fasta3x.doc

序列对齐 Compare a protein sequence to a protein sequence database or a DNA sequence to a DNA sequenc

    #

    You do not need to include library format numbers if  you
    only use the Pearson/FASTA version of the PIR protein se-
    quence library.  If no library  type  is  specified,  the
    program assumes that type 0 is being used.

     Test the setup by running FASTA.  Enter the sequence file
'mgstm1.aa' when the program requests it (this file is included
with the programs).  The program should then ask you to select a
protein sequence library.  Alternatively, if you run the TFASTA
program and use the mgstm1.aa query sequence, the program should
show you a selection of DNA sequence libraries.  Once the fastgbs
file has been set up correctly, you can set FASTLIBS=fastgbs in
your AUTOEXEC.BAT file, and you will not need to remember where
the libraries are kept or how they are named.

3.  Using the FASTA Package

3.1.  Overview

     The FASTA sequence comparison programs all require similar
information, the name of a query sequence file, a library file,
and the ktup parameter.  All of the programs can accept arguments
on the command line, or they will prompt for the file names and
ktup value.

To use FASTA, simply type:

    FASTA
    and you will be prompted for :
         the name of the test sequence file
         the name of the library file
         and whether you want ktup = 1 or 2. (or 1 to 6 for DNA sequences)
         (ktup of 2 is about 5 times faster than ktup = 1)

The program can also be run by typing

    FASTA test.aa /lib/bigfile.lib ktup (1 or 2)

Included with the package are several test files.  To check to
make certain that everything is working, you can try:

    fasta musplfm.aa prot_test.lib
    and
    tfastx mgstm1.aa gst.nlib

3.2.  Sequence files

     The fasta3 programs know about three kinds of sequence
files: (1) plain sequence files - files that contain nothing but
sequence residues - can only be used as query sequences. (2)
FASTA format files.  These are the same as plain sequence files,
each sequence is preceded by a comment line with a '>' in the
first column. (3) distributed sequence libraries (this is a broad
class that includes the NBRF/PIR VMS and blocked ascii formats,
Genbank flat-file format, EMBL flat-file format, and
Intelligenetics format.  All of the files that you create should
be of type (1) or (2).  FASTA format files (ones with a '>' and
comment before the sequence) are preferred, because they can be
used as query or library sequence files by all of the programs.

     I have included several sample test files, *.aa and *.seq as
well as two small sequence libraries, prot_test.lib and gst.nlib.
The first line may begin with a '>' by a comment.  Spaces and
tabs (and anything else that is not an amino-acid code) are
ignored.

     Library files should have the form:

    >Sequence name and identifier
    A F A S Y T .... actual sequence.
    F S S       .... second line of sequence.
    >Next sequence name and identifier

This is often referred to as "FASTA" or format.  You can build
your own library by concatenating several sequence files.  Just
be sure that each sequence is preceded by a line beginning with a
'>' with a sequence name.

     The test file should not have lines longer than 120
characters, and sequences entered with word processors should use
a document mode, with normal carriage returns at the end of
lines.

     A different format is required to specify the ordered
peptide mixture for fastf3/tfastf3. For example:

    >mgstm1
    MGCEN,
    MIDYP,
    MLLAY,
    MLLGY

indicates m in the first position of all three peptides (as from
CNBr), G, I, L (twice) in the second position (first cycle),
C,D,L (twice) in the third position, etc.  The commas (,) are
required to indicate the number of fragments in the mixture, but
there should be no comma after the last residue.

     For the fasts3/tfasts3 program, the format is the same,
except that there is no requirement for the peptides to be the
same length.

