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 that are displayed in an annotation track. BED lines have three required fields and nine additional optional fields. The number of fields per line must be consistent throughout any single set of data in an annotation track. The order of the optional fields is binding: lower-numbered fields must always be populated if higher-numbered fields are used. If your data set is BED-like, but it is very large and you would like to keep it on your own server, you should use the bigBed data format. The first three required BED fields are:
The 9 additional optional BED fields are:
Example: track name=pairedReads description="Clone Paired Reads" useScore=1 Example: browser position chr7:127471196-127495720 Example: browser position chr7:127471196-127495720 |
tophat输出结果junction.bed中定义的junction就是中间是intron两边是exon的这种序列结构, JUNC00000001包含两个exon和中间的intron
cat junctions.bed
track name=junctions description="TopHat junctions"
test_chromosome 177 400 JUNC00000001 61 + 177 400 255,0,0 2 73,50 0,173
test_chromosome 350 550 JUNC00000002 45 + 350 550 255,0,0 2 50,50 0,150

exon1: 177-250(display), 177-249(actual)
intron: 250-350(display), 250-349(actual)
exon2: 350-400(display), 350-399(actual)
chrom(test_chromosome): The name of the chromosome.
这里就是test_chromosome
chromStart(177): The starting position of the feature in the
chromosome or scaffold. The first base in a chromosome is numbered
0.
chromosome上feature(在这里就是junction)的起始位置
chromEnd(400): The ending position of the feature in the chromosome
or scaffold. The chromEnd base is not included in the display of
the feature. For example, the first 100 bases of a chromosome are
defined as chromStart=0, chromEnd=100, and span the bases numbered
0-99.
对应的终止位置
name(JUNC00000001): Defines the name of the BED line.
score(61): A score between 0 and 1000.
strand(+): Defines the strand: either '+' or '-'.
thickStart(177): The starting position at which the feature is
drawn thickly (for example, the start codon in gene
displays).
thickEnd(400): The ending position at which the feature is drawn
thickly (for example, the stop codon in gene displays).
itemRgb(255,0,0): An RGB value of the form R,G,B (e.g. 255,0,0). If
the track line itemRgb attribute is set to "On", this RBG value
will determine the display color of the data contained in this BED
line. NOTE: It is recommended that a simple color scheme (eight
colors or less) be used with this attribute to avoid overwhelming
the color resources of the Genome Browser and your Internet
browser.
blockCount(2): The number of blocks (exons) in the BED line.
外显子个数,2个
blockSizes(73,50): A comma-separated list of the block sizes. The
number of items in this list should correspond to
blockCount.外显子大小,两个数字用逗号隔开
blockStarts(0,173): A comma-separated list of block starts. All of
the blockStart positions should be calculated relative to
chromStart. The number of items in this list should correspond to
blockCount.
外显子起始位置,不从chromosome的起始开始,而是从chromStart开始数,也就是junction的起始位置开始计算,第一个碱基是0
用bed_to_junc转换后得到.juncs其中只保留了junction中intron的部分
cat new_list.juncs
test_chromosome 249 350 +
test_chromosome 399 500 +
<chrom> <left> <right> <+/->
http://genome.ucsc.edu/FAQ/FAQformat.html#format1
http://www.ensembl.org/info/website/upload/bed.html
http://zhongguozhanying.blog.163.com/blog/static/21618709520135484450746/
http://blog.sina.com.cn/s/blog_7cffd14001012rtd.html
https://github.com/WormBase/wormbase-pipeline/blob/master/scripts/align_RNASeq.pl
tophat输出结果junction.bed的更多相关文章
- 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 ...
- RNA-seq连特异性
RNA-seq连特异性 Oct 15, 2015 The strandness of RNA-seq analysis 前段时间一直在研究关于illumina TrueSeq stranded RNA ...
- 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 ...
- TopHat
What is TopHat? TopHat is a program that aligns RNA-Seq reads to a genome in order to identify exon- ...
- 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 ...
- poj 1041(字典序输出欧拉回路)
John's trip Time Limit: 1000MS Memory Limit: 65536K Total Submissions: 8641 Accepted: 2893 Spe ...
- 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 ...
- mapreduce多文件输出的两方法
mapreduce多文件输出的两方法 package duogemap; import java.io.IOException; import org.apache.hadoop.conf ...
- Android Studio 多个编译环境配置 多渠道打包 APK输出配置
看完这篇你学到什么: 熟悉gradle的构建配置 熟悉代码构建环境的目录结构,你知道的不仅仅是只有src/main 开发.生成环境等等环境可以任意切换打包 多渠道打包 APK输出文件配置 需求 一般我 ...
随机推荐
- DTCMS规格统一赋值
admin\article_edit.aspx 已经存在 市场价格 和销售价格统一赋值 //赋值规格市场价格 $("#field_control_market_price").bl ...
- Less和Sass编译
使用koala编译 Koala 是一款由国人开发的开源预处理语言图形编译工具,目前已支持 Less.Sass.Compass 与CoffeeScript. 目前支持以下系统:Windows,Mac, ...
- 四个基数任意次数组合相加得到一个数N,求所有可能组合
#include <iostream> #include <vector> usingnamespace std; vector<int> vec; constin ...
- (转)《深入理解java虚拟机》学习笔记9——并发编程(一)
随着多核CPU的高速发展,为了充分利用硬件的计算资源,操作系统的并发多任务功能正变得越来越重要,但是CPU在进行计算时,还需要从内存读取输出,并将计算结果存放到内存中,然而由于CPU的运算速度比内存高 ...
- IOS 学习教程
IOS 学习教程http://www.gaixue.com/course/236#### 讲课http://wenku.baidu.com/view/6786064fe518964bcf847c63. ...
- 【MongoDB】 安装为windows services
参考 http://stackoverflow.com/questions/2404742/how-to-install-mongodb-on-windows # mongodb.conf # da ...
- String声明为NULL和""的区别
代码虐我千百遍,我待代码如初恋. String 声明为 NULL 则声明了一个变量不指向任何一块地址,则 length()会出现错误. 声明为"",则是一个长度为0的字符串.
- unity手游之聊天SDK集成与使用二
集成思路 如果是自己的小游戏的话,可以把好友等信息直接保存在亲加服务器上,通过调用api来操作. 我们游戏只使用sdk的通信功能,好友等信息保存在自己的服务器上. 用户在登陆游戏的时候,通过算法用用户 ...
- 小小地预览HTML5
程序示例 <!doctype html> <html> <head> <title>First </title> <meta char ...
- 解决Oracle ORA-00984: column not allowed here
某列是字符列,结果忘记加单引号了 INSERT INTO prt_document_present (company_code, doc_no, seq_no, field_name, desc_ms ...