Analyze DNA methylation in Oxford Nanopore data without bisulfite conversion. Use modkit to summarize modified-base information into per-site methylation frequencies, inspect sample statistics, and focus analysis on CpG islands or promoter regions.
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Calls DNA methylation from Oxford Nanopore sequencing data using signal-level analysis. Use when detecting 5mC or 6mA modifications directly from nanopore reads without bisulfite conversion.
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Reference examples tested with: methylKit 1.28+, minimap2 2.26+, samtools 1.19+
Before using code patterns, verify installed versions match. If versions differ:
<tool> --version then <tool> --help to confirm flagsIf code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.
"Call methylation from my Nanopore reads" → Extract 5mC/6mA modification probabilities from basecalled reads and summarize per-site methylation frequencies.
modkit pileup aligned.bam methylation.bed --ref ref.faONT's modkit is the recommended tool for methylation analysis from basecalled data.
# Assumes BAM has MM/ML tags from dorado basecalling
modkit pileup input.bam methylation.bed \
--ref reference.fa \
--cpg \
--combine-strands
# bedMethyl format
chr1 1000 1001 . 10 + 1000 1001 0,0,0 10 80.5
# Columns: chrom, start, end, name, score, strand, thickStart, thickEnd,
# itemRgb, coverage, percent_modified
# Dorado basecalling with 5mC model
dorado basecaller dna_r10.4.1_e8.2_400bps_sup@v4.2.0 \
pod5_dir/ \
--modified-bases 5mCG \
> calls.bam
# Index and align
samtools fastq calls.bam | \
minimap2 -ax map-ont -y reference.fa - | \
samtools sort -o aligned.bam
samtools index aligned.bam
# CpG islands only
modkit pileup aligned.bam cpg_islands.bed \
--ref reference.fa \
--cpg \
--include-bed cpg_islands.bed
# Promoter regions
modkit pileup aligned.bam promoters.bed \
--ref reference.fa \
--cpg \
--include-bed promoters.bed
# Get modification summary statistics
modkit summary aligned.bam
# Output includes:
# - Total reads with modifications
# - Modification types detected
# - Fraction modified per type
# Create BED files for each sample
modkit pileup sample1.bam sample1.bed --ref ref.fa --cpg
modkit pileup sample2.bam sample2.bed --ref ref.fa --cpg
# Compare with methylKit or DSS in R
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Support protein design with cloud laboratory testing for binding, expression, thermal stability, and enzyme activity. Covers sequence optimization, submitting experiments through the Adaptyv API, checking progress, and downloading experimental results.
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Build flexible daily plans that account for ADHD-related difficulties with time estimation and getting started. Narrow priorities to three tasks, add transition buffers, and choose small next actions that match the energy available that day.
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Build Python workflows for data recorded over time, including classification, forecasting, anomaly detection, and pattern search. Using aeon, the skill guides preprocessing, algorithm selection, feature extraction, and evaluation through interfaces compatible with scikit-learn.
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Use a browser to research topics, extract page information, fill forms, and test websites. Guides agents through identifying page controls, interacting with web apps, saving screenshots or PDFs, and reusing saved login sessions.
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Combine health measurements, exercise, sleep, nutrition, and mental health records to examine trends, unusual changes, and estimated risks. The skill produces personalized suggestions and text or interactive HTML reports using local data without external API calls.
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Predict structures for designed protein sequences and protein complexes with AlphaFold2 or ColabFold. Inspect structure files and confidence scores to assess folding and chain interfaces, with guidance for local runs, Modal execution, and common prediction errors.
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