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生物信息学上HMMER、HMM、Pfam的使用
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这个帖子发布于4年零300天前，其中的信息可能已发生改变或有所发展。
我现在正在使用HMMER的Windows版的，文献上有如下语句：Predicted open reading frames(ORFs) from the annotation of S. tuberosum group Phureja assembly V3 were screened using HMMER V.3() against the raw hidden Markov model (HMM) corresponding to the Pfam NBS (NB-ARC) family (PF00931). The HMMws downloaded from the Pfam home page (). The analysis using the raw HMM of the NBS domain resulted in 351 candidates.我想根据文献中的方法去分析，已经把HMMER V.3的Windows版本下下来了，可是里面的*.exe文件都没法打开。还有HMM也不知道如何从Pfam上下载。请高手指点！谢谢！文献：Genome sequence and analysis of the tuber crop potato, Nature.
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HMM是一种建立预测模型的算法。不知道楼主准备应用HMM做哪方面的研究。楼主提到的.exe文件是已经建立好的模型，可能不适合你的研究。
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谢谢！我已经会使用用HMMER做简单的基因组分析了，不过现在又遇到了一个问题，还望大家赐教！下面是文献中拟南芥的分析方法：Identification and Classification of NBS-LRR–Encoding GenesThe complete set of NBS-encoding sequences was identified from the Arabidopsis genome of ecotype Col-0 in a reiterative process (Table 1, Figure 1). Four analytical steps were used to compile the final set of sequences. First, a set of 159 genes with the NBS motif was selected from the complete set of predicted Arabidopsis proteins (http://mips.gsf.de) using a hidden Markov model (HMM) (Eddy, 1998) for the NBS domain from the Pfam database (PF0931; ).In the second analytical step, selected protein sequences were aligned based only on the NBS domain using CLUSTAL W. This alignment then was used to develop an Arabidopsisspecific HMM model to identify related sequences. The refined HMM was compared again against the complete set of predicted Arabidopsis proteins. All sequences that matched the model with a score of 0.05 or greater were incorporated into the HMM. The refined HMM was compared again with the entire set of Arabidopsis open reading frames (ORFs) with the threshold for acceptance decreased to 0.001. The 10 sequences with scores just above this threshold and the 15 sequences with scores just below this threshold were analyzed for the presence of the TIR, NBS, or LRR motifs using Pfam andvisual inspection. Four of the 10 sequences just above the 0.001 threshold value did not contain TIR, NBS, or LRR motif all sequences above these 10 contained NBS motifs. Below this threshold, only 2 of the next 15 proteins contained the NBS motif by Pfam analysis and therefore were retained in the analysis. The remaining 13 low-scoring proteins were either predominantly LRRs or were receptor- all lacked any recognizable NBS motifs. This analysis identified 194 annotated genes that encoded homologs of NBS-LRR R proteins.就是利用HMMER和pfam在基因组中进行一轮一轮的搜索，我不明白的是红色标出的部分，即：进行完一轮一轮的搜索后，选出了threshhold上面的10个和下面的15个进行pfam analysis，我想问一下大家有没有人懂得这个pfam analysis应该是如何进行的？因为HMMER分析本身就是基于pfam数据库的，而之后又单独拿出这10个和15个，依然进行pfam分析，应该怎么分析和操作呢？希望高手指点！
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The Pfam database is a large collection of protein
families, each represented by multiple sequence alignments
and hidden Markov models (HMMs)。首先文献中的所谓10个，15个是用作者自己建立的HMM model筛选出来的，建立方法文中也有提到。之后，他再将这些筛选出来的，去用Pfam上的HMM model去检查有没有常见的几个motif吧
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KLCG 我现在正在使用HMMER的Windows版的，文献上有如下语句：Predicted open reading frames(ORFs) from the annotation of S. tuberosum group Phureja assembly V3 were screened using HMMER V.3() against the raw hidden Markov model (HMM) corresponding to the Pfam NBS (NB-ARC) family (PF00931). The HMMws downloaded from the Pfam home page (). The analysis using the raw HMM of the NBS domain resulted in 351 candidates.我想根据文献中的方法去分析，已经把HMMER V.3的Windows版本下下来了，可是里面的*.exe文件都没法打开。还有HMM也不知道如何从Pfam上下载。请高手指点！谢谢！文献：Genome sequence and analysis of the tuber crop potato, Nature.我的HMMER下载解压后，也是.exe打不开，求问楼主后来怎么解决的呢，谢谢了，急用HMMER~
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请问楼主解压后怎么安装运行
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你好 我也在苦于学习HMMER。同样的我下下来了HMMER3.1的压缩文件，解压后不知道怎么应用！求解！谢谢！
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你好,我跟你碰到了相同的问题,就是用windows打不开hmmer里面的文件,应该怎么弄呢?多谢赐教!
