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bio-bedgraph-handling生物床图处理

Agent Skill

bio-bedgraph-handling 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

360

周安装

15

GitHub Stars

公开资料未说明

下载量

120
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:bio-bedgraph-handling(生物床图处理)
来源仓库:https://github.com/gptomics/bioskills
仓库路径:skills/bio-bedgraph-handling
安装命令:
npx skills add gptomics/bioskills --skill "bio-bedgraph-handling"
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

AgentSkills.tonpx skills
npx skills add gptomics/bioskills --skill "bio-bedgraph-handling"

简介

发现并安装 AI 代理的技能。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适用于基因组覆盖度数据的存储与可视化预处理。
  • 支持 bedGraph 格式转换、排序和归一化操作。
  • 需确保坐标系统一致(如 hg38)。
  • bio-bedgraph-handling 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

bedGraph Handling

bedGraph is a text format for displaying continuous-valued data on genome browsers. Common for coverage, signal intensity, and scores.

bedGraph Format

track type=bedGraph name="Sample" description="Coverage"
chr1    0       100     1.5
chr1    100     200     2.3
chr1    200     300     0.8

Four columns: chrom, start, end, value (0-based, half-open)

Create bedGraph from BAM

Using bedtools genomecov

bedtools genomecov -ibam sample.bam -bg > sample.bedgraph
bedtools genomecov -ibam sample.bam -bg -split > sample.bedgraph
bedtools genomecov -ibam sample.bam -bg -scale 1.5 > sample.scaled.bedgraph

Strand-Specific

bedtools genomecov -ibam sample.bam -bg -strand + > sample.plus.bedgraph
bedtools genomecov -ibam sample.bam -bg -strand - > sample.minus.bedgraph

5' End Coverage (ChIP-seq)

bedtools genomecov -ibam sample.bam -bg -5 > sample.5prime.bedgraph

Normalize by Library Size (CPM)

total_reads=$(samtools view -c -F 260 sample.bam)
scale=$(echo "scale=10; 1000000 / $total_reads" | bc)

bedtools genomecov -ibam sample.bam -bg -scale $scale > sample.cpm.bedgraph

Sort bedGraph

bedGraph must be sorted for conversion to bigWig.

sort -k1,1 -k2,2n sample.bedgraph > sample.sorted.bedgraph
LC_ALL=C sort -k1,1 -k2,2n sample.bedgraph > sample.sorted.bedgraph

Convert bedGraph to bigWig

Using UCSC bedGraphToBigWig

bedGraphToBigWig sample.sorted.bedgraph chrom.sizes sample.bw
fetchChromSizes hg38 > hg38.chrom.sizes
bedGraphToBigWig sample.sorted.bedgraph hg38.chrom.sizes sample.bw

Generate chrom.sizes

samtools faidx reference.fa
cut -f1,2 reference.fa.fai > chrom.sizes
fetchChromSizes hg38 > hg38.chrom.sizes
mysql --user=genome --host=genome-mysql.soe.ucsc.edu -A -e \
    "select chrom, size from hg38.chromInfo" > hg38.chrom.sizes

Clip to Chromosome Boundaries

bedClip sample.bedgraph chrom.sizes sample.clipped.bedgraph
bedGraphToBigWig sample.clipped.bedgraph chrom.sizes sample.bw

Convert bigWig to bedGraph

bigWigToBedGraph sample.bw sample.bedgraph
bigWigToBedGraph sample.bw sample.chr1.bedgraph -chrom=chr1
bigWigToBedGraph sample.bw sample.region.bedgraph -chrom=chr1 -start=1000 -end=2000

Merge bedGraph Files

Using bedtools unionbedg

bedtools unionbedg -i sample1.bedgraph sample2.bedgraph sample3.bedgraph \
    -header -names sample1 sample2 sample3 > merged.bedgraph

Average Across Samples

bedtools unionbedg -i sample1.bedgraph sample2.bedgraph sample3.bedgraph | \
    awk '{sum=0; for(i=4;i<=NF;i++) sum+=$i; print $1,$2,$3,sum/(NF-3)}' OFS='\t' \
    > average.bedgraph

Mathematical Operations

bedtools map for Region Statistics

bedtools map -a regions.bed -b sample.bedgraph -c 4 -o mean > region_means.bed
bedtools map -a regions.bed -b sample.bedgraph -c 4 -o sum > region_sums.bed
bedtools map -a regions.bed -b sample.bedgraph -c 4 -o max > region_max.bed

Subtract Background

bedtools unionbedg -i treatment.bedgraph input.bedgraph | \
    awk '{diff=$4-$5; if(diff<0) diff=0; print $1,$2,$3,diff}' OFS='\t' \
    > subtracted.bedgraph

Log Transform

awk '{print $1,$2,$3,log($4+1)/log(2)}' OFS='\t' sample.bedgraph > sample.log2.bedgraph

Smooth Signal

bedtools slop -i sample.bedgraph -g chrom.sizes -b 50 | \
    bedtools merge -i - -c 4 -o mean > smoothed.bedgraph

