This notebook analyzes feature distributions. We categorize features as being multimodal, skewed but unimodel, or symmetric and unimodal. A statistic (Hartigan’s dip test statistic) is used to check for multimodality. Unimodal features with skewness > 2 are categorized as “skewed”. All other features are categorized as symmetric and unimodal. This is reported in a table in the notebook and also available as a CSV file. Additionally, we plot the histogram of each feature, saved as a PNG.
set.seed(42)Download files
mkdir -p ~/Downloads/BBBC022_workspace
cd ~/Downloads/BBBC022_workspace
wget https://s3.amazonaws.com/imaging-platform-collaborator/2016_09_09_cytominer_workshop/backend_BBBC022_20646.tar.gz
wget https://s3.amazonaws.com/imaging-platform-collaborator/2016_09_09_cytominer_workshop/metadata_BBBC022.tar.gz
tar xvzf backend_BBBC022_20646.tar.gz
tar xvzf metadata_BBBC022.tar.gz
Load database backend
workspace_dir <- file.path(Sys.getenv("HOME"), "Downloads", "BBBC022_workspace")
batch_id <- "BBBC022_2013"
plate_id <- "20646"
plate_backend <-
file.path(workspace_dir,
paste0("backend/", batch_id, "/", plate_id, "/", plate_id,".sqlite"))
db <- src_sqlite(path = plate_backend)Load metadata
barcode_platemap <-
suppressMessages(read_csv(file.path(workspace_dir, paste0("metadata/", batch_id, "/barcode_platemap.csv"))))
metadata <-
paste0(
file.path(workspace_dir, paste0("metadata/", batch_id,"/platemap/")),
barcode_platemap$Plate_Map_Name %>% unique(),
".txt"
) %>%
map_df(function(x) suppressMessages(read_tsv(x))) %>%
rename(Plate_Map_Name = plate_map_name) %>%
inner_join(barcode_platemap, by = c("Plate_Map_Name")) %>%
mutate(Plate = Assay_Plate_Barcode,
Well = well_position) %>%
mutate(broad_sample = ifelse(is.na(broad_sample), "DMSO", broad_sample))
names(metadata) %<>% str_c("Metadata", ., sep = "_")
if (db_has_table(db$con, table = "metadata")) {
db$con %>% db_drop_table(table = "metadata")
}
metadata <- dplyr::copy_to(db, metadata)Sample cells from DMSO wells
frac_cells_per_image <- .8
images_per_well <- 6
# sample images from DMSO wells
sampled_images <-
metadata %>%
filter(Metadata_broad_sample == "DMSO") %>%
inner_join(tbl(db, "Image"), by = c("Metadata_Plate" = "Image_Metadata_Plate",
"Metadata_Well" = "Image_Metadata_Well")) %>%
select(matches("Metadata_|TableNumber|ImageNumber")) %>%
collect() %>%
group_by(Metadata_Plate, Metadata_Well) %>%
sample_n(images_per_well) %>%
ungroup()
if (db_has_table(db$con, table = "sampled_images")) {
db$con %>% db_drop_table(table = "sampled_images")
}
sampled_images <- dplyr::copy_to(db, sampled_images)
# sample cells from the sampled images
sampled_objects <-
sampled_images %>%
inner_join(
tbl(db, "Cells") %>% select(TableNumber, ImageNumber, ObjectNumber),
by = c("TableNumber", "ImageNumber")) %>%
collect() %>%
group_by(TableNumber, ImageNumber) %>%
sample_frac(frac_cells_per_image) %>%
ungroup()
if (db_has_table(db$con, table = "sampled_objects")) {
db$con %>% db_drop_table(table = "sampled_objects")
}
sampled_objects <- dplyr::copy_to(db, sampled_objects)
sampled_objects %<>%
inner_join(tbl(db, "Cells"), by = c("TableNumber", "ImageNumber", "ObjectNumber")) %>%
inner_join(tbl(db, "Cytoplasm"), by = c("TableNumber", "ImageNumber", "ObjectNumber")) %>%
inner_join(tbl(db, "Nuclei"), by = c("TableNumber", "ImageNumber", "ObjectNumber")) %>%
collect(n = Inf)Peform Hartigan’s dip test for multimodality.