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你好，能请教下hmmer怎么用么？
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在http://hmmer.janelia.org/software网站上，下载了hmmer-3.1b1-cygwin.tar.gz这个文件，应该是windows版的用法吧，可是就没有exe文件啊，请问这个怎么安装使用的？
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windows下应该不需要cygwin (营造Linux环境的)打开DOS （附件—》命令提示符）切换到hmm目录下，并运行hmm子程序如hmmsearch。输入hmmseach pf123.hmm InputSeq.fas &OutResults
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你好，我想问下 the raw HMM of the NBS domain ，这个是在哪里找的。最近我也在看这篇文献，有许多问题，还希望能多多指教。
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你好，可以加你交流基因组分析吗？××××
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dachong99 edited on
你好，我也在做基因组分析，HMMER不会呀，可不可以交流下呢
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你搞懂了什么原因了吗？请教
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你好，我下载的HMMER也是exe程序打不开，应该怎么办？
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您好，我最近也开始研究生物信息学，想问您一下 如何在pfam 上下载HMM模型啊？还有这个模型在HMMER上如何进行比对啊?
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您好 想请教您一下如何在pfam
上下载HMM profile 啊
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3秒自动关闭窗口hmmbuild - build a profile HMM from an alignment
User's Guide
[options] hmmfile alignfile
reads a multiple
sequence alignment file
alignfile , builds a new profile HMM, and saves
the HMM in
alignfile may be in ClustalW, GCG MSF, or SELEX alignment
By default, the model is configured to find one or more nonoverlapping
alignments to the complete model. This is analogous to the behavior of
program of HMMER 1. To configure the model for a single global
alignment, use the
-g to configure the model for multiple local
alignments a la the old program hmmfs, use the -f
and to configure
the model for a single local alignment (a la standard Smith/Waterman,
or the old hmmsw program), use the -s
] Configure the
model for finding multiple domains per sequence, where each domain can
be a local (fragmentary) alignment. This is analogous to the old hmmfs
program of HMMER 1.
] Configure the model for finding a single global
alignment to a target sequence, analogous to the standard Needleman/Wunsch
algorithm or the old hmms program of HMMER 1.
] P includes
version number and summary of all options, including expert options.
] Name this HMM &s&.
&s& can be any string of non-whitespace characters (e.g.
one "word"). There is no length limit (at least not one imposed by HMMER;
your shell will complain about command line lengths first).
the starting alignment to
&f&, in SELEX format. The columns which were assigned
to match states will be marked with x's in an #=RF annotation line.
either the -hand
-fast construction options were chosen, the alignment
may have been slightly altered to be compatible with Plan 7 transitions,
so saving the final alignment and comparing to the
starting alignment
can let you view these alterations. See the User's Guide for more information
on this arcane side effect.
] Configure the model for finding a single
local alignment per target sequence. This is analogous to the standard
Smith/Waterman algorithm or the
hmmsw program of HMMER 1.
this model to an existing hmmfile rather than creating
hmmfile. Useful
for building HMM libraries (like Pfam).
] Force overwriting of an existing
hmmfile. Otherwise HMMER will refuse to clobber your existing HMM files,
for safety's sake.
] Force the sequence alignment
to be interpreted as amino acid sequences. Normally HMMER autodetects whether
the alignment is protein or DNA, but sometimes alignments are so small
that autodetection is ambiguous. See -nucleic.
[-archpri &x&
] Set the "architecture
prior" used by MAP architecture construction to
&x&, where
&x& is a probability
between 0 and 1. This parameter governs a geometric prior distribution
over model lengths. As &x&
increases, longer models are favored a priori.
&x& decreases, it takes more residue conservation in a column to make
a column a "consensus" match column in the model architecture. The 0.85
default has been chosen empirically as a reasonable setting.
the HMM to hmmfile in HMMER binary format instead of readable ASCII text.
[-cfile &f&
] Save the observed emission and transition counts to
the architecture has been determined (e.g. after residues/gaps have been
assigned to match, delete, and insert states). This option is used in HMMER
development for generating data files useful for training new Dirichlet
priors. The format of count files is documented in the User's Guide.
] Quickly and heuristically determine the architecture of the model by
assigning all columns will more than a certain fraction of gap characters
to insert states. By default this fraction is 0.5, and it can be changed
using the -gapmax option. The default construction algorithm is a maximum
a posteriori (MAP) algorithm, which is slower.
