怎么使用hmmer比对多个query基因_百度知道
怎么使用hmmer比对多个query基因
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hmmer下载与安装对于Mac OS/X, Linux, UNIX系统，用源代码编译安装：% wget ftp://selab.janelia.org/pub/software/hmmer3/3.0/hmmer-3.0.tar.gz % tar zxf hmmer-3.0.tar.gz % cd hmmer-3.0 % ./configure % make % make checkwindows系统，直接下载二进制压缩包，解压就可以使用。hmmer包含的程序phmmer： 与Blastp类似，使用一个蛋白质序列搜索蛋白质序列库；& phmmer tutorial/HBB HUMAN uniprot sprot.fajackhmmer： 与psiBlast类似，蛋白质序列迭代搜索蛋白质序列库；& jackhmmer tutorial/HBB HUMAN uniprot sprot.fahmmbuild： 用多重比对序列构建HMM模型；hmmsearch： 使用HMM模型搜索序列库；hmmscan： 使用序列搜索HMM库；hmmalign： 使用HMM为线索，构建多重比对序列；& hmmalign globins4.hmm tutorial/globins45.fahmmconvert： 转换HMM格式hmmemit： 从HMM模型中，得到一个模式序列；hmmfetch： 通过名字或者接受号从HMM库中取回一个HMM模型；hmmpress：格式化HMM数据库，以便于hmmscan搜索使用；hmmstat： 显示HMM数据库的统计信息；使用HMM模型搜索序列数据库使用hmmbuild构建HMM模型，输入为Stockholm格式或者FASTA格式的多重比对序列文件（如：tutorial/globins4.sto），命令如下：& hmmbuild globins4.hmm tutorial/globins4.stoglobins4.hmm为输出的HMM模型使用hmmsearch搜索蛋白质序列数据库，蛋白质序列数据库为FASTA格式，命令如下：& hmmsearch globins4.hmm uniprot sprot.fasta & globins4.outglobins4.out为输出的结果文件，如下：*示例使用官方教程中的示例使用蛋白质序列搜索HMM数据库构建HMM数据库，HMM数据库是包含多个HMM模型的文件，可以从Pfam、SMART、TIGRFams下载，也可以自己由多重比对序列集中构建，如：& hmmbuild globins4.hmm tutorial/globins4.sto& hmmbuild fn3.hmm tutorial/fn3.sto& hmmbuild Pkinase.hmm tutorial/Pkinase.sto& cat globins4.hmm fn3.hmm Pkinase.hmm & minifam使用hmmpress格式化数据库，包括压缩以及创建索引，命令如下：& hmmpress minifam这个步骤可以很快的执行完成，输出的内容如下：Working… done.Pressed and indexed 3 HMMs (3 names and 2 accessions).Models pressed into binary file: minifam.h3mSSI index for binary model file: minifam.h3iProfiles (MSV part) pressed into: minifam.h3fProfiles (remainder) pressed into: minifam.h3p使用hmmscan搜索HMM数据库，命令如下：& hmmscan minifam tutorial/7LESS_DROME
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Enables programmatic parsing of HMMER version 3 reports
Christian Zmasek, Ben J Woodcroft
7fe415b44ed45eaa899a6b9a0caf70f6e3feefd9e(PDF) HMM-ModE: implementation, benchmarking and validation with HMMER3
See all >4 CitationsSee all >37 ReferencesSee all >3 Figures
12.64Agency for Science, Technology and Research (A*STAR)28.86Jawaharlal Nehru UniversityBackground
HMM-ModE is a computational method that generates family specific profile HMMs using negative training sequences. The method optimizes the discrimination threshold using 10 fold cross validation and modifies the emission probabilities of profiles to reduce common fold based signals shared with other sub-families. The protocol depends on the program HMMER for HMM profile building and sequence database searching. The recent release of HMMER3 has improved database search speed by several orders of magnitude, allowing for the large scale deployment of the method in sequence annotation projects. We have rewritten our existing scripts both at the level of parsing the HMM profiles and modifying emission probabilities to upgrade HMM-ModE using HMMER3 that takes advantage of its probabilistic inference with high computational speed. The method is benchmarked and tested on GPCR dataset as an accurate and fast method for functional annotation.
The implementation of this method, which now works with HMMER3, is benchmarked with the earlier version of HMMER, to show that the effect of local-local alignments is marked only in the case of profiles containing a large number of discontinuous match states. The method is tested on a gold standard set of families and we have reported a significant reduction in the number of false positive hits over the default HMM profiles. When implemented on GPCR sequences, the results showed an improvement in the accuracy of classification compared with other methods used to classify the familyat different levels of their classification hierarchy.
Conclusions
The present findings show that the new version of HMM-ModE is a highly specific method used to differentiate between fold (superfamily) and function (family) specific signals, which helps in the functional annotation of protein sequences. The use of modified profile HMMs of GPCR sequences provides a simple yet highly specific method for classification of the family, being able to predict the sub-family specific sequences with high accuracy even though sequences share common physicochemical characteristics between sub-families.Discover the world's research15+ million members118+ million publications700k+ research projects
Content uploaded by Author content-483.pdf912 BSorry, there is no online preview for this file type.
ArticleJun 2016ChapterSep 2016ArticleFull-text availableJun 2017eLifeArticleFull-text availableAug 2017Mol Med RepProject[...]ProjectA generic platform for the analysis of high-throughput transcriptomics, proteomics and metabolomics data. Project[...]ProjectTo understand the mechanism of the various steps involved in GPI biosynthesis.
To perform a in-depth sequence analysis of all the enzymes and various other auxillary factors involved in the process. ArticleAugust 2013 · G-protein-coupled receptors (GPCRs) constitute a remarkable protein family of receptors that are involved in a broad range of biological processes. A large number of clinically used drugs elicit their biological effect via a GPCR. Thus, developing a reliable computational method for predicting the functional roles of GPCRs would be very useful in the pharmaceutical industry. Nowadays,... [Show full abstract]ArticleOctober 2009 · G-Protein Coupled Receptors (GPCR) are the largest family of membrane bound receptor and plays a vital role in various biological
processes with their amenability to drug intervention. They are the spotlight for the pharmaceutical industry. Experimental methods are both
time consuming and expensive so there is need to develop a computational approach for classification to expedite the drug... [Show full abstract]ArticleJuly 2006 · As the potential drug targets, G-protein coupled receptors (GPCRs) and nuclear receptors (NRs) are the focuses in pharmaceutical research. It is of great practical significance to develop an automated and reliable method to facilitate the identification of novel receptors. In this study, a method of fast Fourier transform-based support vector machine was proposed to classify GPCRs and NRs from... [Show full abstract]Conference PaperDecember 2006G-protein coupled receptors (GPCRs) are a large superfam- ily of integral membrane proteins that transduce signals across the cell membrane. Because of that important property and other physiological roles undertaken by the GPCR family, they have been an important tar- get of therapeutic drugs. The function of many GPCRs is not known and accurate classication of GPCRs can help us to predict... [Show full abstract]&>&hmmer-3.0.tar.gz
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