数据与复现生物信息与基因组学FreedomIntelligence/OpenClaw-Medical-Skills数据与复现
BI

bio-differential-expression-timeseries-de

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

Analyze time-series RNA-seq data using limma voom with splines, maSigPro, and ImpulseDE2. Identify genes with dynamic expression patterns. Use when analyzing time-series or longitudinal expression data.

OpenClawNanoClaw分析处理复现实验bio-differential-expression-timeseries-de🧬 bioinformatics (gptomics bio-* suite)bioinformatics — differential expression & transcriptomicsanalyze

原始来源

FreedomIntelligence/OpenClaw-Medical-Skills

https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-differential-expression-timeseries-de

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

技能摘要

来自 SKILL.md 的关键信息

2 min

核心说明

  • Identify genes ,支持 significant temporal expression patterns in time-course experiments。
  • counts <- read.table('counts.txt',header=TRUE,row.names=1) metadata <- read.table('metadata.txt',header=TRUE)。

原始文档

SKILL.md 摘录

Approaches

MethodBest For
limma with splinesSmooth temporal patterns
maSigProMultiple time points, regression
ImpulseDE2Impulse-like patterns
DESeq2 LRTDiscrete time comparisons

limma with Splines

Goal: Identify genes with smooth temporal expression patterns using flexible spline models.

Approach: Fit voom-transformed counts with natural spline basis functions in limma, testing spline coefficients for significance.

"Find genes that change over time in my RNA-seq experiment" → Model temporal expression using spline regression and test whether spline terms are significantly non-zero.

Setup

library(limma)
library(edgeR)
library(splines)

适用场景

  • 适合在analyzing time-series 或 longitudinal expression data时使用。

不适用场景

  • Do not rely on this catalog entry alone ,用于 installation 或 maintenance details。

上游相关技能

  • differential-expression/deseq2-basics - Standard DE analysis
  • differential-expression/de-visualization - Visualize results
  • differential-expression/batch-correction - Handle batch effects
  • pathway-analysis/go-enrichment - Functional analysis of clusters
  • temporal-genomics/circadian-rhythms - Circadian rhythm detection for time-course data
  • temporal-genomics/temporal-clustering - Cluster genes by temporal expression profile

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