starfish_feature: starfish_feature

In yanglab-computationalgenomics/Starfish: Detecting connected CGR regions and inferring mechanisms from structural variation and copy number data

starfish_feature

Description

This function loads "connected" CGR regions and complex SVs reported by starfish_link, then combines CNV calls and sample gender to construct a CGR region vs. feature matrix for downstream clustering and classification.

Usage

starfish_feature(
  cgr,
  complex_sv,
  cnv_file,
  gender_file,
  prefix = "",
  genome_v = "hg19",
  cnv_factor = "auto",
  arm_del_rm = TRUE
)

Arguments

cgr	"connected" CGR regions, which is the output of starfish_link_out$starfish_call
complex_sv	complex SVs, which is the output from starfish_link_out$interleave_tra_complex_sv
cnv_file	a CNV dataframe with 5 columns: "chromosome","start","end","total_cn", and "sample". "total_cn" should contain absolute copy numbers
gender_file	a sample table with 2 columns: "sample" and "gender". Gender could be "Female, "female","F","f","Male","male","M", or "m". If the gender is unknown, any other characters could be given, such as "unknown", and the gender will be inferred by the CN baseline of chromosome X
prefix	the prefix for all intermediate files, default is none
genome_v	which genome assembly was used to call SV and CNV. It should be "hg19" or "hg38", default is "hg19"
cnv_factor	the CN fluctuation beyond or below baseline to identify loss and gain fragments for samples with decimal CN, default is "auto", or users can provide a value between 0 and 1
arm_del_rm	the logical value of removing arm level deletion or not, default is TRUE

Value

a list of files: $cluster_feature is the CGR region vs. feature matrix,$cnv_baseline is the cnv file with baseline annotation

yanglab-computationalgenomics/Starfish documentation built on July 27, 2022, 10:26 a.m.