diptest_p_values <-
sampled_objects %>%
select(matches("^Cells_|^Cytoplasm_|^Nuclei_")) %>%
map(function(x) diptest::dip.test(x)[["p.value"]]) %>%
as_data_frame() %>%
gather(feature, diptest_p_value)
diptest_p_values$diptest_p_value_adjusted <-
p.adjust(diptest_p_values$diptest_p_value, method = "BH")Compute skewness
skewnesses <-
sampled_objects %>%
select(matches("^Cells_|^Cytoplasm_|^Nuclei_")) %>%
map(e1071::skewness) %>%
as_data_frame() %>%
gather(feature, skewness)Collect, summarize and save statistics
features_statistics <-
inner_join(diptest_p_values, skewnesses, by = c("feature")) %>%
mutate(is_multimodal = diptest_p_value_adjusted < 0.05) %>%
mutate(is_skewed = skewness > 2) %>%
mutate(is_skewed = ifelse(is_multimodal, NA, is_skewed))
features_statistics %>%
group_by(is_skewed) %>%
tally() %>%
knitr::kable(caption = "Feature skewness summary", digits = 2)| is_skewed | n |
|---|---|
| FALSE | 601 |
| TRUE | 203 |
| NA | 20 |
features_statistics %>%
group_by(is_multimodal) %>%
tally() %>%
knitr::kable(caption = "Feature multimodality summary", digits = 2)| is_multimodal | n |
|---|---|
| FALSE | 808 |
| TRUE | 16 |
features_statistics %>%
mutate(neg_log_p_value_adjusted_dip = -log(diptest_p_value_adjusted, base = 10)) %>%
filter(diptest_p_value_adjusted < 0.25) %>%
select(feature, neg_log_p_value_adjusted_dip) %>%
arrange(-neg_log_p_value_adjusted_dip) %>%
knitr::kable(caption = "Feature multimodality table", digits = 3)| feature | neg_log_p_value_adjusted_dip |
|---|---|
| Cells_Intensity_MaxIntensityEdge_DNA | Inf |
| Cells_Intensity_MinIntensityEdge_AGP | Inf |
| Cells_Intensity_UpperQuartileIntensity_DNA | Inf |
| Cells_Neighbors_FirstClosestObjectNumber_5 | Inf |
| Cells_Neighbors_NumberOfNeighbors_5 | Inf |
| Cells_Neighbors_SecondClosestObjectNumber_5 | Inf |
| Cytoplasm_Intensity_MinIntensityEdge_AGP | Inf |
| Nuclei_Intensity_IntegratedIntensity_DNA | Inf |
| Nuclei_Neighbors_FirstClosestObjectNumber_1 | Inf |
| Nuclei_Neighbors_NumberOfNeighbors_1 | Inf |
| Nuclei_Neighbors_PercentTouching_1 | Inf |
| Nuclei_Neighbors_SecondClosestObjectNumber_1 | Inf |
| Cells_Parent_Nuclei | 3.765 |
| Cytoplasm_Parent_Cells | 3.765 |
| Cytoplasm_Parent_Nuclei | 3.765 |
| Nuclei_AreaShape_Orientation | 2.316 |
| Cells_AreaShape_FormFactor | 0.663 |
features_statistics %>%
select(feature, skewness) %>%
na.omit() %>%
filter(abs(skewness) > 2) %>%
arrange(-abs(skewness)) %>%
knitr::kable(caption = "Feature skewness table", digits = 3)| feature | skewness |
|---|---|
| Cells_AreaShape_EulerNumber | -172.108 |
| Cytoplasm_AreaShape_EulerNumber | -19.323 |
| Nuclei_Texture_AngularSecondMoment_DNA_5 | 15.635 |
| Nuclei_Texture_AngularSecondMoment_DNA_3 | 14.804 |
| Cytoplasm_Intensity_MaxIntensity_DNA | 13.839 |
| Cytoplasm_Intensity_StdIntensity_DNA | 11.171 |
