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  EMBOSS: compseq
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<A HREF="/" ONMOUSEOVER="self.status='Go to the EMBOSS home page';return true"><img border=0 src="emboss_icon.jpg" alt="" width=150 height=48></a>
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<b><font size="+6">
compseq
</font></b>
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</table>
<br>&nbsp;
<p>


<H2>
    Function
</H2>
Count composition of dimer/trimer/etc words in a sequence
<H2>
    Description
</H2>

This takes a specified length of sequence and counts the number of
distinct subsequences of that length that there are in the input
sequence(s).

<p>

It can read in the result of a previous compseq analysis and use this
to set the expected frequencies of the subsequences.

<p>

Unless you tell 'compseq' otherwise, it expects each word to be equally
likely.  The 'Expected' frequency therefore of any dimer is 1/16 - this
is simply the inverse of the number of possible dimers (AA, AC, AG, AT,
CA, CC, CG, CT, GA, GC, GG, GT, TA, TC, TG, TT). 

<p>


Similarly, the 'Expected' frequency of any trimer is 1/64, etc. 

<p>


Obviously this is not the case in real sequences - there will be bias in
favour of some words. 

<p>


Compseq cannot otherwise guess what the 'Expected' frequency is.  You
can, however, tell it what the Expected frequencies are by giving
compseq the output of the analysis of another set of sequences, produced
by a previous compseq run. 

<p>

So you take a set of sequences that are representative of the type of
sequence you expect and you run compseq on it to get your expected
sequence frequencies. 

<p>

You then take the sequences you wish to investigate, run compseq on them
giving compseq the expected frequencies that you have established,
above.  You tell compseq what the file of expected frequencies is by
specifying it with '-infile filename' on the command-line. 

<H2>
    Usage
</H2>
<b>Here is a sample session with compseq</b>
<p>
To count the frequencies of dinucleotides in a file: 
<p>

<p>
<table width="90%"><tr><td bgcolor="#CCFFFF"><pre>

% <b>compseq tembl:x65923 -word 2 result3.comp </b>
Count composition of dimer/trimer/etc words in a sequence

</pre></td></tr></table><p>
<p>
<a href="#input.1">Go to the input files for this example</a><br><a href="#output.1">Go to the output files for this example</a><p><p>
<p>
<b>Example 2</b>
<p>
To count the frequencies of hexanucleotides, without outputting the results of hexanucleotides that do not occur in the sequence: 
<p>

<p>
<table width="90%"><tr><td bgcolor="#CCFFFF"><pre>

% <b>compseq tembl:x65923 -word 6 result6.comp -nozero </b>
Count composition of dimer/trimer/etc words in a sequence

</pre></td></tr></table><p>
<p>
<a href="#output.2">Go to the output files for this example</a><p><p>
<p>
<b>Example 3</b>
<p>
To count the frequencies of trinucleotides in frame 2 of a sequence and use a previously prepared compseq output to show the expected frequencies: 
<p>

<p>
<table width="90%"><tr><td bgcolor="#CCFFFF"><pre>

% <b>compseq tembl:x65923 -word 3 result3.comp -frame 2 -in prev.comp </b>
Count composition of dimer/trimer/etc words in a sequence

</pre></td></tr></table><p>
<p>
<a href="#input.3">Go to the input files for this example</a><br><a href="#output.3">Go to the output files for this example</a><p><p>

<H2>
    Command line arguments
</H2>

<table CELLSPACING=0 CELLPADDING=3 BGCOLOR="#f5f5ff" ><tr><td>
<pre>
   Standard (Mandatory) qualifiers:
  [-sequence]          seqall     Sequence(s) filename and optional format, or
                                  reference (input USA)
   -word               integer    [2] This is the size of word (n-mer) to
                                  count.
                                  Thus if you want to count codon frequencies,
                                  you should enter 3 here. (Integer from 1 to
                                  20)
  [-outfile]           outfile    [*.compseq] This is the results file.

