list(c(-64,64)), length(images_f)) %>% setNames(images_f) # Named list with x limits
## Parameters v1
## 06/09/2021
label_m = c('E165','P0','W1','W2','W3','W12','W52','W113') %>% setNames(images_m)
label_f = c('E165','P0','W1','W2','W3','W12','W52','W113') %>% setNames(images_f)
# label_f = rep('',8) %>% setNames(images_f)
rotate_m = c(0,0,0,0,0,0,0,0) %>% setNames(images_m)
rotate_f = c(0,0,0,0,0,0,0,0) %>% setNames(images_f)
nodge_x_m = c(0,0,0,0,0,0,0,0) %>% setNames(images_m)
nodge_y_m = c(-20,10,0,10,0,0,0,0) %>% setNames(images_m)
nodge_x_f = c(0,0,0,0,0,0,0,0) %>% setNames(images_f)
nodge_y_f = c(-35,5,-10,0,0,0,0,0) %>% setNames(images_f)
mirror_m = c('no','xy','x','no','no','no','y','no') %>% setNames(images_m)
mirror_f = c('no','no','no','no','no','no','y','xy') %>% setNames(images_f)
## Run these to check and select E165 pieces in 'filter_piece'
#[email protected] %>% filter(orig.ident ==images_m[[1]]) %>% count(Piece_ID)
#[email protected] %>% filter(orig.ident ==images_f[[1]]) %>% count(Piece_ID)
##
## Get distribution value range
cells = map(c(images_m, images_f), function(img){obj@images[[img]]@coordinates %>% rownames}) %>% unlist
if(mode %in% c('feature')){
dist_range = range( GetAssayData(obj) %>% .[feature, cells, drop=F] )
}else if(mode =='meta_numeric'){
dist_range = range( [email protected][cells, feature, drop=F])
}
#### Plot gene features #####
if(mode == 'feature'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
filter_piece_col = 'Piece_ID', filter_piece = m_filter_piece,
xlimits = xlimits_m, ylimits = ylimits_m,
dist_range = dist_range, # Pass to SingleSTDistIdentPlot
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
filter_piece_col = 'Piece_ID', filter_piece = f_filter_piece,
xlimits = xlimits_f, ylimits = ylimits_f,
dist_range = dist_range, # Pass to SingleSTDistIdentPlot
...
)
}else if(mode =='meta'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode, meta_palette = meta_palette,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
filter_piece_col = 'Piece_ID', filter_piece = m_filter_piece,
xlimits = xlimits_m, ylimits = ylimits_m,
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode, meta_palette = meta_palette,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
filter_piece_col = 'Piece_ID', filter_piece = f_filter_piece,
xlimits = xlimits_f, ylimits = ylimits_f,
...
)
}else if(mode =='meta_numeric'){
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
filter_piece_col = 'Piece_ID', filter_piece = m_filter_piece,
xlimits = xlimits_m, ylimits = ylimits_m,
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
filter_piece_col = 'Piece_ID', filter_piece = f_filter_piece,
xlimits = xlimits_f, ylimits = ylimits_f,
...
)
}else if(mode == 'assay'){ # 7/27/2021 For cell assay
p_mlist = MultipleSTDistIdentPlot(obj, images_m, feature= feature, left_label='M', mode = mode,
pt_size=pt_size, mirror =mirror_m, top_labels=label_m,
filter_meta = [email protected], filter_col='Sex',
filter_group='M',
nodges_x= nodge_x_m, nodges_y= nodge_y_m,
filter_piece_col = 'Piece_ID', filter_piece = m_filter_piece,
xlimits = xlimits_m, ylimits = ylimits_m,
assay_use = assay_use,
...
)
p_flist = MultipleSTDistIdentPlot(obj, images_f, feature= feature, left_label='F', mode = mode,
pt_size=pt_size, mirror =mirror_f, #top_labels=label_f,
filter_meta = [email protected], filter_col='Sex',
filter_group='F',
nodges_x= nodge_x_f, nodges_y= nodge_y_f,
filter_piece_col = 'Piece_ID', filter_piece = f_filter_piece,
xlimits = xlimits_f, ylimits = ylimits_f,
assay_use = assay_use,
...
)
}
# Combine plots
male_widths = map(xlimits_m, ~abs(.x[[1]]-.x[[2]])) %>% unlist
male_hights = map(ylimits_m, ~abs(.x[[1]]-.x[[2]])) %>% unlist
switch(missing(plot_subtitle), NULL, plot_subtitle)
message('Current version works well with width = 35, height = 10 ')
mstrip = wrap_plots(p_mlist, nrow=1, widths = male_widths, heights =male_hights)
fstrip = wrap_plots(p_flist, nrow=1, widths = male_widths, heights =male_hights)
# Plot annotations
if(missing(plot_title)) plot_title = feature
if(missing(plot_subtitle)) plot_subtitle = ""
if(missing(plot_caption)) plot_caption = ""
((mstrip/fstrip) &
theme(plot.margin = unit(c(0,0,0,0),'lines')) )+ ## Still dont know how to remove space between 2 stirps ....
plot_annotation(
title = plot_title,
subtitle = plot_subtitle,
caption = plot_caption,
theme = theme(plot.title = element_text(face = 'bold', size = plot_title_size),
plot.subtitle = element_text(face = 'bold', size = plot_subtitle_size),
plot.caption = element_text(face = 'bold', size = plot_caption_size))
)
}
make_nmk_multiple_st_plot = function(obj, features, ...){
p_list = map(features, function(feature){
STDistPlot_NMK_MF(obj = obj, feature = feature, ...)
}) %>% setNames(features)
message("Done. Output as a list of plots")
p_list
}