cumulative_is {ISAnalytics} | R Documentation |
Given an input integration matrix that can be grouped over time,
this function adds integrations in groups assuming that
if an integration is observed at time point "t" then it is also observed in
time point "t+1".
cumulative_is( x, key = c("SubjectID", "CellMarker", "Tissue", "TimePoint"), timepoint_col = "TimePoint", include_tp_zero = FALSE, keep_og_is = TRUE, expand = FALSE )
x |
An integration matrix, ideally aggregated via
|
key |
The aggregation key used |
timepoint_col |
The name of the time point column |
include_tp_zero |
Should time point 0 be included? |
keep_og_is |
Keep original set of integrations as a separate column? |
expand |
If |
A data frame
Other Analysis functions:
CIS_grubbs()
,
comparison_matrix()
,
compute_abundance()
,
cumulative_count_union()
,
is_sharing()
,
iss_source()
,
purity_filter()
,
sample_statistics()
,
separate_quant_matrices()
,
threshold_filter()
,
top_integrations()
data("integration_matrices", package = "ISAnalytics") data("association_file", package = "ISAnalytics") aggreg <- aggregate_values_by_key( x = integration_matrices, association_file = association_file, value_cols = c("seqCount", "fragmentEstimate") ) cumulated_is <- cumulative_is(aggreg) cumulated_is