   Additional (Optional) qualifiers (* if not always prompted):
   -infile             infile     This is a file previously produced by
                                  'compseq' that can be used to set the
                                  expected frequencies of words in this
                                  analysis.
                                  The word size in the current run must be the
                                  same as the one in this results file.
                                  Obviously, you should use a file produced
                                  from protein sequences if you are counting
                                  protein sequence word frequencies, and you
                                  must use one made from nucleotide
                                  frequencies if you are analysing a
                                  nucleotide sequence.
   -frame              integer    [0] The normal behaviour of 'compseq' is to
                                  count the frequencies of all words that
                                  occur by moving a window of length 'word' up
                                  by one each time.
                                  This option allows you to move the window up
                                  by the length of the word each time,
                                  skipping over the intervening words.
                                  You can count only those words that occur in
                                  a single frame of the word by setting this
                                  value to a number other than zero.
                                  If you set it to 1 it will only count the
                                  words in frame 1, 2 will only count the
                                  words in frame 2 and so on. (Integer 0 or
                                  more)
*  -[no]ignorebz       boolean    [Y] The amino acid code B represents
                                  Asparagine or Aspartic acid and the code Z
                                  represents Glutamine or Glutamic acid.
                                  These are not commonly used codes and you
                                  may wish not to count words containing them,
                                  just noting them in the count of 'Other'
                                  words.
*  -reverse            boolean    [N] Set this to be true if you also wish to
                                  also count words in the reverse complement
                                  of a nucleic sequence.
   -calcfreq           boolean    [N] If this is set true then the expected
                                  frequencies of words are calculated from the
                                  observed frequency of single bases or
                                  residues in the sequences.
                                  If you are reporting a word size of 1
                                  (single bases or residues) then there is no
                                  point in using this option because the
                                  calculated expected frequency will be equal
                                  to the observed frequency.
                                  Calculating the expected frequencies like
                                  this will give an approximation of the
                                  expected frequencies that you might get by
                                  using an input file of frequencies produced
                                  by a previous run of this program. If an
                                  input file of expected word frequencies has
                                  been specified then the values from that
                                  file will be used instead of this
                                  calculation of expected frequency from the
                                  sequence, even if 'calcfreq' is set to be
                                  true.
   -[no]zerocount      boolean    [Y] You can make the output results file
                                  much smaller if you do not display the words
                                  with a zero count.

   Advanced (Unprompted) qualifiers: (none)
   Associated qualifiers:

   "-sequence" associated qualifiers
   -sbegin1            integer    Start of each sequence to be used
   -send1              integer    End of each sequence to be used
   -sreverse1          boolean    Reverse (if DNA)
   -sask1              boolean    Ask for begin/end/reverse
   -snucleotide1       boolean    Sequence is nucleotide
   -sprotein1          boolean    Sequence is protein
   -slower1            boolean    Make lower case
   -supper1            boolean    Make upper case
   -sformat1           string     Input sequence format
   -sdbname1           string     Database name
   -sid1               string     Entryname
   -ufo1               string     UFO features
   -fformat1           string     Features format
   -fopenfile1         string     Features file name

   "-outfile" associated qualifiers
   -odirectory2        string     Output directory

   General qualifiers:
   -auto               boolean    Turn off prompts
   -stdout             boolean    Write standard output
   -filter             boolean    Read standard input, write standard output
   -options            boolean    Prompt for standard and additional values
   -debug              boolean    Write debug output to program.dbg
   -verbose            boolean    Report some/full command line options
   -help               boolean    Report command line options. More
                                  information on associated and general
                                  qualifiers can be found with -help -verbose
   -warning            boolean    Report warnings
   -error              boolean    Report errors
   -fatal              boolean    Report fatal errors
   -die                boolean    Report dying program messages

</pre>
</td></tr></table>
<P>
<table border cellspacing=0 cellpadding=3 bgcolor="#ccccff">
<tr bgcolor="#FFFFCC">
<th align="left" colspan=2>Standard (Mandatory) qualifiers</th>
<th align="left">Allowed values</th>
<th align="left">Default</th>
</tr>

<tr>
<td>[-sequence]<br>(Parameter 1)</td>
<td>Sequence(s) filename and optional format, or reference (input USA)</td>
<td>Readable sequence(s)</td>
<td><b>Required</b></td>
</tr>

<tr>
<td>-word</td>
<td>This is the size of word (n-mer) to count.
Thus if you want to count codon frequencies, you should enter 3 here.</td>
<td>Integer from 1 to 20</td>
<td>2</td>
</tr>

<tr>
<td>[-outfile]<br>(Parameter 2)</td>
<td>This is the results file.</td>
<td>Output file</td>
<td><i>&lt;*&gt;</i>.compseq</td>
</tr>

<tr bgcolor="#FFFFCC">
<th align="left" colspan=2>Additional (Optional) qualifiers</th>
<th align="left">Allowed values</th>
<th align="left">Default</th>
</tr>

<tr>
<td>-infile</td>
<td>This is a file previously produced by 'compseq' that can be used to set the expected frequencies of words in this analysis.
The word size in the current run must be the same as the one in this results file. Obviously, you should use a file produced from protein sequences if you are counting protein sequence word frequencies, and you must use one made from nucleotide frequencies if you are analysing a nucleotide sequence.</td>
<td>Input file</td>
<td><b>Required</b></td>
</tr>

<tr>
<td>-frame</td>
<td>The normal behaviour of 'compseq' is to count the frequencies of all words that occur by moving a window of length 'word' up by one each time.
This option allows you to move the window up by the length of the word each time, skipping over the intervening words.
You can count only those words that occur in a single frame of the word by setting this value to a number other than zero.
If you set it to 1 it will only count the words in frame 1, 2 will only count the words in frame 2 and so on.</td>
<td>Integer 0 or more</td>
<td>0</td>
</tr>