4.  Statistical Significance

     All the programs in the FASTA3 package attempt to calculate
accurate estimates of the statistical significance of a match.
For fasta3, ssearch3, and fastx3/y3, these estimates are very
accurate (Pearson, 1998, Zhang et al., 1997)..  Altschul et al.
(Altschul et al., 1994) provides an excellent review of the
statistics of local similarity scores.  Local sequence similarity
scores follow the extreme value distribution, so that P(s > x) =
1 - exp(-exp(-lambda(x-u)) where u = ln(Kmn)/lambda and m,m are
the lengths of the query and library sequence. This formula can
be rewritten as: 1 - exp(-Kmn exp(-lambda x), which shows that
the average score for an unrelated library sequence increases
with the logarithm of the length of the library sequence.  The
fasta3 programs use simple linear regression against the the log
of the library sequence length to calculate a normalized "z-
score" with mean 50, regardless of library sequence length, and
variance 10. (Several other estimation methods are available with
the -z option.) These z-scores can then be used with the extreme
value distribution and the poisson distribution (to account for
the fact that each library sequence comparison is an independent
test) to calculate the number of library sequences to obtain a
score greater than or equal to the score obtained in the search.
The original idea and routines to do the linear regression on
library sequence length were provided Phil Green, U. Washington.
This version uses a slightly different strategy for fitting the
data than those originally provided by Dr. Green.

     The expected number of sequences is plotted in the histogram
using an "*". Since the parameters for the extreme value
distribution are not calculated directly from the distribution of
similarity scores, the pattern of "*'s" in the histogram gives a
qualitative view of how well the statistical theory fits the
similarity scores calculated by the programs.  For fasta3, if
optimized scores are calculated for each sequence in the database
(the default), the agreement between the actual distribution of
"z-scores" and the expected distribution based on the length
dependence of the score and the extreme value distribution is
usually very good.  Likewise, the distribution of ssearch3 Smith-
Waterman scores typically agrees closely with the <actual
distribution of "z-scores."  The agreement with unoptimized
scores, ktup=2, is often not very good, with too many high
scoring sequences and too few low scoring sequences compared with
the predicted relationship between sequence length and similarity
score.  In those cases, the expectation values may be
overestimates.

     With version 33t01, all the FASTA programs also report a
"bit" score, which is equivalent to the bit score reported by
BLAST2.  The FASTA33/BLAST2 bit score is calculated as: (lambda*S
- ln K)/ln 2, where S is the raw similarity score, lambda and K
are statistical parameters estimated from the distribution of
unrelated sequence similarity scores.  The statistical
signficance of a given bit score depends on the lengths of the
query and library sequences and the size of the library, but a 1
bit increase in score corresponds to a 2-fold reduction in
expectation; a 10-bit increase implies 1000-fold lower
expectation, etc.

     The statistical routines assume that the library contains a
large sample of unrelated sequences.  If this is not true, then
statistical parameters can be estimated by using the -z 11-15,
options.  -z options greater than 10 calculate a shuffled
similarity score for each library sequence, in addition to the
unshuffled score, and estimate the statistical parameters from
the scores of the shuffled sequences.  If there are fewer than 20
sequences in the library, the statistical calculations are not
done.

     For protein searches, library sequences with E() values <
0.01 for searches of a 10,000 entry protein database are almost
always homologous. Frequently sequences with E()-values from 1 -
10 are related as well, but unrelated sequences ( 1 - 10 per
search) will have scores in this renage as well. Remember,
however, that these E() values also reflect differences between
the amino acid composition of the query sequence and that of the
"average" library sequence.  Thus, when searches are done with
query sequences with "biased" amino-acid composition, unrelated
sequences may have "significant" scores because of sequence bias.
PRSS3 can address this problem by calculating similarity scores
for random sequences with the same length and amino acid
composition.

5.  Options

     Command line options are available to change the scoring
parameters and output display. Command line options must preceed
other program arguments, such as the query and library file
names.

5.1.  Command line options

-a   (fasta3, ssearch3 only) show both sequences in their
     entirety.

-A   force Smith-Waterman alignments for fasta3 DNA sequences.
     By default, only fasta3 protein sequence comparisons use
     Smith-Waterman alignments.

-B   Show normalized score as a z-score, rather than a bit-score
     in the list of best scores.

-b # Number of sequence scores to be shown on output.  In the
     absence of this option, fasta (and tfasta and ssearch)
     display all library sequences obtaining similarity scores
     with expectations less than 10.0 if optimized score are
     used, or 2.0 if they are not. The -b option can limit the
     display further, but it will not cause additional sequences
     to be displayed.

