HiCDCPlus_chr: HiCDCPlus_chr

In mervesa/HiCDCPlus: Hi-C Direct Caller Plus

HiCDCPlus_chr

Description

This function finds significant interactions in a HiC-DC readable matrix restricted to a single chromosome and expresses statistical significance of counts through the following: 'pvalue': significance P-value, 'qvalue': FDR corrected P-value, mu': expected counts, 'sdev': modeled standard deviation of expected counts.

Usage

HiCDCPlus_chr(
  gi,
  covariates = NULL,
  distance_type = "spline",
  model_distribution = "nb",
  binned = TRUE,
  df = 6,
  Dmin = 0,
  Dmax = 2e+06,
  ssize = 0.01,
  splineknotting = "uniform",
  model_filepath = NULL
)

Arguments

gi	Instance of a single chromosome GenomicInteractions object containing intra-chromosomal interaction information (minimally containing counts and genomic distance).
covariates	covariates to be considered in addition to genomic distance D. Defaults to all covariates besides 'D','counts','mu','sdev',pvalue','qvalue' in mcols(gi)
distance_type	distance covariate form: 'spline' or 'log'. Defaults to 'spline'.
model_distribution	'nb' uses a Negative Binomial model, 'nb_vardisp' uses a Negative Binomial model with a distance specific dispersion parameter inferred from the data, 'nb_hurdle' uses the legacy HiC-DC model.
binned	TRUE if uniformly binned or FALSE if binned by restriction enzyme fragment cut sites.
df	degrees of freedom for the genomic distance spline function if distance_type='spline'. Defaults to 6, which corresponds to a cubic spline as explained in Carty et al. (2017)
Dmin	minimum distance (included) to check for significant interactions, defaults to 0
Dmax	maximum distance (included) to check for significant interactions, defaults to 2e6 or maximum in the data; whichever is minimum.
ssize	Distance stratified sampling size. Can decrease for large chromosomes. Increase recommended if model fails to converge. Defaults to 0.01.
splineknotting	Spline knotting strategy. Either "uniform", uniformly spaced in distance, or placed based on distance distribution of counts "count-based" (i.e., more closely spaced where counts are more dense).
model_filepath	Outputs fitted HiC-DC model object as an .rds file with chromosome name indicatd on it. Defaults to NULL (no output).

Value

A valid gi instance with additional mcols(.): pvalue': significance P-value, 'qvalue': FDR corrected P-value, mu': expected counts, 'sdev': modeled standard deviation of expected counts.

Examples

gi_list<-generate_binned_gi_list(50e3,chrs='chr22')
gi_list<-add_hic_counts(gi_list,
hic_path<-system.file("extdata", "GSE63525_HMEC_combined_example.hic",
package = "HiCDCPlus"))
gi<-HiCDCPlus_chr(gi_list[[1]])

mervesa/HiCDCPlus documentation built on June 8, 2022, 3:43 a.m.