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博客园 - Life·Intelligence

SSHFS + VS Code 挂载集群代码目录(macOS)| 集群vibe coding - Life·Intelligence OpenClaw 多 Channel 实战总结(Windows 环境) OpenClaw Windows 安装与 Debug 最终版教程(适用于 MiniPC i3-N305 / 无 GPU) miniconda转miniforge | conda | license LightDock | 蛋白质-多肽对接 | peptide-protein docking 蛋白结构预测 | alphafold | colabfold | docking 全栈生信 | PyMol使用教程 细胞通讯推断 | CCI | CellChat | CellphoneDB | iTALK | NicheNet ChromHMM教程 极简 | GRN | SCENIC | pySCENIC | 安装使用最新版scenicplus - Life·Intelligence Linux下载zenodo数据 findOverlappingPeaks | peak取交集操作 根据基因名批量查询下载PDB蛋白结构数据库 R小技巧汇总 Signac处理bulk ATAC-seq数据 - Life·Intelligence Differential motif enrichment | CentriMo | meme 亚马逊云 | AWS S3 | 基本操作 ATAC-seq | TOBIAS | footprint分析 TCGA+GTEx基因表达数据合并 | 多癌种表达分析
共定位 | colocalization 分析 | 表观因子
Life·Intelli · 2024-12-18 · via 博客园 - Life·Intelligence

这是个非常经典的分析,用于来确定蛋白互作。

传统的蛋白互作分析,就是co-IP,Mass spec等,但这类技术的假阳性和敏感度都不够。

还有就是荧光图,然后对图像做共定位分析,这个需要非常高分辨率的共聚焦显微镜。

还有一种,表观因子的共定位分析,那就是对ChIP-seq和Cut&Run的summit做距离分析。

bedtools closest 已经帮你实现了这个功能。【peak注释到gene其实也用了类似的函数】

https://bedtools.readthedocs.io/en/latest/content/tools/closest.html

这个方法存在的问题:

  • summit的鉴定非常依赖高质量的ChIP-seq和Cut&Run数据

但我觉得这个技术整体是可行的,能够得到一部分有意义的信息。

代码:

bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Paul_dTAG/DMSO_SMARCC1_1.sorted.mapped.bam_summits.bed -d > SOX9_SMARCC1.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed -d > SOX9_SOX9.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Raghwan_dTAG/dT29_SMB1_DM1.sorted.mapped.bam_summits.bed -d > SOX9_SMB1.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Raghwan_dTAG/dT29_SC1_DM1.sorted.mapped.bam_summits.bed -d > SOX9_SC1.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Raghwan_dTAG/dT29_PBR1_DM1.sorted.mapped.bam_summits.bed -d > SOX9_PBR1.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Raghwan_dTAG/dT29_BRD9_DM1.sorted.mapped.bam_summits.bed -d > SOX9_BRD9.summit.distance
bedtools closest -a Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed -b Raghwan_dTAG/dT29_ARD1_DM1.sorted.mapped.bam_summits.bed -d > SOX9_ARD1.summit.distance

有时候需要归一化,sort一下bed

cut -f1-5 SRX181192.05.bed > SRX181192.05.bed2
cut -f1-5 SRX181191.05.bed > SRX181191.05.bed2



sort -k1,1 -k2,2n Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.bed > Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.sorted.bed

sort -k1,1 -k2,2n SRX181192.05.bed2 > SRX181192.05.sorted.bed
sort -k1,1 -k2,2n SRX181191.05.bed2 > SRX181191.05.sorted.bed

bedtools sort -g chr.list -i Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.sorted.bed2 > Raghwan_dTAG/dT29_SOX9_DM1.sorted.mapped.bam_summits.sorted.bed

bedtools sort -g chr.list -i SRX181192.05.bed3 > SRX181192.05.sorted.bed
bedtools sort -g chr.list -i SRX181191.05.bed3 > SRX181191.05.sorted.bed

grep "chr\?\?" SRX181192.05.bed2 > SRX181192.05.bed3
grep "chr\?\?" SRX181191.05.bed2 > SRX181191.05.bed3

grep -v "_gl" SRX181192.05.bed2 > SRX181192.05.bed3
grep -v "_gl" SRX181191.05.bed2 > SRX181191.05.bed3

sort -k1,1 -k2,2n Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed > Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed2
bedtools sort -g chr.list -i Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed2 > Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.sorted.bed

bedtools closest -a Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed2 -b SRX181192.05.sorted.bed -d > SOX9_NME2_1.summit.distance
bedtools closest -a Paul_dTAG/DMSO_SOX9_1.sorted.mapped.bam_summits.bed2 -b SRX181191.05.sorted.bed -d > SOX9_NME2_2.summit.distance

参考:

- http://localhost:17449/lab/tree/projects/BAF_SOX9/diffbind/5.Motif.ipynb#summit-distance