ATAC-seq data analysis: from FASTQ to peaks ATAC-seq Data Standards and Processing Pipeline in ENCODE ATAC-seq数据分析实战 Harvard FAS Informatics - ATAC-seq Guidelines 第一篇文章是我学习ATAC-seq的首选文章。它非常耐心细致地讲解了从raw data到ATAC-seq 的peak数据的分析流程,非常建议读一读。 第二...
Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012 Mar 4;9(4):357-9.Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map f...
Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, Marth G, Abecasis G, Durbin R; 1000 Genome Project Data Processing Subgroup. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009 Aug 15;25(16):2078-9. ...
ChIP-seq Data Standards and Processing Pipeline ATAC-seq Data Standards and Prototype Processing Pipeline 还有比这更靠谱的pipeline吗,肯定是没了。但是开始学习时肯定不推荐用这些pipeline,封装得太好了,完全学不到什么精华知识。 安装完成后,建议自己构建小测试数据来测试流程,我测试了没问题。 这些流程的NB之处...
Merge branch 'dev' ofhttps://github.com/databio/pepatacinto dev Oct 31, 2022 README BSD-2-Clause license PEPATAC is a pipeline for ATAC-seq data. For more information see:http://pepatac.databio.org/ Docs Develop docs with: mkdocs serve -f mkdocs.yml ...
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wget -4 -q ftp://ftp.ccb.jhu.edu/pub/data/bowtie2_indexes/mm10.zip unzip mm10.zip 因为我自己服务器没法run bowtie(bowtie2对人类全基因组的比对至少消耗4G以上吧),但代码还是可以写的: #把sort直接一步做了 bowtie2 -x /public/reference/index/bowtie/mm10 -1 test1.fq -2 test2.fq |...
Data processing and analysis Raw code for the brain analysis is available athttps://github.com/adeylab/txci-atac. Raw code for the cell line and lung/liver datasets is available athttps://github.com/cusanovichlab/txciatac. The specific programs (and their version) used in data analyses we...
The primary tool currently used to pre-process 10X Chromium single-cell ATAC-seq data is Cell Ranger, which can take very long to run on standard datasets. To facilitate rapid pre-processing that enables reproducible workflows, we present a suite of tools called scATAK for pre-processing ...
ATACProc is a pipeline to analyze ATAC-seq data. Currently datasets involving one of the four reference genomes, namely hg19, hg38, mm9 and mm10 are supported. Important features of this pipeline are: Supports single or paired-end fastq or BAM formatted data. ...