| Cytoplasm_Intensity_MaxIntensityEdge_DNA | 9.932 |
| Cells_Intensity_LowerQuartileIntensity_DNA | 8.895 |
| Nuclei_Intensity_StdIntensity_AGP | 7.923 |
| Nuclei_Intensity_MassDisplacement_AGP | 7.878 |
| Nuclei_Intensity_MaxIntensityEdge_Mito | 7.680 |
| Nuclei_Intensity_StdIntensity_Mito | 7.584 |
| Nuclei_Intensity_MaxIntensity_Mito | 7.374 |
| Cells_Intensity_MaxIntensityEdge_Mito | 7.200 |
| Cytoplasm_Intensity_MaxIntensityEdge_Mito | 7.000 |
| Cytoplasm_Intensity_MaxIntensity_Mito | 6.493 |
| Cells_Intensity_MaxIntensity_Mito | 6.303 |
| Cells_Intensity_StdIntensity_AGP | 6.125 |
| Cells_Texture_AngularSecondMoment_AGP_5 | 6.037 |
| Nuclei_Intensity_StdIntensityEdge_Mito | 5.982 |
| Cells_Intensity_UpperQuartileIntensity_ER | 5.899 |
| Nuclei_Intensity_UpperQuartileIntensity_Mito | 5.847 |
| Nuclei_Intensity_MassDisplacement_RNA | 5.833 |
| Nuclei_Intensity_MedianIntensity_ER | 5.758 |
| Nuclei_Intensity_LowerQuartileIntensity_ER | 5.700 |
| Cells_Texture_AngularSecondMoment_AGP_3 | 5.674 |
| Nuclei_Intensity_MaxIntensityEdge_DNA | 5.665 |
| Nuclei_Intensity_MedianIntensity_Mito | 5.646 |
| Nuclei_Intensity_MassDisplacement_DNA | 5.578 |
| Nuclei_Texture_AngularSecondMoment_RNA_5 | 5.477 |
| Cytoplasm_Texture_AngularSecondMoment_AGP_5 | 5.365 |
| Nuclei_Intensity_MassDisplacement_Mito | 5.355 |
| Cells_Intensity_StdIntensity_Mito | 5.352 |
| Nuclei_Intensity_UpperQuartileIntensity_AGP | 5.342 |
| Nuclei_Intensity_StdIntensity_RNA | 5.340 |
| Nuclei_Intensity_UpperQuartileIntensity_ER | 5.338 |
| Cytoplasm_Intensity_StdIntensityEdge_DNA | 5.312 |
| Nuclei_Intensity_StdIntensity_DNA | 5.259 |
| Nuclei_Intensity_LowerQuartileIntensity_Mito | 5.255 |
| Nuclei_Intensity_MeanIntensity_Mito | 5.246 |
| Cytoplasm_Intensity_StdIntensity_Mito | 5.238 |
| Nuclei_Intensity_StdIntensityEdge_AGP | 5.229 |
| Nuclei_Texture_AngularSecondMoment_AGP_5 | 5.173 |
| Nuclei_Intensity_MedianIntensity_AGP | 5.145 |
| Cytoplasm_Texture_AngularSecondMoment_AGP_3 | 5.135 |
| Nuclei_Texture_AngularSecondMoment_AGP_3 | 5.047 |
| Cells_Intensity_MaxIntensity_DNA | 5.025 |
| Nuclei_Intensity_MaxIntensity_AGP | 5.011 |
| Nuclei_Intensity_MaxIntensity_DNA | 4.981 |
| Nuclei_Intensity_LowerQuartileIntensity_AGP | 4.912 |
| Nuclei_Texture_AngularSecondMoment_RNA_3 | 4.866 |
| Nuclei_Intensity_MeanIntensity_AGP | 4.844 |
| Nuclei_Intensity_MeanIntensity_ER | 4.829 |
| Cytoplasm_Intensity_StdIntensityEdge_AGP | 4.825 |
| Cells_Intensity_UpperQuartileIntensity_Mito | 4.824 |
| Cytoplasm_Intensity_StdIntensity_AGP | 4.769 |
| Nuclei_Intensity_MedianIntensity_RNA | 4.743 |
| Cells_Intensity_StdIntensityEdge_Mito | 4.628 |
| Nuclei_Intensity_UpperQuartileIntensity_RNA | 4.585 |
| Nuclei_Intensity_LowerQuartileIntensity_RNA | 4.568 |
| Cytoplasm_Intensity_StdIntensityEdge_Mito | 4.530 |
| Cells_Intensity_MaxIntensity_AGP | 4.417 |
