{pangenome} R# Documentation

pangenome

require(GCModeller);

#' pan-genome analysis toolkit
imports "pangenome" from "comparative_toolkit";

pan-genome analysis toolkit

.NET clr type export
pangenome: PanGenomeResult

分析结果存储结构（修改为支持多基因组）
ortho_groups: UnionFind

并查集辅助类，用于高效处理基因家族的聚类


.NET clr function exports
as.data.frame.svtable SVTable:
as.data.frame.pavtable PAVTable:
as.data.frame.genomestatrow GenomeStatRow:

泛基因组报告页面所使用的 JSON 数据模型。
as.data.frame.pcascatterdataset PCAScatterDataset:

PAV矩阵的PCA分析结果数据（用于三维散点图）
as.data.frame.genomeentropydataset GenomeEntropyDataset:

基因组级别的三维散点图数据（均衡度熵 / 特有基因占比 / 核心基因占比）
as.data.frame.svdomainentropydataset SVDomainEntropyDataset:

SV 结构变异的信息熵散点图与 KMeans 聚类结果
build_context

Load the pangenome analysis context
multiple_genome_alignment
family_groups
analysis

run pan-genome analysis
set_ortho_group

set orthology group for make gene family
source_id

set species name to the genome gff3 context model
scatter_set
report_html

generates the html report text for the pan-genome analysis result
genetic_distance
pav_matrix
sv_copy_number_matrix

export the SV CopyNumber matrix of the structural variations (rows are gene families which have at least one SV event, columns are genomes)
sv_median_matrix

export the SV Median matrix of the structural variations (rows are gene families which have at least one SV event, columns are genomes)
category_percent_matrix

export the gene family distribution percent matrix (rows are genomes plus one average row, columns are the four family categories)
sv_entropy

get the SV structural variation information entropy scatter data and the kmeans clustering result
curve_data
sv_table

export structure variant result table
pav_table
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