update example

DESCRIPTION

@@ -3,7 +3,7 @@ Title: Haplotype-Aware CNV Analysis from scRNA-Seq
 URL: https://github.com/kharchenkolab/numbat
 Version: 1.1.0
 Authors@R: c(person("Teng","Gao", email="[email protected]", role=c("cre", "aut")), person("Hirak", "Sarkar", email="[email protected]", role="aut"), person("Evan", "Biederstedt", email="[email protected]", role="aut"), person("Peter", "Kharchenko", email = "[email protected]", role = "aut"))
-Description: A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nat Biotechnol (2022) <doi:10.1038/s41587-022-01468-y>.
+Description: A computational method that infers copy number variations (CNVs) in cancer scRNA-seq data and reconstructs the tumor phylogeny. 'numbat' integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. 'numbat' can be used to: 1. detect allele-specific copy number variations from single-cells; 2. differentiate tumor versus normal cells in the tumor microenvironment; 3. infer the clonal architecture and evolutionary history of profiled tumors. 'numbat' does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). Additional examples and documentations are available at <https://kharchenkolab.github.io/numbat/>. For details on the method please see Gao et al. Nature Biotechnology (2022) <doi:10.1038/s41587-022-01468-y>.
 License: MIT + file LICENSE
 Encoding: UTF-8
 LazyData: true

R/utils.R

@@ -472,7 +472,7 @@ switch_prob_cm = function(d, nu = 1, min_p = 1e-10) {
 #' @param phasing logical Whether to use phasing information (internal use only)
 #' @param verbose logical Verbosity
 #' @examples
-#' bulk_analyzed = analyze_bulk(bulk_example, t = 1e-5)
+#' bulk_analyzed = analyze_bulk(bulk_example, t = 1e-5, find_diploid = FALSE, retest = FALSE)
 #' @return a pseudobulk profile dataframe with called CNV information
 #' @export
 analyze_bulk = function(