<?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>sunpast.r-universe.dev</title><link>https://sunpast.r-universe.dev</link><description>Recent package updates in sunpast</description><generator>R-universe</generator><image><url>https://github.com/sunpast.png</url><title>R packages by sunpast</title><link>https://sunpast.r-universe.dev</link></image><lastBuildDate>Sat, 19 Sep 2026 09:52:18 GMT</lastBuildDate><item><title>[wanglabcsu] PERCEPTIONx 0.3.0</title><author>jiading682@qq.com (Jia Ding)</author><description>An R implementation of the PERCEPTION approach (Sinha et
al., 2024) for predicting personalized drug response from
single-cell tumor transcriptomics. It trains drug-response
models on large-scale cell-line screens, predicts sensitivity
at clone and patient level, and ships an interactive
visualization suite plus a Shiny web application.</description><link>https://github.com/r-universe/wanglabcsu/actions/runs/39243291079</link><pubDate>Sat, 19 Sep 2026 09:52:18 GMT</pubDate><r:package>PERCEPTIONx</r:package><r:version>0.3.0</r:version><r:status>success</r:status><r:repository>https://wanglabcsu.r-universe.dev</r:repository><r:upstream>https://github.com/WangLabCSU/PERCEPTIONx</r:upstream><r:article><r:source>shiny_app.Rmd</r:source><r:filename>shiny_app.html</r:filename><r:title>PERCEPTION-shiny User Guide</r:title><r:created>2026-08-28 14:03:03</r:created><r:modified>2026-09-19 09:52:18</r:modified></r:article><r:article><r:source>shiny_app_cn.Rmd</r:source><r:filename>shiny_app_cn.html</r:filename><r:title>PERCEPTION-shiny 使用教程</r:title><r:created>2026-08-28 14:03:03</r:created><r:modified>2026-09-19 09:52:18</r:modified></r:article><r:article><r:source>pipeline.Rmd</r:source><r:filename>pipeline.html</r:filename><r:title>PERCEPTIONx: Complete Pipeline Tutorial</r:title><r:created>2026-06-16 18:26:56</r:created><r:modified>2026-09-03 06:55:00</r:modified></r:article></item></channel></rss>