ConfigSignal.files: QcConfigSignal

In jrboyd/seqtsne: Application of t-sne to NGS Genomic Signal Profiles

QcConfigSignal

Description

QcConfigSignal

QcConfigSignal

QcConfigSignal null placeholder

QcConfigSignal.files

QcConfigSignal.save_config

Usage

ConfigSignal.files(
  file_paths,
  file_paths.input = character(),
  run_separately = TRUE,
  sample_names = NULL,
  sample_names.split = NULL,
  group_names = NULL,
  group_name.input = "input",
  group_colors = NULL,
  view_size = getOption("SQC_VIEW_SIZE", 3000),
  window_size = getOption("SQC_WINDOW_SIZE", 200),
  read_mode = NULL,
  cluster_value = NULL,
  linearQuantile_cutoff = 0.98,
  sort_value = NULL,
  plot_value = NULL,
  sort_method = c("hclust", "sort")[2],
  center_signal_at_max = FALSE,
  flip_signal_mode = flip_signal_modes$none,
  n_clusters = 6
)

Arguments

file_paths	character paths to files
group_names	vector of group names to assign from according to groups
group_colors	vector of colors to use per group
view_size	view size in bp to apply. Defaults to 3000.
window_size	The window size used when fetching signal. Lower values increase resolution but also RAM usage. Default is 200 bp.
read_mode	Read mode of signal data, one of bam_SE, bam_PE, or bigwig. Use SQC_READ_MODES$.
cluster_value	Value in SQC_SIGNAL_VALUES$ to use for clustering. RPM values are not valid if read_mode is "bigwig".
linearQuantile_cutoff	Quantile to use for linearQuantile normalization procedure. Values above this cutoff are treated as outliers.
sort_value	Value in SQC_SIGNAL_VALUES$ to use for sorting. RPM values are not valid if read_mode is "bigwig".
plot_value	Value in SQC_SIGNAL_VALUES$ to represent in plots. RPM values are not valid if read_mode is "bigwig".
sort_method	One of two available method to use when sorting within clusters. If "hclust", hierarchical clustering is applied. If the default of "sort", regions are sorting by decreasing signal.
center_signal_at_max	If TRUE, signal is centered at local maxima prior to any clustering. The default is FALSE. See details for explanation or interaction with assessment features.
flip_signal_mode	Value is SQC_FLIP_SIGNAL_MODES$. If not "none" (Default) signal profiles are flipped so that highest signal is on one side or the other. See details for explanation or interaction with assessment features.
n_clusters	The number of k-means clusters for the heatmap. Since center_signal_at_max and flip_signal_mode have the potential to modify the assessment regions based on signal run groups, the modified assessment feature set is store in signal_data for each run group. They can be accessed like this: sqc$signal_data$FEATURE_NAME$SIGNAL_NAME$query_gr

Value

A QcConfigSignal object

A null/empty QcConfigSignal object

A QcConfigSignal object

a QcConfigSignal object

A list of 2 items prof_dt and query_gr. prof_dt is a tidy data.table of signal profiles. query_gr is a GRanges that may have been modified from input query_gr if signal profiles are flipped or centered according to center_signal_at_max or flip_signal_mode in the signal config.

Invisibly returns path to saved config file.

Slots

view_size

read_mode

fetch_options

cluster_value

linearQuantile_cutoff

sort_value

sort_method

plot_value

heatmap_limit_values

lineplot_free_limits

center_signal_at_max

flip_signal_mode

n_clusters

Examples

bam_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bam_config.csv")
bam_config_df = .parse_config_body(bam_config_file)
sig_conf = QcConfigSignal(bam_config_df)

bigwig_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bigwig_config.csv")
bigwig_config_df = .parse_config_body(bigwig_config_file)
sig_conf.bw = QcConfigSignal(bigwig_config_df)
QcConfigSignal.null()
bam_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bam_config.csv")
QcConfigSignal.parse(bam_config_file)

bigwig_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bigwig_config.csv")
QcConfigSignal.parse(bigwig_config_file)
bam_files = dir(system.file(package = "ssvQC", "extdata"), pattern = "CTCF.+bam$", full.names = TRUE)
object = QcConfigSignal.files(bam_files)
plot(object)

object2 = QcConfigSignal.files(bam_files,
  sample_names = c("MCF10A_CTCF", "MCF10AT1_CTCF", "MCF10CA1a_CTCF"), 
  group_names = c("10A", "AT1", "CA1"),
  group_colors = c("firebrick", "slategray2", "forestgreen")
)
plot(object2)
bam_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bam_config.csv")
qc_signal = QcConfigSignal.parse(bam_config_file)

feature_config_file = system.file(package = "ssvQC", "extdata/ssvQC_peak_config.csv")
qc_features = QcConfigFeatures.parse(feature_config_file)
query_gr = qc_features$assessment_features
fetch_signal_at_features(qc_signal, query_gr)
bam_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bam_config.csv")
bam_config = QcConfigSignal.parse(bam_config_file)
#QcConfigSignal.save_config(bam_config, "bam_config.csv")

bigwig_config_file = system.file(package = "ssvQC", "extdata/ssvQC_bigwig_config.csv")
bigwig_config = QcConfigSignal.parse(bigwig_config_file)
#QcConfigSignal.save_config(bigwig_config, "bigwig_config.csv")

jrboyd/seqtsne documentation built on Nov. 5, 2022, 6:37 a.m.