[-gapmax &x&
] Controls the
-fast model construction algorithm, but if
-fast is not being used, has
no effect. If a column has more than a fraction &x& of gap symbols in it,
it gets assigned to an insert column. &x&
is a frequency from 0 to 1, and
by default is set to 0.5. Higher values of &x& mean more columns get assigned
to consensus, a smaller values of
mean fewer
columns get assigned to consensus, and models get smaller. &x&
the architecture of the model by hand: the alignment file must be in SELEX
format, and the #=RF annotation line is used to specify the architecture.
Any column marked with a non-gap symbol (such as an 'x', for instance) is
assigned as a consensus (match) column in the model.
[-idlevel &x&
] Controls
both the determination of effective sequence number and the behavior of
weighting option. The sequence alignment is clustered by
percent identity, and the number of clusters at a cutoff threshold of
is used to determine the effective sequence number. Higher values of
give more clusters and higher effect lower values
give fewer clusters and lower effective sequence numbers. &x&
a fraction from 0 to 1, and
by default is set to 0.62 (corresponding to
the clustering level used in constructing the BLOSUM62 substitution matrix).
] Turn off the effective sequence number calculation, and use the
true number of sequences instead. This will usually reduce the sensitivity
of the final model (so don't do it without good reason!)
the alignment to be interpreted as nucleic acid sequence, either RNA or
DNA. Normally HMMER autodetects whether the alignment is protein or DNA,
but sometimes alignments are so small that autodetection is ambiguous.
See -amino.
[-null &f&
] Read a null model from
&f&. The default for protein is
to use average amino acid frequencies from Swissprot 34 and p1 = 350/351;
for nucleic acid, the default is to use 0.25 for each base and p1 = .
For documentation of the format of the null model file and further explanation
of how the null model is used, see the User's Guide.
] Apply a heuristic
PAM- (substitution matrix-) based prior instead of the default mixture Dirichlet.
The substitution matrix is read from
[-pamwgt &x&
] Controls
the weight on a PAM-based prior. Only has effect if -pam
option is also
&x& is a positive real number, 20.0 by default.
&x& is the number of
"pseudocounts" contriubuted by the heuristic prior. Very high values of
can force a scoring system that is entirely driven by the substitution
matrix, making HMMER somewhat approximate Gribskov profiles.
[-prior &f&
] Read a Dirichlet prior from
replacing the default mixture Dirichlet.
The format of prior files is documented in the User's Guide, and an example
is given in the Demos directory of the HMMER distribution.
[-swentry &x&
] Controls the total probability that is distributed to local entries into
the model, versus starting at the beginning of the model as in a global
alignment. &x& is a probability from 0 to 1, and by default is set to 0.5.
Higher values of &x& mean that hits that are fragments on their left (N
or 5'-terminal) side will be penalized less, but complete global alignments
will be penalized more. Lower values of &x& mean that fragments on the left
will be penalized more, and global alignments on this side will be favored.
This option only affects the configurations that allow local alignments,
-s and -f; unless one of these options is also activated, this option
has no effect. You have independent control over local/global alignment
behavior for the N/C (5'/3') termini of your target sequences using
and -swexit.
[-swexit &x&
] Controls the total probability that is distributed
to local exits from the model, versus ending an alignment at the end of
the model as in a global alignment. &x& is a probability from 0 to 1, and
by default is set to 0.5. Higher values of &x& mean that hits that are fragments
on their right (C or 3'-terminal) side will be penalized less, but complete
global alignments will be penalized more. Lower values of &x& mean that fragments
on the right will be penalized more, and global alignments on this side
will be favored. This option only affects the configurations that allow
local alignments, e.g.
-s and -f; unless one of these options is also activated,
this option has no effect. You have independent control over local/global
alignment behavior for the N/C (5'/3') termini of your target sequences
-swentry and -swexit.
] Print more possibly useful stuff,
such as the individual scores for each sequence in the alignment.
] Use the BLOSUM filtering algorithm to weight the sequences, instead of
the default. Cluster the sequences at a given percentage identity (see
-idlevel); assign each cluster a total weight of 1.0, distributed equally
amongst the members of that cluster.
] Use the Gerstein/Sonnhammer/Chothia
ad hoc sequence weighting algorithm. This is already the default, so this
option has no effect (unless it follows another option in the -w family,
in which case it overrides it).
] Use the Krogh/Mitchison maximum entropy
algorithm to "weight" the sequences. This supercedes the Eddy/Mitchison/Durbin
maximum discrimination algorithm, which gives almost identical weights
but is less robust. ME weighting seems
to give a marginal increase in
sensitivity over the default GSC weights, but takes a fair amount of time.
] Turn off all sequence weighting.
[-wvoronoi
] Use the Sibbald/Argos
Voronoi sequence weighting algorithm in place of the default GSC weighting.
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