make_pppfunction to create marked point patterns.
parse_phenotypesmakes nicer names for expression-based phenotypes.
phenotype_columnsin support of akoyabio/phenoptrReports#36.
read_cell_datamore robust against data with comma as the decimal separator.
count_touching_cells_fastfor phenoptrReports spatial map viewer.
phenoptrReportsto avoid installation pain.
phenoptrReportsis still needed to build the vignettes and to run a few of the examples.
validate_phenotype_definitionssupport expressions in phenotype definitions.
density_bandsto work with cell seg data in microns with slide origin (#10).
New feature (and breaking change):
find_nearest_distancenow create columns containing the Cell ID of the nearest cell, as well as the columns with the actual distance. This column can be used to find the locations of nearest cells and to find mutual nearest neighbors. The “Computing inter-cell distances” tutorial shows some uses of this data.
read_cell_seg_datarecognizes and correctly reads inForm data which uses comma as the decimal separator (#8).
count_touching_cellsignores phenotype pairs of self to self with a warning because the touching algorithm does not handle this case (#7).
Failed with error: ‘there is no package called ‘rtree’’message that
count_within_detailto give per-cell counts.
get_field_infoto work with the standard (CRAN)
count_withinand related functions return
within_meanwhen there are no
fromcells (rather than a mean of 0).
spatial_distribution_reportvignette and example to use
phenoptrExamples, which contains the required component data file (#3).
count_touching_cellswhen there is exactly one touching cell pair (#4)
count_within_manyin support of phenoptrReports.
count_withindoes not count self when ‘from’ and ‘to’ phenotypes are the same.
field_column(moved from phenoptrReports) and
compute_all_nearest_distanceto recognize “Annotation ID” as a field name.
spatial_distribution_reportto work with consolidated data from
square mmto match inForm output.
spatial_distribution_reportworks correctly with cell seg data in microns. To do so, it requires a component data file for the target field. Image dimensions are taken from that file.
count_touching_cellsworks correctly when cell seg data is in microns.
count_withinwon’t complain if the data doesn’t have a
parse_phenotypesfunction simplifies creation of selectors for
select_rowsrecognizes the column format of phenotype-per-marker data.
NAselector as “select all”. This is helpful in lists of selectors.
read_cell_seg_dataattempts to skip microns conversion if it was already done.
count_touching_cellsto work with two-pixel-wide membrane map. #8
count_within_batchto work with cell seg files which don’t have
density_bandsto estimate cell density at a distance from a boundary.
subset_distance_matrixin a backwards-incompatible way. This was done to put the
csdparameter first, matching other functions with a
spatial_distribution_reportcreates an HTML report showing the location and nearest-neighbor relations of cells in a single field.
count_touching_cellsuses morphological analysis of nuclear and membrane segmentation maps to find touching cells of paired phenotypes.
read_componentsreads component image files.
count_within_batchcount the number of
fromcells having a
tocell within a given radius.
list_cell_seg_fileslists all cell seg data files in a folder.
NAvalues in distance columns of cell seg tables. Previously
NAvalues could cause the column to be read as character data.