已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

CpGtools: a python package for DNA methylation analysis

Python(编程语言) 程序设计语言 R包 软件 生物导体 源代码
作者
Ting Wei,Jinfu J. Nie,Nicholas B. Larson,Zhenqing Ye,Jeanette E. Eckel-Passow,Keith D. Robertson,Jean-Pierre A. Kocher,Liguo Wang
出处
期刊:Bioinformatics [Oxford University Press]
卷期号:37 (11): 1598-1599 被引量:8
标识
DOI:10.1093/bioinformatics/btz916
摘要

Motivation DNA methylation can be measured at the single CpG level using sodium bisulfite conversion of genomic DNA followed by sequencing or array hybridization. Many analytic tools have been developed, yet there is still a high demand for a comprehensive and multifaceted tool suite to analyze, annotate, QC and visualize the DNA methylation data. Results We developed the CpGtools package to analyze DNA methylation data generated from bisulfite sequencing or Illumina methylation arrays. The CpGtools package consists of three types of modules: (i) 'CpG position modules' focus on analyzing the genomic positions of CpGs, including associating other genomic and epigenomic features to a given list of CpGs and generating the DNA motif logo enriched in the genomic contexts of a given list of CpGs; (ii) 'CpG signal modules' are designed to analyze DNA methylation values, such as performing the PCA or t-SNE analyses, using Bayesian Gaussian mixture modeling to classify CpG sites into fully methylated, partially methylated and unmethylated groups, profiling the average DNA methylation level over user-specified genomics regions and generating the bean/violin plots and (iii) 'differential CpG analysis modules' focus on identifying differentially methylated CpGs between groups using different statistical methods including Fisher's Exact Test, Student's t-test, ANOVA, non-parametric tests, linear regression, logistic regression, beta-binomial regression and Bayesian estimation. Availability and implementation CpGtools is written in Python under the open-source GPL license. The source code and documentation are freely available at https://github.com/liguowang/cpgtools. Supplementary information Supplementary data are available at Bioinformatics online.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
qzh发布了新的文献求助10
4秒前
Lucas应助科研通管家采纳,获得10
4秒前
华仔应助科研通管家采纳,获得10
4秒前
橘x应助科研通管家采纳,获得100
4秒前
从容水蓝应助科研通管家采纳,获得10
4秒前
华仔应助科研通管家采纳,获得10
4秒前
共享精神应助科研通管家采纳,获得10
4秒前
从容水蓝应助科研通管家采纳,获得10
4秒前
顾矜应助科研通管家采纳,获得10
4秒前
5秒前
7秒前
NexusExplorer应助结实的寒烟采纳,获得10
8秒前
Tree完成签到 ,获得积分10
9秒前
绾妤完成签到 ,获得积分0
12秒前
乖巧的菜猪完成签到 ,获得积分10
12秒前
123456完成签到 ,获得积分10
14秒前
健壮的花瓣完成签到 ,获得积分10
15秒前
16秒前
24发布了新的文献求助10
17秒前
17秒前
疯狂的梦琪完成签到,获得积分20
18秒前
19秒前
20秒前
组难装完成签到,获得积分10
21秒前
泶1完成签到,获得积分10
21秒前
23秒前
26秒前
小龙陈发布了新的文献求助10
26秒前
哇哦哦完成签到 ,获得积分10
28秒前
Lucas应助七分甜采纳,获得10
29秒前
刘雨森完成签到 ,获得积分10
30秒前
悦耳青梦发布了新的文献求助10
31秒前
啊锐完成签到,获得积分0
31秒前
Lucas应助cqhecq采纳,获得10
33秒前
xin完成签到 ,获得积分10
35秒前
38秒前
40秒前
Akim应助小龙陈采纳,获得10
41秒前
Ujjel75发布了新的文献求助10
44秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Modern Epidemiology, Fourth Edition 5000
Handbook of pharmaceutical excipients, Ninth edition 5000
Digital Twins of Advanced Materials Processing 2000
Weaponeering, Fourth Edition – Two Volume SET 2000
Polymorphism and polytypism in crystals 1000
Social Cognition: Understanding People and Events 800
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6027245
求助须知:如何正确求助?哪些是违规求助? 7675546
关于积分的说明 16184948
捐赠科研通 5174865
什么是DOI,文献DOI怎么找? 2769039
邀请新用户注册赠送积分活动 1752492
关于科研通互助平台的介绍 1638233