-c # Threshold score for optimization (OPTCUT).  Set "-c 1" to
     optimize every sequence in a database.

-E # Limit the number of scores and alignments shown based on the
     expected number of scores.  Used to override the expectation
     value of 10.0 used by default.  When used with -Q, -E 2.0
     will show all library sequences with scores with an
     expectation value <= 2.0.

-d # Maximum number of alignments to be displayed.  Ignored if
     "-Q" is not used.

-f   Penalty for the first residue in a gap (-12 by default for
     proteins, -16 for DNA, -15 for FAST[XY]/TFAST[XY]).

-F # Limit the number of scores and alignments shown based on the
     expected number of scores. "-E #" sets the highest E()-value
     shown; "-F #" sets the lowest E()-value. Thus, "-F 0.0001"
     will not show any matches or alignments with E() < 0.0001.
     This allows one to skip over close relationships in searches
     for more distant relationships.

-g   Penalty for additional residues in a gap (-2 by default for
     proteins, -4 for DNA, -3 for FAST[XY]/TFAST[XY]).

-h   Penalty for frameshift (fastx3/y3, tfastx3/y3 only).

-H   Omit histogram.

-i   Invert (reverse complement) the query sequence if it is DNA.
     For tfasta3/x3/y3, search the reverse complement of the
     library sequence only.

-j # Penalty for frameshift within a codon (fasty3/tfasty3 only).

-l file
     Location of library menu file (FASTLIBS).

-L   Display more information about the library sequence in the
     alignment.

-M low-high
     Range of amino acid sequence lengths to be included in the
     search.

-m # Specify alignment type: 0, 1, 2, 3, 4, 5, 6, 9, 10

             -m 0        -m 1          -m 2          -m 3        -m 4
         MWRTCGPPYT   MWRTCGPPYT    MWRTCGPPYT                 MWRTCGPPYT
         ::..:: :::     xx  X       ..KS..Y...    MWKSCGYPYT   ----------
         MWKSCGYPYT   MWKSCGYPYT

     -m 5 provides a combination of -m 4 and -m 0. -m 6 provides
     -m 5 plus HTML formatting.

-m 9 provides coordinates and scores with the best score
     information.  A simple " -m 9 extends the normal best score
     information:

         The best scores are:                                      opt bits E(14548)
         XURTG4 glutathione transferase (EC 2.5.1.18) 4 -   ( 219) 1248 291.7 1.1e-79

     to include the additional information (on the same line,
     separated by a <tab>):

         %_id  %_gid   sw  alen  an0  ax0  pn0  px0  an1  ax1 pn1 px1 gapq gapl  fs
         0.771 0.771 1248  218    1  218    1  218    1  218    1  219   0   0   0

      -m 9c provides additional information: an encoded alignment
     string.  Thus:

                10        20        30        40        50          60         70
         GT8.7  NVRGLTHPIRMLLEYTDSSYDEKRYTMGDAPDFDRSQWLNEKFKL--GLDFPNLPYL-IDGSHKITQ
                :.::  . :: ::  .   .:::         : .:    ::.:   .: : ..:.. :::  :..:
         XURTG  NARGRMECIRWLLAAAGVEFDEK---------FIQSPEDLEKLKKDGNLMFDQVPMVEIDG-MKLAQ
                        20        30                 40        50        60

     would be encoded:

         =23+9=13-2=10-1=3+1=5

     The alignment encoding is with repect to the alignment, not
     the sequences.  The coordinate of the alignment is given
     earlier in the " -m 9c" line.

-m 10
     -m 10 is a new, parseable format for use with other
     programs.  See the file "readme.v20u4" for a more complete
     description.

     As of version "fa34t23b2", it has become possible to combine
     independent "-m" options.  Thus, one can use "-m 1 -m 6 -m
     9".

-M low-high
     Include library sequences (proteins only) with lengths
     between low and high.

-n   Force the query sequence to be treated as a DNA sequence.
     This is particularly useful for query sequences that contain
     a large number of ambiguous residues, e.g. transcription
     factor binding sites.

-O   Send copy of results to "filename."  Helpful for