| Cells_Intensity_MedianIntensity_DNA | 4.416 |
| Nuclei_Texture_AngularSecondMoment_Mito_5 | 4.416 |
| Cells_Texture_AngularSecondMoment_Mito_5 | 4.318 |
| Cells_Intensity_StdIntensity_RNA | 4.317 |
| Nuclei_Intensity_MeanIntensity_RNA | 4.316 |
| Cells_Intensity_StdIntensity_ER | 4.314 |
| Nuclei_Texture_AngularSecondMoment_Mito_3 | 4.273 |
| Cytoplasm_Intensity_MedianIntensity_DNA | 4.243 |
| Cells_Intensity_UpperQuartileIntensity_RNA | 4.192 |
| Cytoplasm_Intensity_StdIntensity_ER | 4.098 |
| Cells_Texture_AngularSecondMoment_Mito_3 | 4.073 |
| Nuclei_Intensity_StdIntensity_ER | 4.054 |
| Cells_Intensity_UpperQuartileIntensity_AGP | 4.044 |
| Cytoplasm_Intensity_MaxIntensity_AGP | 4.022 |
| Cells_Intensity_MaxIntensityEdge_ER | 3.972 |
| Cells_Intensity_StdIntensityEdge_ER | 3.887 |
| Cytoplasm_Intensity_UpperQuartileIntensity_DNA | 3.877 |
| Cytoplasm_Intensity_UpperQuartileIntensity_ER | 3.841 |
| Cells_Texture_AngularSecondMoment_RNA_5 | 3.809 |
| Nuclei_Intensity_MaxIntensityEdge_AGP | 3.778 |
| Nuclei_Intensity_MeanIntensityEdge_RNA | 3.776 |
| Cytoplasm_Intensity_StdIntensityEdge_RNA | 3.766 |
| Nuclei_Intensity_MeanIntensityEdge_AGP | 3.749 |
| Cells_Intensity_StdIntensityEdge_AGP | 3.746 |
| Cells_RadialDistribution_RadialCV_AGP_3of4 | 3.727 |
| Cells_Intensity_StdIntensityEdge_RNA | 3.726 |
| Cytoplasm_Intensity_MaxIntensityEdge_AGP | 3.701 |
| Cells_RadialDistribution_RadialCV_AGP_4of4 | 3.673 |
| Nuclei_Intensity_MaxIntensity_RNA | 3.630 |
| Cytoplasm_Intensity_StdIntensity_RNA | 3.623 |
| Cells_Intensity_MaxIntensity_RNA | 3.602 |
| Nuclei_Intensity_StdIntensityEdge_DNA | 3.541 |
| Cells_Intensity_MaxIntensityEdge_AGP | 3.498 |
| Cells_Intensity_MeanIntensity_ER | 3.468 |
| Cells_Texture_AngularSecondMoment_RNA_3 | 3.429 |
| Cytoplasm_Intensity_MassDisplacement_DNA | 3.398 |
| Cells_RadialDistribution_RadialCV_Mito_1of4 | 3.393 |
| Cells_RadialDistribution_RadialCV_AGP_2of4 | 3.380 |
| Cytoplasm_Intensity_StdIntensityEdge_ER | 3.352 |
| Nuclei_Intensity_UpperQuartileIntensity_DNA | 3.313 |
| Cells_Intensity_MassDisplacement_AGP | 3.306 |
| Cytoplasm_Texture_SumAverage_DNA_5 | 3.303 |
| Cells_RadialDistribution_MeanFrac_AGP_1of4 | 3.289 |
| Cells_Intensity_MaxIntensityEdge_RNA | 3.278 |
| Nuclei_Intensity_IntegratedIntensity_Mito | 3.253 |
| Cells_Intensity_StdIntensity_DNA | 3.187 |
| Cytoplasm_Texture_Contrast_DNA_3 | 3.181 |
| Cytoplasm_Texture_AngularSecondMoment_RNA_5 | 3.167 |
| Cells_RadialDistribution_RadialCV_AGP_1of4 | 3.144 |
| Cytoplasm_Texture_AngularSecondMoment_Mito_5 | 3.144 |
| Nuclei_Intensity_StdIntensityEdge_RNA | 3.123 |
| Nuclei_Intensity_MeanIntensityEdge_Mito | 3.122 |
| Cytoplasm_Texture_SumAverage_DNA_3 | 3.109 |
| Cells_RadialDistribution_MeanFrac_AGP_4of4 | -3.101 |
| Cytoplasm_Texture_Contrast_RNA_5 | 3.071 |
