数据与复现临床医学与医药FreedomIntelligence/OpenClaw-Medical-Skills数据与复现

tumor-clonal-evolution-agent

维护者 FreedomIntelligence · 最近更新 2026年4月1日

Model tumor clonal evolution: phylogenetic trees, clonal dynamics, branching patterns from somatic variants.

OpenClawNanoClaw分析处理复现实验tumor-clonal-evolution-agent🧠 bioos extended suiteoncology & precision medicine agentsmodel

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/tumor-clonal-evolution-agent

技能摘要

2 min

Tumor Clonal Evolution Agent analyzes intratumoral heterogeneity (ITH)，reconstructs tumor phylogenies，、 tracks clonal dynamics over time. It integrates multi-region sequencing data，longitudinal liquid biopsies，、 mathematical modeling to predict treatment response 、 resistance emergence。
When analyzing multi-region tumor sequencing to map spatial heterogeneity。
To reconstruct tumor phylogenetic trees 、 identify ancestral mutations。
用于 tracking clonal evolution through serial liquid biopsy samples。
To predict time to treatment failure ，使用 evolutionary modeling。

原始文档

Clonal Deconvolution: Identifies tumor subpopulations and estimates their cellular fractions using variant allele frequencies (VAF) from bulk sequencing.
Phylogenetic Reconstruction: Builds tumor evolutionary trees showing relationships between subclones and their mutational acquisition order.
Longitudinal Tracking: Monitors subclone dynamics over time using ctDNA variant frequencies from serial blood draws.
Resistance Prediction: Applies Bayesian evolutionary frameworks to forecast emergence of resistant clones and time to progression.
Spatial ITH Mapping: Integrates multi-region data to visualize spatial distribution of subclones across tumor sites.
Fitness Estimation: Calculates subclone fitness parameters to identify aggressive populations driving tumor progression.

Input: Multi-region or longitudinal mutation data (VCF/MAF), tumor purity estimates, copy number profiles.
Clustering: Cluster mutations into subclones using PyClone, SciClone, or MOBSTER.
Phylogeny: Reconstruct evolutionary trees using CITUP, PhyloWGS, or CALDER.
Modeling: Apply mathematical models (Lotka-Volterra, birth-death) to estimate dynamics.
Prediction: Forecast treatment response and resistance timeline.
Output: Phylogenetic trees, subclone trajectories, resistance predictions, actionable insights.

User: "Analyze the clonal evolution from these 6 longitudinal ctDNA samples and predict time to progression."

Agent Action:

Use tumor-clonal-evolution-agent ，用于 clinical，translational，或 medical research tasks。
Apply tumor-clonal-evolution-agent when healthcare-specific guidance is required。