<tr>
<td>-[no]ignorebz</td>
<td>The amino acid code B represents Asparagine or Aspartic acid and the code Z represents Glutamine or Glutamic acid.
These are not commonly used codes and you may wish not to count words containing them, just noting them in the count of 'Other' words.</td>
<td>Boolean value Yes/No</td>
<td>Yes</td>
</tr>

<tr>
<td>-reverse</td>
<td>Set this to be true if you also wish to also count words in the reverse complement of a nucleic sequence.</td>
<td>Boolean value Yes/No</td>
<td>No</td>
</tr>

<tr>
<td>-calcfreq</td>
<td>If this is set true then the expected frequencies of words are calculated from the observed frequency of single bases or residues in the sequences.
If you are reporting a word size of 1 (single bases or residues) then there is no point in using this option because the calculated expected frequency will be equal to the observed frequency.
Calculating the expected frequencies like this will give an approximation of the expected frequencies that you might get by using an input file of frequencies produced by a previous run of this program. If an input file of expected word frequencies has been specified then the values from that file will be used instead of this calculation of expected frequency from the sequence, even if 'calcfreq' is set to be true.</td>
<td>Boolean value Yes/No</td>
<td>No</td>
</tr>

<tr>
<td>-[no]zerocount</td>
<td>You can make the output results file much smaller if you do not display the words with a zero count.</td>
<td>Boolean value Yes/No</td>
<td>Yes</td>
</tr>

<tr bgcolor="#FFFFCC">
<th align="left" colspan=2>Advanced (Unprompted) qualifiers</th>
<th align="left">Allowed values</th>
<th align="left">Default</th>
</tr>

<tr>
<td colspan=4>(none)</td>
</tr>

</table>

<H2>
    Input file format
</H2>

Normal sequence(s) USA.

<p>

<a name="input.1"></a>
<h3>Input files for usage example </h3>

'tembl:x65923' is a sequence entry in the example nucleic acid database 'tembl'
<p>
<p><h3>Database entry: tembl:x65923</h3>
<table width="90%"><tr><td bgcolor="#FFCCFF">
<pre>
ID   X65923; SV 1; linear; mRNA; STD; HUM; 518 BP.
XX
AC   X65923;
XX
DT   13-MAY-1992 (Rel. 31, Created)
DT   18-APR-2005 (Rel. 83, Last updated, Version 11)
XX
DE   H.sapiens fau mRNA
XX
KW   fau gene.
XX
OS   Homo sapiens (human)
OC   Eukaryota; Metazoa; Chordata; Craniata; Vertebrata; Euteleostomi; Mammalia;
OC   Eutheria; Euarchontoglires; Primates; Haplorrhini; Catarrhini; Hominidae;
OC   Homo.
XX
RN   [1]
RP   1-518
RA   Michiels L.M.R.;
RT   ;
RL   Submitted (29-APR-1992) to the EMBL/GenBank/DDBJ databases.
RL   L.M.R. Michiels, University of Antwerp, Dept of Biochemistry,
RL   Universiteisplein 1, 2610 Wilrijk, BELGIUM
XX
RN   [2]
RP   1-518
RX   PUBMED; 8395683.
RA   Michiels L., Van der Rauwelaert E., Van Hasselt F., Kas K., Merregaert J.;
RT   " fau cDNA encodes a ubiquitin-like-S30 fusion protein and is expressed as
RT   an antisense sequences in the Finkel-Biskis-Reilly murine sarcoma virus";
RL   Oncogene 8(9):2537-2546(1993).
XX
DR   H-InvDB; HIT000322806.
XX
FH   Key             Location/Qualifiers
FH
FT   source          1..518
FT                   /organism="Homo sapiens"
FT                   /chromosome="11q"
FT                   /map="13"
FT                   /mol_type="mRNA"
FT                   /clone_lib="cDNA"
FT                   /clone="pUIA 631"
FT                   /tissue_type="placenta"
FT                   /db_xref="taxon:9606"
FT   misc_feature    57..278
FT                   /note="ubiquitin like part"
FT   CDS             57..458
FT                   /gene="fau"
FT                   /db_xref="GDB:135476"
FT                   /db_xref="GOA:P35544"
FT                   /db_xref="GOA:P62861"
FT                   /db_xref="HGNC:3597"
FT                   /db_xref="UniProtKB/Swiss-Prot:P35544"
FT                   /db_xref="UniProtKB/Swiss-Prot:P62861"
FT                   /protein_id="CAA46716.1"
FT                   /translation="MQLFVRAQELHTFEVTGQETVAQIKAHVASLEGIAPEDQVVLLAG
FT                   APLEDEATLGQCGVEALTTLEVAGRMLGGKVHGSLARAGKVRGQTPKVAKQEKKKKKTG
FT                   RAKRRMQYNRRFVNVVPTFGKKKGPNANS"
FT   misc_feature    98..102
FT                   /note="nucleolar localization signal"
FT   misc_feature    279..458
FT                   /note="S30 part"
FT   polyA_signal    484..489
FT   polyA_site      509
XX
SQ   Sequence 518 BP; 125 A; 139 C; 148 G; 106 T; 0 other;
     ttcctctttc tcgactccat cttcgcggta gctgggaccg ccgttcagtc gccaatatgc        60
     agctctttgt ccgcgcccag gagctacaca ccttcgaggt gaccggccag gaaacggtcg       120
     cccagatcaa ggctcatgta gcctcactgg agggcattgc cccggaagat caagtcgtgc       180
     tcctggcagg cgcgcccctg gaggatgagg ccactctggg ccagtgcggg gtggaggccc       240
     tgactaccct ggaagtagca ggccgcatgc ttggaggtaa agttcatggt tccctggccc       300
     gtgctggaaa agtgagaggt cagactccta aggtggccaa acaggagaag aagaagaaga       360
     agacaggtcg ggctaagcgg cggatgcagt acaaccggcg ctttgtcaac gttgtgccca       420
     cctttggcaa gaagaagggc cccaatgcca actcttaagt cttttgtaat tctggctttc       480
     tctaataaaa aagccactta gttcagtcaa aaaaaaaa                               518
//
</pre>
</td></tr></table><p>

