top_integrations {ISAnalytics} | R Documentation |
The input data frame will be sorted by the highest values in
the columns specified and the top n rows will be returned as output.
The user can choose to keep additional columns in the output
by passing a vector of column names or passing 2 "shortcuts":
keep = "everything"
keeps all columns in the original data frame
keep = "nothing"
only keeps the mandatory columns
(mandatory_IS_vars()
) plus the columns in the columns
parameter.
top_integrations( x, n = 20, columns = "fragmentEstimate_sum_RelAbundance", keep = "everything", key = NULL )
x |
An integration matrix (data frame containing
|
n |
How many integrations should be sliced (in total or for each group)? Must be numeric or integer and greater than 0 |
columns |
Columns to use for the sorting. If more than a column is supplied primary ordering is done on the first column, secondary ordering on all other columns |
keep |
Names of the columns to keep besides |
key |
Either |
Either a data frame with at most n rows or a data frames with at most n*(number of groups) rows.
Other Analysis functions:
CIS_grubbs()
,
comparison_matrix()
,
compute_abundance()
,
cumulative_count_union()
,
cumulative_is()
,
is_sharing()
,
purity_filter()
,
sample_statistics()
,
separate_quant_matrices()
,
threshold_filter()
smpl <- tibble::tibble( chr = c("1", "2", "3", "4", "5", "6"), integration_locus = c(14536, 14544, 14512, 14236, 14522, 14566), strand = c("+", "+", "-", "+", "-", "+"), CompleteAmplificationID = c("ID1", "ID2", "ID1", "ID1", "ID3", "ID2"), Value = c(3, 10, 40, 2, 15, 150), Value2 = c(456, 87, 87, 9, 64, 96), Value3 = c("a", "b", "c", "d", "e", "f") ) top <- top_integrations(smpl, n = 3, columns = c("Value", "Value2"), keep = "nothing" ) top_key <- top_integrations(smpl, n = 3, columns = "Value", keep = "Value2", key = "CompleteAmplificationID" )