ATAC-seq Data Processing Abstract ATAC-seq (Assay for Transposase-Accessible Chromatin using sequencing) has gained wide popularity as a fast, straightforward, and efficient way of generating genome-wide maps of open chromatin and guiding identification of active regulatory elements and inference of DNA...
See Buenrostroet al., 2015, ENCODE - ATAC-seq Data Standards and Prototype Processing Pipeline, and Harvard FAS Informatics - ATAC-seq Guidelines for details. 两个或更多的生物学重复样本 每个重复样本包含单端测序的2500万条非重复、非线粒...
A data processing platform for ChIP-seq; RNA-seq; MNase-seq; DNase-seq; ATAC-seq; and GRO-seq datasets + Guzman & D’Orso (2017) Last updated: 2017 ENCODE Python; Bash Complete pipeline following ENCODE standards for ATAC/DNase-seq analysis ...
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...
See Buenrostroet al., 2015, ENCODE - ATAC-seq Data Standards and Prototype Processing Pipeline, and Harvard FAS Informatics - ATAC-seq Guidelines for details. 两个或更多的生物学重复样本 每个重复样本包含单端测序的2500万条非重复、非线粒体的比对读段,以及双端测序的5000万条 ...
ENCODE - ATAC-seq Data Standards and Prototype Processing Pipeline:https://www.encodeproject.org/atac-seq/ 以下是ENCODE所使用的标准,以下将详细解释每个术语的具体描述。 当前标准: 实验需要有>=2个生物学重复 每个重复数据量至少:25M 非重复re...
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. ...
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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。