| Cells_RadialDistribution_MeanFrac_AGP_2of4 | 3.053 |
| Cells_Texture_Correlation_AGP_3 | 3.049 |
| Nuclei_Intensity_MassDisplacement_ER | 3.036 |
| Cytoplasm_Intensity_MeanIntensity_DNA | 3.031 |
| Cytoplasm_Texture_AngularSecondMoment_Mito_3 | 3.002 |
| Cells_Intensity_MeanIntensity_Mito | 3.001 |
| Cytoplasm_Intensity_MeanIntensity_ER | 2.943 |
| Nuclei_Texture_SumVariance_ER_5 | 2.923 |
| Cytoplasm_Texture_AngularSecondMoment_RNA_3 | 2.920 |
| Nuclei_Intensity_IntegratedIntensity_AGP | 2.891 |
| Nuclei_Intensity_MinIntensity_Mito | 2.874 |
| Cytoplasm_Intensity_MaxIntensity_RNA | 2.873 |
| Cytoplasm_Intensity_MaxIntensityEdge_ER | 2.866 |
| Nuclei_AreaShape_Solidity | -2.846 |
| Nuclei_Texture_SumVariance_AGP_5 | 2.844 |
| Cytoplasm_Intensity_MassDisplacement_AGP | 2.834 |
| Cells_RadialDistribution_MeanFrac_AGP_3of4 | 2.813 |
| Nuclei_Texture_Contrast_DNA_5 | 2.795 |
| Nuclei_Intensity_MinIntensity_AGP | 2.793 |
| Cells_Intensity_MeanIntensity_RNA | 2.766 |
| Nuclei_Intensity_MinIntensityEdge_AGP | 2.753 |
| Nuclei_Intensity_MeanIntensityEdge_ER | 2.751 |
| Cytoplasm_Intensity_MaxIntensityEdge_RNA | 2.751 |
| Cells_Texture_SumEntropy_Mito_5 | -2.744 |
| Cytoplasm_Intensity_LowerQuartileIntensity_DNA | 2.737 |
| Nuclei_Intensity_MaxIntensityEdge_RNA | 2.723 |
| Cytoplasm_Texture_DifferenceVariance_RNA_5 | 2.710 |
| Cells_Texture_SumEntropy_Mito_3 | -2.706 |
| Cytoplasm_Texture_Contrast_DNA_5 | 2.705 |
| Nuclei_Intensity_MinIntensityEdge_Mito | 2.669 |
| Nuclei_Intensity_IntegratedIntensity_RNA | 2.663 |
| Nuclei_Neighbors_PercentTouching_1 | 2.654 |
| Cells_Intensity_MedianIntensity_AGP | 2.650 |
| Cytoplasm_Intensity_UpperQuartileIntensity_RNA | 2.646 |
| Cytoplasm_Texture_Contrast_RNA_3 | 2.643 |
| Cytoplasm_Texture_Gabor_Mito_3 | 2.639 |
| Nuclei_Intensity_IntegratedIntensityEdge_AGP | 2.637 |
| Cells_RadialDistribution_MeanFrac_Mito_1of4 | 2.626 |
| Cytoplasm_Texture_Gabor_ER_3 | 2.619 |
| Cells_Texture_Gabor_RNA_3 | 2.615 |
| Cells_Intensity_MeanIntensity_AGP | 2.592 |
| Nuclei_Intensity_MinIntensity_ER | 2.535 |
| Cytoplasm_Texture_Contrast_ER_5 | 2.525 |
| Nuclei_Texture_SumVariance_AGP_3 | 2.515 |
| Cells_Intensity_MeanIntensityEdge_DNA | 2.498 |
| Nuclei_Intensity_IntegratedIntensityEdge_RNA | 2.493 |
| Cytoplasm_Intensity_UpperQuartileIntensity_AGP | 2.492 |
| Cytoplasm_Texture_Gabor_AGP_3 | 2.491 |
| Cells_Texture_SumVariance_AGP_5 | 2.486 |
| Nuclei_Intensity_IntegratedIntensityEdge_Mito | 2.480 |
| Cells_Texture_Correlation_DNA_3 | -2.476 |
| Nuclei_Intensity_IntegratedIntensity_ER | 2.472 |
| Nuclei_Texture_SumVariance_ER_3 | 2.467 |
| Cells_Texture_InfoMeas2_Mito_3 | -2.463 |
| Cells_Texture_SumVariance_AGP_3 | 2.454 |
| Cytoplasm_Texture_SumVariance_DNA_5 | 2.445 |
| Cells_Intensity_StdIntensityEdge_DNA | 2.441 |
| Cells_RadialDistribution_RadialCV_Mito_2of4 | 2.411 |
