<?xml version="1.0" encoding="utf-8" ?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom" xmlns:r="https://r-universe.dev"><channel><title>zying106.r-universe.dev</title><link>https://zying106.r-universe.dev</link><description>Recent package updates in zying106</description><generator>R-universe</generator><image><url>https://github.com/zying106.png</url><title>R packages by zying106</title><link>https://zying106.r-universe.dev</link></image><lastBuildDate>Fri, 04 Sep 2026 00:02:14 GMT</lastBuildDate><item><title>[biocstaging] epiPortrait 0.99.3</title><author>12207129@zju.edu.cn (Ying ZHANG)</author><description>Provides methods for replicate-aware quantitative
phenotyping and comparison of epigenomic domains from
normalized continuous signal tracks and per-sample native
peak/domain calls (histone-mark ChIP-seq / CUT&amp;Tag as the
primary use case; also applicable to ATAC-seq-derived domains).
It characterizes each shared genomic domain by integrated
signal magnitude (Intensity), sample-specific native peak
breadth geometry, and continuous within-domain signal
architecture (SignalDispersion). Replicate-level evidence is
retained and aggregated with specified support rules, enabling
condition-specific classification of Intensity-Super,
Breadth-Super, Dual-Super, Typical, or Uncertain domain states
without using the consensus-domain width as the breadth caller.
The package further supports condition transitions, continuous
domain-width remodeling, signal quality control, genome-aware
domain annotation with a three-level export (per-domain
summary, per-domain-gene pair, and raw relationship detail),
optional BEDPE contact evidence, expression-aware
candidate-gene prioritization, differential domain analysis on
continuous BigWig signal using limma, and result visualization.</description><link>https://github.com/r-universe/biocstaging/actions/runs/37194221942</link><pubDate>Fri, 04 Sep 2026 00:02:14 GMT</pubDate><r:package>epiPortrait</r:package><r:version>0.99.3</r:version><r:status>success</r:status><r:repository>https://biocstaging.r-universe.dev</r:repository><r:upstream>https://github.com/BiocStaging/epiPortrait</r:upstream><r:article><r:source>epiPortrait.Rmd</r:source><r:filename>epiPortrait.html</r:filename><r:title>From Signal Tracks to Replicate-Supported Epigenomic Domain Phenotypes</r:title><r:created>2026-05-13 01:17:37</r:created><r:modified>2026-09-02 14:07:22</r:modified></r:article></item></channel></rss>