Iris Spatial Features

How to install in R:

#install devtools from cran
install.packages('devtools')
 
#load devtools and install the package
library(devtools)
install_github("gusef/IrisSpatialFeatures")

How to use the package:

There is a vignette included in the 'vignette' directory of the package.

Common task walkthroughs

1. Read in all samples

Uses the default mask to define the ROI if one is included

data <- read_raw('Test ROI')

2. Read in all samples and a custom ROI mask

Assumes every frame of every sample has *_ROI.tif with a defined area.

data <- read_raw('Test ROI',customMask="ROI")

3. Extract counts/mm2 from the data for samples and individual frames

sample_count_density <- counts_per_mm2_sample_data_frame(data)
frame_count_density <- counts_per_mm2_data_frame(data)

4. Extract raw counts from the data for samples and individual frames

sample_count <- counts_sample_data_frame(data)
frame_count <- counts_data_frame(data)

5. Analyze counts in samples with a tumor and margin defined

Assumes each sample and frame has *_Tumor.tif and *_Invasive_Margin.tif with defined areas

data <- read_raw('Test tumor IM mixed case copy',
                 readTumorAndMarginMasks=TRUE)
tumor <- extract_ROI(data,'tumor')
stroma <- extract_ROI(data,'stroma')
invasive_margin <- extract_ROI(data,'invasive_margin')

tumor_count_density <- counts_per_mm2_sample_data_frame(tumor)
stroma_count_density <- counts_per_mm2_sample_data_frame(stroma)
invasive_margin_count_density <- counts_per_mm2_sample_data_frame(invasive_margin)

6. Analyze the complete tumor in samples with a tumor and margin defined

Only requires *_Tumor.tif for each frame. We use it as a custom mask and don't concern ourselves with the Invasive Margine files.

tumor <- read_raw('Test tumor IM mixed case copy', 
                 customMask='Tumor')
tumor_count_density <- counts_per_mm2_sample_data_frame(tumor)