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bio-epitranscriptomics-m6a-differential
Maintainer FreedomIntelligence · Last updated April 1, 2026
Differential m6A methylation analysis between conditions.
Original source
FreedomIntelligence/OpenClaw-Medical-Skills
https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-epitranscriptomics-m6a-differential
- Maintainer
- FreedomIntelligence
- License
- MIT
- Last updated
- April 1, 2026
Skill Snapshot
Key Details From SKILL.md
Key Notes
- design <- data.frame( condition = factor(c('ctrl', 'ctrl', 'treat', 'treat')) ).
- result <- exomePeak2( bam_ip = c('ctrl_IP1.bam', 'ctrl_IP2.bam', 'treat_IP1.bam', 'treat_IP2.bam'), bam_input = c('ctrl_Input1.bam', 'ctrl_Input2.bam', 'treat_Input1.bam', 'treat_Input2.bam'), gff = 'genes.gtf', genome = 'hg38', experiment_design = design ).
Source Doc
Excerpt From SKILL.md
exomePeak2 Differential Analysis
library(exomePeak2)
## Get differential sites
diff_sites <- results(result, contrast = c('condition', 'treat', 'ctrl'))
IP and input counts per sample
qnb_result <- qnbtest( IP_count_matrix, Input_count_matrix, group = c(1, 1, 2, 2) # 1=ctrl, 2=treat )
Use cases
- Use bio-epitranscriptomics-m6a-differential for genomics and bioinformatics workflows.
- Apply bio-epitranscriptomics-m6a-differential to sequencing, variant, or omics analysis tasks.
Not for
- Do not rely on this catalog entry alone for installation or maintenance details.
Upstream Related Skills
- m6a-peak-calling - Identify peaks first
- differential-expression/de-results - Similar statistical concepts
- modification-visualization - Plot differential sites
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