<a name="input.3"></a>
<h3>Input files for usage example 3</h3>
<p><h3>File: prev.comp</h3>
<table width="90%"><tr><td bgcolor="#FFCCFF">
<pre>
#
# Output from 'compseq'
#
# The Expected frequencies are calculated on the (false) assumption that every
# word has equal frequency.
#
# The input sequences are:
#	HSFAU


Word size	3
Total count	516

#
# Word	Obs Count	Obs Frequency	Exp Frequency	Obs/Exp Frequency
#
AAA	17		0.0329457	0.0156250	2.1085271
AAC	5		0.0096899	0.0156250	0.6201550
AAG	18		0.0348837	0.0156250	2.2325581
AAT	4		0.0077519	0.0156250	0.4961240
ACA	5		0.0096899	0.0156250	0.6201550
ACC	6		0.0116279	0.0156250	0.7441860
ACG	2		0.0038760	0.0156250	0.2480620
ACT	7		0.0135659	0.0156250	0.8682171
AGA	12		0.0232558	0.0156250	1.4883721
AGC	7		0.0135659	0.0156250	0.8682171
AGG	16		0.0310078	0.0156250	1.9844961
AGT	10		0.0193798	0.0156250	1.2403101
ATA	2		0.0038760	0.0156250	0.2480620
ATC	3		0.0058140	0.0156250	0.3720930
ATG	7		0.0135659	0.0156250	0.8682171
ATT	2		0.0038760	0.0156250	0.2480620
CAA	10		0.0193798	0.0156250	1.2403101
CAC	6		0.0116279	0.0156250	0.7441860
CAG	13		0.0251938	0.0156250	1.6124031
CAT	5		0.0096899	0.0156250	0.6201550
CCA	12		0.0232558	0.0156250	1.4883721
CCC	13		0.0251938	0.0156250	1.6124031
CCG	8		0.0155039	0.0156250	0.9922481
CCT	10		0.0193798	0.0156250	1.2403101
CGA	2		0.0038760	0.0156250	0.2480620
CGC	10		0.0193798	0.0156250	1.2403101
CGG	9		0.0174419	0.0156250	1.1162791
CGT	4		0.0077519	0.0156250	0.4961240
CTA	5		0.0096899	0.0156250	0.6201550
CTC	11		0.0213178	0.0156250	1.3643411
CTG	10		0.0193798	0.0156250	1.2403101
CTT	11		0.0213178	0.0156250	1.3643411
GAA	11		0.0213178	0.0156250	1.3643411
GAC	6		0.0116279	0.0156250	0.7441860
GAG	10		0.0193798	0.0156250	1.2403101
GAT	4		0.0077519	0.0156250	0.4961240
GCA	7		0.0135659	0.0156250	0.8682171
GCC	18		0.0348837	0.0156250	2.2325581
GCG	8		0.0155039	0.0156250	0.9922481
GCT	10		0.0193798	0.0156250	1.2403101
GGA	13		0.0251938	0.0156250	1.6124031
GGC	17		0.0329457	0.0156250	2.1085271
GGG	7		0.0135659	0.0156250	0.8682171
GGT	9		0.0174419	0.0156250	1.1162791
GTA	6		0.0116279	0.0156250	0.7441860
GTC	9		0.0174419	0.0156250	1.1162791
GTG	8		0.0155039	0.0156250	0.9922481
GTT	5		0.0096899	0.0156250	0.6201550
TAA	7		0.0135659	0.0156250	0.8682171
TAC	3		0.0058140	0.0156250	0.3720930
TAG	4		0.0077519	0.0156250	0.4961240
TAT	1		0.0019380	0.0156250	0.1240310
TCA	10		0.0193798	0.0156250	1.2403101
TCC	6		0.0116279	0.0156250	0.7441860
TCG	7		0.0135659	0.0156250	0.8682171
TCT	10		0.0193798	0.0156250	1.2403101
TGA	4		0.0077519	0.0156250	0.4961240
TGC	9		0.0174419	0.0156250	1.1162791
TGG	14		0.0271318	0.0156250	1.7364341
TGT	5		0.0096899	0.0156250	0.6201550
TTA	2		0.0038760	0.0156250	0.2480620
TTC	10		0.0193798	0.0156250	1.2403101
TTG	7		0.0135659	0.0156250	0.8682171
TTT	7		0.0135659	0.0156250	0.8682171

