Package index • dlptools

All functions

ASCN_COLORS: colors for signals results of allele balances
ASCN_PHASE_COLORS: ASCN phase colors
CNV_COLOURS: standard colors used in dlp plots
DEFAULT_CONTINUOUS_COLOR_RANGE: min, median, max for a continuous color range
STATE_COLORS: alias of standard colors used in dlp plots
add_centromere_locations(): add centromere information to reads by chromosome
add_chromosome_length(): add chromosome lengths to a cn dataframe
add_missing_bins_for_cells(): Add back chr, start, end of bins missing from cells
add_telomere_positions(): add telomere positions to a CN df
add_tip_ancestors_to_df(): add parent node labels to a dataframe of cell ids with states
add_wu_change_shape(): see dlptools::extract_wu_features
add_wu_seg_state_bins(): see dlptools::extract_wu_features
basic_tile_plot(): create a tile plot of read state calls.
bme_vec(): picks beginning, middle, and end of a vector to handle when vectors that are too long are passed
build_left_annot(): builds the left-side annotations of the cells
cell_cn_profile(): plot copy number profile plot of a cell.
cell_id_order_as_plotted(): grab cell ids in the order that they are plotted
cell_states_to_strings(): collapse cell states to strings
characterize_foreground_allele_state_changes(): mark types of allele specific foreground state changes
characterize_foreground_total_state_changes(): mark the types of change between a parent node state and the tip.
check_args(): confirms arguments are compatible for the plotting wrapper
check_if_state_columns_are_valid(): internal check for using the characterization function
check_or_fetch_clone_palette(): confirm pallete given has enough colors or generate one
check_the_vibe(): just a silly alias.
chip_plot(): Plot metrics across the chip
chr_name_check(): internal for checking the names of chromosome columns in a dataframe.
compare_two_cells(): internal workhorse of pairwise_bin_difference function
compute_tip_sibling_distances(): measure string distances between sibling tips
confirm_cols_present(): confirm if columns exist in dataframe
convert_dists_to_pairwise(): convert cell distances to a pairwise matrix
convert_long_reads_to_wide(): convert long format reads to wide format
count_default_process_feats(): wrapper around classic process based features
count_oscillations(): count the length of oscillating chains of CN.
create_chrom_arm_intervals(): create a list of intervals spanning chromosome arms
create_chrom_window_intervals(): break a chromosome up into intervals of a defined window size
create_chromosome_column_fct(): create a sorted factor vector of chromosomes
create_expected_bins(): create bins of given size for a genome
cust_mode(): find most common element in a vector
cut_categories_and_count(): count values that map to given categories
decide_if_oscillation(): decide if a 3 segment chain counts as an oscillation
does_palette_cover_plot_vals(): internal to confirm color choice was ok
expand_length_to_bins(): For a given length, create bins of a given size
extract_bp_per_arm(): convenience function to extracting breakpoints per chromosome arm
extract_bp_per_window(): convenience function to extracting breakpoints per window size
extract_breakpoints(): extracting counts of breakpoints per user-defined scope
extract_changepoint(): extract the CN change between adjacent segments.
extract_cn(): extract copy state values.
extract_oscillations(): extract the legths of chains of osscilating copy number segments
extract_ploidy_cn_feature(): Count changes of state relative to ploidy.
extract_segment_position_feature(): count the segment-span-on-chromosome event types.
extract_segment_sizes(): sizes of the segments
extract_sigminer_wang_features(): thin wrapper around sigminer feature tally
extract_wu_features(): Extract CN features following Wu et al
factor_column_mixedsort(): naturally sort a column from a dataframe.
fetch_continuous_color_ramp(): internal function for setting up heatmap continuous range colors chooses defaults, unless overwritten by user.
fetch_heatmap_color_palette(): grab colors for various hm possibilities.
fill_state_from_neighbours(): infer missing data using the upstream neighbour bin
find_outlier_cells(): Find outlier cells using a beta distribution
format_sitka_tree(): clean tree tip labels and drop any locus tips from sitka trees
format_states_for_hm(): format states for plotting in a heatmap
gc_plot(): visualize GC correction for a cell
generate_hm_image(): generate a ComplexHeatmap::Heatmap image, either to console or file.
generate_state_hm(): creates a complex heatmap of a given matrix of states.
get_clone_id_label_positions(): get a row number of where to place each clone label.
get_clone_members(): create list of list of cell_ids that belong to each clone id.
get_column_metrics(): get plotted values bounds
get_dist_to_sibs(): get distance of states to siblings for a tree tip
get_package_file_path(): retrieve file path to package data files
get_tip_parents(): resolve who the immediate parent nodes are for each tip.
get_tips_that_avoid_redundant_comps(): get tips labels that will avoid duplicate sibling comparisons
import_annotations_df(): read an annotations file (t(c)sv)
import_clones(): read a clones t(c)sv file
import_dlp_files(): generic function to import dlp files
import_telos_file(): load UCSC gap files for telomeres
import_tree(): read a tree from a file in newick format
is_chr_used_in_chroms(): detect if chromosomes labels include "chr"
is_not_numeric_lacks_order(): confirms a vector is not numeric and is unorderd
library_from_cell(): extract library ID from the typically formatted cell_ids
load_chrom_info_file(): loading UCSC chromosome length files
load_mask_file(): internal to control mask file loading.
load_ucsc_centromeres(): load and prep default centromerefiles from UCSC
make_cellid_matrix(): pivot a cell_id dataframe to a wide matrix.
make_clone_palette(): generate a color palette for clone labels
make_corrupt_tree_heatmap(): create a complex heatmap object with a tree.
make_tree_plot_obj(): create a ggplot object of a phylogenetic tree
map_states_to_letters(): convert a vector of states to letters
mark_bins_overlapping_centromeres(): add boolean if bin overlaps with a centromere.
mark_cn_relative_to_ploidy(): Mark if CN states are gains or losses relative to cell ploidy
mark_mask_regions(): add a mask column to a dataframe
mark_segs_chromosome_span(): label CN segments based on relative chromosomal positions
medicc_profiles_to_foreground(): medicc profiles files to foreground assessment
mode_ploidy(): find the mode CN per chromosome, then mode across the chromosomes
pairwise_bin_difference(): metric of pairwise differences between two cells.
plot_bg_state_highlight(): generate a plot of just the background states, making the foreground white.
plot_fg_state_highlight(): generate a plot of just the foreground states, making the background white.
plot_heatmap_of_tip_changes(): make a plot of just the foreground events
plot_nnd_outlier_cells(): visualize cell nearest neighbour distance values
plot_state_hm(): main hm building function
pull_chr_from_col_name(): extract chromosome name from a bin name (chr_start_end)
pull_info_from_cell_id(): generic extractor of info contained in cell ids
read_medicc_profiles(): ingest a medicc profiles file
read_medicc_tree(): read medicc tree to phylo object.
reads_to_segs(): convert reads table to segments table
rle_states(): convert states to run length encoding
sample_from_cell(): extract sample ID from the typically formatted cell_ids
segs_to_reads(): split segments into bins of a requested size.
sort_df_by_cell_order(): sort a table given a vector of cell_ids
weighted_ploidy(): calculate sample ploidy with a weighted CN mean