Python with pyBigWig

Write bedGraph

import pyBigWig

bw = pyBigWig.open('output.bedgraph', 'w')
bw.addHeader([('chr1', 248956422), ('chr2', 242193529)])

chroms = ['chr1', 'chr1', 'chr1']
starts = [0, 100, 200]
ends = [100, 200, 300]
values = [1.5, 2.3, 0.8]
bw.addEntries(chroms, starts, ends=ends, values=values)
bw.close()

Read bigWig to bedGraph Format

import pyBigWig

bw = pyBigWig.open('sample.bw')

for chrom, size in bw.chroms().items():
    intervals = bw.intervals(chrom)
    if intervals:
        for start, end, value in intervals:
            print(f'{chrom}\t{start}\t{end}\t{value}')

bw.close()

Convert bigWig Region to bedGraph

import pyBigWig

bw = pyBigWig.open('sample.bw')
intervals = bw.intervals('chr1', 1000000, 2000000)

with open('region.bedgraph', 'w') as f:
    for start, end, value in intervals:
        f.write(f'chr1\t{start}\t{end}\t{value}\n')

bw.close()

deepTools for Normalization

bamCoverage (BAM to bedGraph/bigWig)

bamCoverage -b sample.bam -o sample.bw --normalizeUsing RPKM
bamCoverage -b sample.bam -o sample.bw --normalizeUsing CPM
bamCoverage -b sample.bam -o sample.bw --normalizeUsing BPM
bamCoverage -b sample.bam -o sample.bedgraph --outFileFormat bedgraph --normalizeUsing CPM

bamCompare (Treatment vs Control)

bamCompare -b1 treatment.bam -b2 input.bam -o log2ratio.bw --scaleFactorsMethod readCount
bamCompare -b1 treatment.bam -b2 input.bam -o subtracted.bw --ratio subtract

bigwigCompare

bigwigCompare -b1 treatment.bw -b2 input.bw -o ratio.bw --ratio log2
bigwigCompare -b1 sample1.bw -b2 sample2.bw -o diff.bw --ratio subtract

Filtering and Subsetting

Filter by Value

awk '$4 >= 1.0' sample.bedgraph > high_signal.bedgraph
awk '$4 > 0' sample.bedgraph > nonzero.bedgraph

Extract Regions

bedtools intersect -a sample.bedgraph -b regions.bed > subset.bedgraph

Remove Specific Chromosomes

grep -v "^chrM" sample.bedgraph | grep -v "_random" > filtered.bedgraph
awk '$1 ~ /^chr[0-9XY]+$/' sample.bedgraph > standard_chroms.bedgraph

Aggregate to Bins

Fixed-Size Bins

bedtools makewindows -g chrom.sizes -w 1000 > bins.bed
bedtools map -a bins.bed -b sample.bedgraph -c 4 -o mean > binned.bedgraph

Gene Bodies

bedtools map -a genes.bed -b sample.bedgraph -c 4 -o mean > gene_signal.bed

Quality Control

Check for Overlapping Intervals

bedtools merge -i sample.bedgraph -c 4 -o collapse | \
    awk 'index($4,",") > 0' | head

Verify Sorted Order

sort -c -k1,1 -k2,2n sample.bedgraph && echo "Sorted" || echo "Not sorted"

Check Value Range

awk 'NR==1 {min=$4; max=$4} {if($4<min) min=$4; if($4>max) max=$4}
     END {print "Min:", min, "Max:", max}' sample.bedgraph

Complete Pipeline

#!/bin/bash
BAM=$1
NAME=$(basename $BAM .bam)
CHROM_SIZES=$2

total_reads=$(samtools view -c -F 260 $BAM)
scale=$(echo "scale=10; 1000000 / $total_reads" | bc)

bedtools genomecov -ibam $BAM -bg -scale $scale > ${NAME}.bedgraph

sort -k1,1 -k2,2n ${NAME}.bedgraph > ${NAME}.sorted.bedgraph

bedClip ${NAME}.sorted.bedgraph $CHROM_SIZES ${NAME}.clipped.bedgraph

bedGraphToBigWig ${NAME}.clipped.bedgraph $CHROM_SIZES ${NAME}.bw

rm ${NAME}.bedgraph ${NAME}.sorted.bedgraph ${NAME}.clipped.bedgraph

echo "Created ${NAME}.bw (CPM normalized)"

Track Header for UCSC

echo 'track type=bedGraph name="Sample" description="CPM normalized" visibility=full color=0,0,255 altColor=255,0,0 autoScale=on graphType=bar' > track.bedgraph
cat sample.bedgraph >> track.bedgraph

Related Skills

  • coverage-analysis - Generate coverage from alignments
  • bigwig-tracks - Work with bigWig format
  • chipseq-visualization - Visualize signal tracks
  • alignment-files - BAM file processing

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

04

需要参考平台分布和安装热度时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

补充不同宿主或平台的使用分布数据

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

windsurf

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按下载量换算33

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OpenCode

16.47%
按下载量换算20

Codex

11.75%
按下载量换算14

Claude Code

7.32%
按下载量换算9

Antigravity

3.52%
按下载量换算4

安全审计

暂无安全审计结果可展示。

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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