Other	0		0.0000000	0.0000000	10000000000.0000000
</pre>
</td></tr></table><p>


<H2>
    Output file format
</H2>

The output format consists of:
<p>
Header information and comments are preceeded by a '#' character
at the start of the line.
<p>
The Word size and the Total count are then given on separate lines,
<p>
The headers of the columns of results are preceeded by a '#'
<p>
The results columns are: the sub-sequence word, the observed
frequency, the expected frequency (which will be read from the input
file if one is given, else it is a simple inverse of the number of words
of the size specified that can be constructed), the ratio of the
observed to expected frequency.
<p>
After a blank line at the end, the results of 'Other' words is
given - this is the number of words with a sequence which has
IUPAC ambiguity codes or other unusual characters in. 

<p>

<a name="output.1"></a>
<h3>Output files for usage example </h3>
<p><h3>File: result3.comp</h3>
<table width="90%"><tr><td bgcolor="#CCFFCC">
<pre>
#
# Output from 'compseq'
#
# The Expected frequencies are calculated on the (false) assumption that every
# word has equal frequency.
#
# The input sequences are:
#	X65923


Word size	2
Total count	517

#
# Word	Obs Count	Obs Frequency	Exp Frequency	Obs/Exp Frequency
#
AA	45		0.0870406	0.0625000	1.3926499
AC	20		0.0386847	0.0625000	0.6189555
AG	45		0.0870406	0.0625000	1.3926499
AT	14		0.0270793	0.0625000	0.4332689
CA	34		0.0657640	0.0625000	1.0522244
CC	43		0.0831721	0.0625000	1.3307544
CG	25		0.0483559	0.0625000	0.7736944
CT	37		0.0715667	0.0625000	1.1450677
GA	31		0.0599613	0.0625000	0.9593810
GC	43		0.0831721	0.0625000	1.3307544
GG	46		0.0889749	0.0625000	1.4235977
GT	28		0.0541586	0.0625000	0.8665377
TA	15		0.0290135	0.0625000	0.4642166
TC	33		0.0638298	0.0625000	1.0212766
TG	32		0.0618956	0.0625000	0.9903288
TT	26		0.0502901	0.0625000	0.8046422

Other	0		0.0000000	0.0000000	10000000000.0000000
</pre>
</td></tr></table><p>

<a name="output.2"></a>
<h3>Output files for usage example 2</h3>
<p><h3>File: result6.comp</h3>
<table width="90%"><tr><td bgcolor="#CCFFCC">
<pre>
#
# Output from 'compseq'
#
# Words with a frequency of zero are not reported.
# The Expected frequencies are calculated on the (false) assumption that every
# word has equal frequency.
#
# The input sequences are:
#	X65923


Word size	6
Total count	513

#
# Word	Obs Count	Obs Frequency	Exp Frequency	Obs/Exp Frequency
#
AAAAAA	6		0.0116959	0.0002441	47.9064327
AAAAAG	1		0.0019493	0.0002441	7.9844055
AAAAGC	1		0.0019493	0.0002441	7.9844055
AAAAGT	1		0.0019493	0.0002441	7.9844055
AAACAG	1		0.0019493	0.0002441	7.9844055
AAACGG	1		0.0019493	0.0002441	7.9844055
AAAGCC	1		0.0019493	0.0002441	7.9844055
AAAGTG	1		0.0019493	0.0002441	7.9844055
AAAGTT	1		0.0019493	0.0002441	7.9844055
AACAGG	1		0.0019493	0.0002441	7.9844055
AACCGG	1		0.0019493	0.0002441	7.9844055
AACGGT	1		0.0019493	0.0002441	7.9844055
AACGTT	1		0.0019493	0.0002441	7.9844055
AACTCT	1		0.0019493	0.0002441	7.9844055
AAGAAG	6		0.0116959	0.0002441	47.9064327
AAGACA	1		0.0019493	0.0002441	7.9844055
AAGATC	1		0.0019493	0.0002441	7.9844055
AAGCCA	1		0.0019493	0.0002441	7.9844055
AAGCGG	1		0.0019493	0.0002441	7.9844055
AAGGCT	1		0.0019493	0.0002441	7.9844055
AAGGGC	1		0.0019493	0.0002441	7.9844055
AAGGTG	1		0.0019493	0.0002441	7.9844055
AAGTAG	1		0.0019493	0.0002441	7.9844055
AAGTCG	1		0.0019493	0.0002441	7.9844055
AAGTCT	1		0.0019493	0.0002441	7.9844055
AAGTGA	1		0.0019493	0.0002441	7.9844055
AAGTTC	1		0.0019493	0.0002441	7.9844055
AATAAA	1		0.0019493	0.0002441	7.9844055
AATATG	1		0.0019493	0.0002441	7.9844055
AATGCC	1		0.0019493	0.0002441	7.9844055
AATTCT	1		0.0019493	0.0002441	7.9844055
ACAACC	1		0.0019493	0.0002441	7.9844055
ACACAC	1		0.0019493	0.0002441	7.9844055


