What is TopHat?

TopHat is a program that aligns RNA-Seq reads to a genome in order to identify exon-exon splice junctions. It is built on the ultrafast short read mapping program Bowtie. TopHat runs on Linux and OS X.

How does TopHat find junctions?

TopHat can find splice junctions without a reference annotation. By first mapping RNA-Seq reads to the genome, TopHat identifies potential exons, since many RNA-Seq reads will contiguously align to the genome. Using this initial mapping information, TopHat builds a database of possible splice junctions and then maps the reads against these junctions to confirm them.

Short read sequencing machines can currently produce reads 100bp or longer but many exons are shorter than this so they would be missed in the initial mapping. TopHat solves this problem mainly by splitting all input reads into smaller segments which are then mapped independently. The segment alignments are put back together in a final step of the program to produce the end-to-end read alignments.

TopHat generates its database of possible splice junctions from two sources of evidence. The first and strongest source of evidence for a splice junction is when two segments from the same read (for reads of at least 45bp) are mapped at a certain distance on the same genomic sequence or when an internal segment fails to map - again suggesting that such reads are spanning multiple exons. With this approach, "GT-AG", "GC-AG" and "AT-AC" introns will be found ab initio. The second source is pairings of "coverage islands", which are distinct regions of piled up reads in the initial mapping. Neighboring islands are often spliced together in the transcriptome, so TopHat looks for ways to join these with an intron. We only suggest users use this second option (--coverage-search)  for short reads (< 45bp) and with a small number of reads (<= 10 million).  This latter option will only report alignments across "GT-AG" introns

TopHat的更多相关文章

  1. tophat输出结果junction.bed

    tophat输出结果junction.bed BED format       BED format provides a flexible way to define the data lines ...

  2. tophat安装

    1     依赖软件:bowtie,bowtie2,samtools,boost c++ library 2     建立索引文件:      bowtie包括bowtie,bowtie-build, ...

  3. RNA-seq差异表达基因分析之TopHat篇

    RNA-seq差异表达基因分析之TopHat篇 发表于2012 年 10 月 23 日 TopHat是基于Bowtie的将RNA-Seq数据mapping到参考基因组上,从而鉴定可变剪切(exon-e ...

  4. 机器学习进阶-图像形态学变化-礼帽与黑帽 1.cv2.TOPHAT(礼帽-原始图片-开运算后图片) 2.cv2.BLACKHAT(黑帽 闭运算-原始图片)

    1.op = cv2.TOPHAT  礼帽:原始图片-开运算后的图片 2. op=cv2.BLACKHAT 黑帽: 闭运算后的图片-原始图片 礼帽:表示的是原始图像-开运算(先腐蚀再膨胀)以后的图像 ...

  5. 使用Tophat+cufflinks分析差异表达

    使用Tophat+cufflinks分析差异表达  2017-06-15 19:09:43     522     0     0 使用TopHat+Cufflinks的流程图 序列的比对是RNA分析 ...

  6. RNA-seq 安装 fastaqc,tophat,cuffilnks,hisat2

    ------------------------------------------ 安装fastqc------------------------------------------------- ...

  7. tophat的用法

    概述:tophat是以bowtie2为核心的一款比对软件. tophat工作分两步: 1.将reads用bowtie比对到参考基因组上. 2.将unmapped-reads打断成更小的fragment ...

  8. SAGE|DNA微阵列|RNA-seq|lncRNA|scripture|tophat|cufflinks|NONCODE|MA|LOWESS|qualitile归一化|permutation test|SAM|FDR|The Bonferroni|Tukey's|BH|FWER|Holm's step-down|q-value|

    生物信息学-基因表达分析 为了丰富中心法则,研究人员使用不断更新的技术研究lncRNA的方方面面,其中技术主要是生物学上的微阵列芯片技术和表达数据分析方法,方方面面是指lncRNA的位置特征. Bac ...

  9. 链终止法|边合成边测序|Bowtie|TopHat|Cufflinks|RPKM|FASTX-Toolkit|fastaQC|基因芯片|桥式扩增|

    生物信息学 Sanger采用链终止法进行测序 带有荧光基团的ddXTP+其他四种普通的脱氧核苷酸放入同一个培养皿中,例如带有荧光基团的ddATP+普通的脱氧核苷酸A.T.C.G放入同一个培养皿,以此类 ...

随机推荐

  1. 一次ie8模式下click无反应的小事

    想起了小学时候数不尽的一件小事,哎,那夕阳下的奔跑,是我逝去的青春啊. 言归正传,先上图: <select id="cardNoList" size="4" ...

  2. mysql 优化(一)

    SHOW VARIABLES like 'slow_query_log'  #查看慢查询设置  1 set GLOBAL slow_query_log_file ="d:/sql/sql_l ...

  3. sudo 命令情景分析

    Linux 下使用 sudo 命令,可以让普通用户也能执行一些或者全部的 root 命令.本文就对我们常用到 sudo 操作情景进行简单分析,通过一些例子来了解 sudo 命令相关的技巧. 情景一:用 ...

  4. ubuntu下安装加装DNS

    感觉在ubuntu下网速特别的慢,所以网上找了下解决方案,本地缓存域名解析相关信息. 首先,安装dns服务 命令: sudo apt-get install dnsmasq 编辑dnsmasq的配置文 ...

  5. java内部类

    1.内部类 2.内部类的名字不会单独存在,根据外部类名的存在而存在.内部类的名字可以和外部其他类的名字一样. 3.这个this.num打印的是inner类里面的num 4.在内部类访问外部类成员变量方 ...

  6. RFID考试背诵

    简答题: 简述RFID标准多元化的原因: 由不同的技术因素.利益因素导致: 工作频率分布在低频至微波的多个频段中,频率不同,技术差异大. 作用距离的差异导致标准不同:因为应答器分为有源.无源两种工作方 ...

  7. python_面向对象编程

    一.编程范式 程序员通过特定的语法+数据结构+算法告诉计算机如果执行任务,实现这个过程有不同的编程方式,对这些不同的编程方式进行归纳总结得出来的编程方式类别,即为编程范式 编程范式:面向过程编程.面向 ...

  8. Redis-基于php简单安装使用

    1.下载php相关redis扩展(apache选vc6),下载地址: https://github.com/phpredis/phpredis/downloads 2.修改php.ini,增加下面两项 ...

  9. .net 账号异地登录

    第一步:给用户名一个对应的字段记录登陆状态,比如 online , 登陆后就为1, 同时还应增加记录用户活动时间,比如actionTime, 在基类(比如初始化Conn的类), 加上 update [ ...

  10. Gson解析json字符串

    // 解析传递过来的json字符串 JsonParser parser = new JsonParser(); JsonObject jsonObj = parser.parse(strJson).g ...