| Nuclei_Intensity_MinIntensity_RNA | 2.391 |
| Cells_Intensity_MaxIntensityEdge_DNA | 2.384 |
| Cells_Intensity_MedianIntensity_ER | 2.379 |
| Cells_Intensity_MaxIntensity_ER | 2.369 |
| Nuclei_Intensity_MinIntensityEdge_RNA | 2.369 |
| Cells_Texture_DifferenceVariance_RNA_5 | 2.360 |
| Cytoplasm_Intensity_MaxIntensity_ER | 2.355 |
| Cytoplasm_Texture_InfoMeas2_Mito_3 | -2.344 |
| Cytoplasm_Texture_Gabor_AGP_5 | 2.337 |
| Cytoplasm_Texture_Gabor_RNA_3 | 2.331 |
| Nuclei_Texture_InfoMeas1_AGP_5 | -2.329 |
| Cells_RadialDistribution_RadialCV_RNA_4of4 | 2.324 |
| Nuclei_AreaShape_Area | 2.318 |
| Cytoplasm_Texture_Gabor_ER_5 | 2.314 |
| Cells_Texture_SumEntropy_AGP_3 | -2.293 |
| Cells_Texture_Entropy_Mito_5 | -2.273 |
| Cytoplasm_Texture_DifferenceVariance_ER_5 | 2.272 |
| Cytoplasm_Texture_Contrast_ER_3 | 2.257 |
| Nuclei_Intensity_StdIntensityEdge_ER | 2.241 |
| Cells_Texture_Entropy_Mito_3 | -2.240 |
| Nuclei_AreaShape_Perimeter | 2.216 |
| Cytoplasm_Texture_SumVariance_DNA_3 | 2.215 |
| Nuclei_Texture_AngularSecondMoment_ER_5 | 2.212 |
| Cells_RadialDistribution_RadialCV_Mito_4of4 | 2.189 |
| Cytoplasm_Texture_Gabor_Mito_5 | 2.182 |
| Nuclei_Intensity_IntegratedIntensity_DNA | 2.175 |
| Nuclei_Intensity_MeanIntensity_DNA | 2.170 |
| Nuclei_Intensity_IntegratedIntensityEdge_DNA | 2.162 |
| Cells_Texture_Gabor_Mito_3 | 2.158 |
| Nuclei_Intensity_MinIntensityEdge_ER | 2.157 |
| Cells_RadialDistribution_RadialCV_Mito_3of4 | 2.156 |
| Cytoplasm_Texture_DifferenceVariance_RNA_3 | 2.150 |
| Cells_Intensity_MedianIntensity_Mito | 2.139 |
| Nuclei_Intensity_MaxIntensity_ER | 2.134 |
| Cytoplasm_Intensity_MedianIntensity_ER | 2.126 |
| Cells_Texture_SumEntropy_AGP_5 | -2.104 |
| Nuclei_Texture_AngularSecondMoment_ER_3 | 2.089 |
| Cells_Texture_SumEntropy_RNA_5 | -2.088 |
| Cytoplasm_Texture_SumEntropy_Mito_5 | -2.086 |
| Cells_Texture_Correlation_AGP_5 | 2.081 |
| Cytoplasm_Intensity_UpperQuartileIntensity_Mito | 2.073 |
| Cytoplasm_Texture_SumEntropy_Mito_3 | -2.066 |
| Cells_RadialDistribution_MeanFrac_ER_1of4 | 2.059 |
| Cells_Texture_Gabor_DNA_3 | 2.058 |
| Cells_Texture_SumEntropy_RNA_3 | -2.057 |
| Cells_Texture_Contrast_RNA_5 | 2.055 |
| Cytoplasm_Texture_Gabor_RNA_5 | 2.025 |
| Cytoplasm_Intensity_MeanIntensity_Mito | 2.008 |
| Nuclei_Texture_SumVariance_Mito_5 | 2.007 |
features_statistics %>% write_csv("feature_statistics.csv")Plot histograms of features and save as PNGs
if(!dir.exists("feature_histograms")) {
dir.create("feature_histograms")
}
feature_names <- names(sampled_objects) %>%
str_subset("Cells_|Cytoplasm_|Nuclei_")
for (feature_name in feature_names) {
g <- ggplot(sampled_objects, aes_string(feature_name)) +
geom_histogram(bins = 50)
ggsave(plot = g,
filename = sprintf("feature_histograms/%s.png", feature_name),
width = 5, height = 5)
}