<font color=red>  [Part of this file has been deleted for brevity]</font>

TGAGGC	1		0.0019493	0.0002441	7.9844055
TGCAGC	1		0.0019493	0.0002441	7.9844055
TGCAGT	1		0.0019493	0.0002441	7.9844055
TGCCAA	1		0.0019493	0.0002441	7.9844055
TGCCCA	1		0.0019493	0.0002441	7.9844055
TGCCCC	1		0.0019493	0.0002441	7.9844055
TGCGGG	1		0.0019493	0.0002441	7.9844055
TGCTCC	1		0.0019493	0.0002441	7.9844055
TGCTGG	1		0.0019493	0.0002441	7.9844055
TGCTTG	1		0.0019493	0.0002441	7.9844055
TGGAAA	1		0.0019493	0.0002441	7.9844055
TGGAAG	1		0.0019493	0.0002441	7.9844055
TGGAGG	4		0.0077973	0.0002441	31.9376218
TGGCAA	1		0.0019493	0.0002441	7.9844055
TGGCAG	1		0.0019493	0.0002441	7.9844055
TGGCCA	1		0.0019493	0.0002441	7.9844055
TGGCCC	1		0.0019493	0.0002441	7.9844055
TGGCTT	1		0.0019493	0.0002441	7.9844055
TGGGAC	1		0.0019493	0.0002441	7.9844055
TGGGCC	1		0.0019493	0.0002441	7.9844055
TGGTTC	1		0.0019493	0.0002441	7.9844055
TGTAAT	1		0.0019493	0.0002441	7.9844055
TGTAGC	1		0.0019493	0.0002441	7.9844055
TGTCAA	1		0.0019493	0.0002441	7.9844055
TGTCCG	1		0.0019493	0.0002441	7.9844055
TGTGCC	1		0.0019493	0.0002441	7.9844055
TTAAGT	1		0.0019493	0.0002441	7.9844055
TTAGTT	1		0.0019493	0.0002441	7.9844055
TTCAGT	2		0.0038986	0.0002441	15.9688109
TTCATG	1		0.0019493	0.0002441	7.9844055
TTCCCT	1		0.0019493	0.0002441	7.9844055
TTCCTC	1		0.0019493	0.0002441	7.9844055
TTCGAG	1		0.0019493	0.0002441	7.9844055
TTCGCG	1		0.0019493	0.0002441	7.9844055
TTCTCG	1		0.0019493	0.0002441	7.9844055
TTCTCT	1		0.0019493	0.0002441	7.9844055
TTCTGG	1		0.0019493	0.0002441	7.9844055
TTGCCC	1		0.0019493	0.0002441	7.9844055
TTGGAG	1		0.0019493	0.0002441	7.9844055
TTGGCA	1		0.0019493	0.0002441	7.9844055
TTGTAA	1		0.0019493	0.0002441	7.9844055
TTGTCA	1		0.0019493	0.0002441	7.9844055
TTGTCC	1		0.0019493	0.0002441	7.9844055
TTGTGC	1		0.0019493	0.0002441	7.9844055
TTTCTC	2		0.0038986	0.0002441	15.9688109
TTTGGC	1		0.0019493	0.0002441	7.9844055
TTTGTA	1		0.0019493	0.0002441	7.9844055
TTTGTC	2		0.0038986	0.0002441	15.9688109
TTTTGT	1		0.0019493	0.0002441	7.9844055

Other	0		0.0000000	0.0000000	10000000000.0000000
</pre>
</td></tr></table><p>

<a name="output.3"></a>
<h3>Output files for usage example 3</h3>
<p><h3>File: result3.comp</h3>
<table width="90%"><tr><td bgcolor="#CCFFCC">
<pre>
#
# Output from 'compseq'
#
# Only words in frame 2 will be counted.
# The Expected frequencies are taken from the file: ../../data/prev.comp
#
# The input sequences are:
#	X65923


