注册 登录  
 加关注
   显示下一条  |  关闭
温馨提示!由于新浪微博认证机制调整,您的新浪微博帐号绑定已过期,请重新绑定!立即重新绑定新浪微博》  |  关闭

云之南

风声,雨声,读书声,声声入耳;家事,国事,天下事,事事关心

 
 
 

日志

 
 
关于我

专业背景:计算机科学 研究方向与兴趣: JavaEE-Web软件开发, 生物信息学, 数据挖掘与机器学习, 智能信息系统 目前工作: 基因组, 转录组, NGS高通量数据分析, 生物数据挖掘, 植物系统发育和比较进化基因组学

网易考拉推荐

聚类 去冗余software  

2011-07-28 20:19:39|  分类: 生信分析软件 |  标签: |举报 |字号 订阅

  下载LOFTER 我的照片书  |
http://www.bioinformatics.org/cd-hit/

http://weizhong-lab.ucsd.edu/cd-hit/

CD-HIT stands for Cluster Database at High Identity with Tolerance. The program (cd-hit) takes a fasta format sequence database as input and produces a set of 'non-redundant' (nr) representative sequences as output

TGICL:
http://compbio.dfci.harvard.edu/tgi/software/
http://sourceforge.net/projects/tgicl/

TGICL installation


http://seqanswers.com/forums/archive/index.php/t-15660.html

TGI Clustering tools (TGICL): a software system for fast clustering of large EST datasets
用tgicl先聚类,然后用phrap组装一次 (或者cap3)


blastcluster进行聚类

Uicluster
http://genome.uiowa.edu/pubsoft/software.html

UCLUST
http://www.drive5.com/uclust/downloads.html
http://www.drive5.com/usearch/index.html

About USEARCH
USEARCH is a unique high-throughput sequence analysis tool. It is a distributed as single binary program that implements a suite of algorithms comparable to BLASTN, BLASTP, BLASTX, BLASTCLUST, CD-HIT, CD-HIT-EST, CD-HIT-2D, CD-HIT-EST-2D, CD-HIT-OTU, CD-HIT-454, ChimeraSlayer, Perseus, RAPsearch and more. It supports a rich set of sequence matching options, including E-values, identity, coverage (fraction of query or target sequence covered by the alignment) and maximum gap length, and a range of output file formats including FASTA, BLAST-like, user-defined tabbed text and a native format designed for clustering applications. Supported alignment styles include local (gapped and ungapped), like BLAST, and global, which is most often used in clustering applications. User-settable parameters allow tuning of substitution scores, gap penalties and Karlin-Altschul statistics.


EST2UNI
http://cichlid.umd.edu/est2uni/

Sequence clustering

From Wikipedia, the free encyclopedia
Jump to: navigation, search

In bioinformatics, sequence clustering algorithms attempt to group sequences that are somehow related. The sequences can be either of genomic, "transcriptomic" (ESTs) or protein origin. For proteins, homologous sequences are typically grouped into families. For EST data, clustering is important to group sequences originating from the same gene before the ESTs are assembled to reconstruct the original mRNA.

Some clustering algorithms use single-linkage clustering, constructing a transitive closure of sequences with a similarity over a particular threshold. UCLUST and CD-HIT use a greedy algorithm that identifies a representative sequence for each cluster and assigns a new sequence to that cluster if it is sufficiently similar to the representative; if a sequence is not matched then it becomes the representative sequence for a new cluster. The similarity score is often based on sequence alignment. Sequence clustering is often used to make a non-redundant set of representative sequences.

Sequence clusters are often synonymous with (but not identical to) protein families. Determining a representative tertiary structure for each sequence cluster is the aim of many structural genomics initiatives.

External links

Sequence clustering packages

Non-redundant sequence databases

  评论这张
 
阅读(2798)| 评论(2)
推荐 转载

历史上的今天

在LOFTER的更多文章

评论

<#--最新日志,群博日志--> <#--推荐日志--> <#--引用记录--> <#--博主推荐--> <#--随机阅读--> <#--首页推荐--> <#--历史上的今天--> <#--被推荐日志--> <#--上一篇,下一篇--> <#-- 热度 --> <#-- 网易新闻广告 --> <#--右边模块结构--> <#--评论模块结构--> <#--引用模块结构--> <#--博主发起的投票-->
 
 
 
 
 
 
 
 
 
 
 
 
 
 

页脚

网易公司版权所有 ©1997-2016