Word size	3
Total count	172

#
# Word	Obs Count	Obs Frequency	Exp Frequency	Obs/Exp Frequency
#
AAA	7		0.0406977	0.0329457	1.2352955
AAC	3		0.0174419	0.0096899	1.8000042
AAG	11		0.0639535	0.0348837	1.8333344
AAT	3		0.0174419	0.0077519	2.2500110
ACA	1		0.0058140	0.0096899	0.6000014
ACC	4		0.0232558	0.0116279	2.0000012
ACG	1		0.0058140	0.0038760	1.4999880
ACT	3		0.0174419	0.0135659	1.2857135
AGA	1		0.0058140	0.0232558	0.2500002
AGC	2		0.0116279	0.0135659	0.8571423
AGG	0		0.0000000	0.0310078	0.0000000
AGT	0		0.0000000	0.0193798	0.0000000
ATA	0		0.0000000	0.0038760	0.0000000
ATC	1		0.0058140	0.0058140	0.9999920
ATG	3		0.0174419	0.0135659	1.2857135
ATT	1		0.0058140	0.0038760	1.4999880
CAA	1		0.0058140	0.0193798	0.3000007
CAC	2		0.0116279	0.0116279	1.0000006
CAG	9		0.0523256	0.0251938	2.0769229
CAT	3		0.0174419	0.0096899	1.8000042
CCA	0		0.0000000	0.0232558	0.0000000
CCC	3		0.0174419	0.0251938	0.6923076
CCG	1		0.0058140	0.0155039	0.3749994
CCT	2		0.0116279	0.0193798	0.6000014
CGA	1		0.0058140	0.0038760	1.4999880
CGC	5		0.0290698	0.0193798	1.5000035
CGG	4		0.0232558	0.0174419	1.3333303
CGT	2		0.0116279	0.0077519	1.5000074
CTA	1		0.0058140	0.0096899	0.6000014
CTC	4		0.0232558	0.0213178	1.0909106
CTG	7		0.0406977	0.0193798	2.1000049
CTT	3		0.0174419	0.0213178	0.8181829
GAA	3		0.0174419	0.0213178	0.8181829
GAC	1		0.0058140	0.0116279	0.5000003
GAG	7		0.0406977	0.0193798	2.1000049
GAT	2		0.0116279	0.0077519	1.5000074
GCA	2		0.0116279	0.0135659	0.8571423
GCC	10		0.0581395	0.0348837	1.6666677
GCG	1		0.0058140	0.0155039	0.3749994
GCT	3		0.0174419	0.0193798	0.9000021
GGA	2		0.0116279	0.0251938	0.4615384
GGC	8		0.0465116	0.0329457	1.4117663
GGG	1		0.0058140	0.0135659	0.4285712
GGT	5		0.0290698	0.0174419	1.6666629
GTA	2		0.0116279	0.0116279	1.0000006
GTC	6		0.0348837	0.0174419	1.9999955
GTG	6		0.0348837	0.0155039	2.2499965
GTT	3		0.0174419	0.0096899	1.8000042
TAA	3		0.0174419	0.0135659	1.2857135
TAC	1		0.0058140	0.0058140	0.9999920
TAG	0		0.0000000	0.0077519	0.0000000
TAT	0		0.0000000	0.0019380	0.0000000
TCA	3		0.0174419	0.0193798	0.9000021
TCC	1		0.0058140	0.0116279	0.5000003
TCG	0		0.0000000	0.0135659	0.0000000
TCT	3		0.0174419	0.0193798	0.9000021
TGA	0		0.0000000	0.0077519	0.0000000
TGC	1		0.0058140	0.0174419	0.3333326
TGG	1		0.0058140	0.0271318	0.2142856
TGT	1		0.0058140	0.0096899	0.6000014
TTA	1		0.0058140	0.0038760	1.4999880
TTC	1		0.0058140	0.0193798	0.3000007
TTG	0		0.0000000	0.0135659	0.0000000
TTT	5		0.0290698	0.0135659	2.1428558

Other	0		0.0000000	0.0000000	10000000000.0000000
</pre>
</td></tr></table><p>



<H2>
    Data files
</H2>


The input data file is not required.
<p>
The input data file format is exactly the same as the output
file format. 
<p>
It expects to read in a previous output file of this program.
An error is produced if the word size of the current compseq job
and that of the output file being read in are different.

<H2>
    Notes
</H2>


The results are held in an array in memory before being written
to a file.  For large values of wordsize, you may run out of memory.
<p>
You can produce very large output files if you choose large values
of wordsize.

<H2>
    References
</H2>

None.

<H2>
    Warnings
</H2>

If you use large word-sizes (over about 7 for nucleic, 5 for protein)
you will use huge amounts of memory. 

<H2>
    Diagnostic Error Messages
</H2>


<dl>
<dt>"The word size is too large for the data structure available."
</dt><dd>You chose a word size that cannot be stored by the program.

<dt>"Insufficient memory - aborting."
</dt><dd>You do not have enough memory - use a machine with more memory.

<dt>"The word size you are counting (n) is different to the word
size in the file of expected frequencies (n)."	
</dt><dd>You chose different word sizes in the run of compseq that produced
your results file used to display the expected word frequencies
to the word size used in this run of compseq.

<dt>"The 'Word size' line was not found, instead found:"
</dt><dd>You appear to be trying to read a corrupted compseq results file
</dl>

<H2>
    Exit status
</H2>


It always exits with status 0 unless one of the above error conditions
is found

<H2>
    Known bugs
</H2>


This program can use a large amount of memory is you specify a large
word size (7 or above).  This may impact the behaviour of other programs
on your machine. 

<p>
If you run out of memory, you may see the program crash with a generic
error message that will be specific to your machine's operating system,
but will probably be a warning about writing to memory that the program
does not own (eg "Segmentation fault" on a Solaris machine)

<p>
This is not a bug, it is a feature of the way this program grabs large
amounts of memory. 

<h2><a name="See also">See also</a></h2>
<table border cellpadding=4 bgcolor="#FFFFF0">
<tr><th>Program name</th><th>Description</th></tr>
<tr>
<td><a href="backtranambig.html">backtranambig</a></td>
<td>Back translate a protein sequence to ambiguous codons</td>
</tr>

<tr>
<td><a href="backtranseq.html">backtranseq</a></td>
<td>Back translate a protein sequence</td>
</tr>

<tr>
<td><a href="banana.html">banana</a></td>
<td>Bending and curvature plot in B-DNA</td>
</tr>

<tr>
<td><a href="btwisted.html">btwisted</a></td>
<td>Calculates the twisting in a B-DNA sequence</td>
</tr>

<tr>
<td><a href="chaos.html">chaos</a></td>
<td>Create a chaos game representation plot for a sequence</td>
</tr>

<tr>
<td><a href="charge.html">charge</a></td>
<td>Protein charge plot</td>
</tr>

<tr>
<td><a href="checktrans.html">checktrans</a></td>
<td>Reports STOP codons and ORF statistics of a protein</td>
</tr>

<tr>
<td><a href="dan.html">dan</a></td>
<td>Calculates DNA RNA/DNA melting temperature</td>
</tr>

<tr>
<td><a href="emowse.html">emowse</a></td>
<td>Protein identification by mass spectrometry</td>
</tr>

<tr>
<td><a href="freak.html">freak</a></td>
<td>Residue/base frequency table or plot</td>
</tr>

<tr>
<td><a href="iep.html">iep</a></td>
<td>Calculates the isoelectric point of a protein</td>
</tr>

<tr>
<td><a href="isochore.html">isochore</a></td>
<td>Plots isochores in large DNA sequences</td>
</tr>

<tr>
<td><a href="mwcontam.html">mwcontam</a></td>
<td>Shows molwts that match across a set of files</td>
</tr>

<tr>
<td><a href="mwfilter.html">mwfilter</a></td>
<td>Filter noisy molwts from mass spec output</td>
</tr>

<tr>
<td><a href="octanol.html">octanol</a></td>
<td>Displays protein hydropathy</td>
</tr>

<tr>
<td><a href="pepinfo.html">pepinfo</a></td>
<td>Plots simple amino acid properties in parallel</td>
</tr>

<tr>
<td><a href="pepstats.html">pepstats</a></td>
<td>Protein statistics</td>
</tr>

<tr>
<td><a href="pepwindow.html">pepwindow</a></td>
<td>Displays protein hydropathy</td>
</tr>

<tr>
<td><a href="pepwindowall.html">pepwindowall</a></td>
<td>Displays protein hydropathy of a set of sequences</td>
</tr>

<tr>
<td><a href="sirna.html">sirna</a></td>
<td>Finds siRNA duplexes in mRNA</td>
</tr>

<tr>
<td><a href="wordcount.html">wordcount</a></td>
<td>Counts words of a specified size in a DNA sequence</td>
</tr>

</table>

<H2>
    Author(s)
</H2>

Gary Williams (gwilliam&nbsp;&copy;&nbsp;rfcgr.mrc.ac.uk)
<br>
MRC Rosalind Franklin Centre for Genomics Research
Wellcome Trust Genome Campus, Hinxton, Cambridge, CB10 1SB, UK



<H2>
    History
</H2>


Completed 2 March 2000

<BR>

5 April 2001 (version 1.12.0) - the operation of the option '-reverse'
has changed.  It is now 'False' by default instead of being 'True' by
default for nucleic sequences.  Too many people were getting confused by
the counts being done on both senses, so this is now done on only the
forward sense by default. 

<H2>
    Target users
</H2>
This program is intended to be used by everyone and everything, from naive users to embedded scripts.

<H2>
    Comments
</H2>
None


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