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compseq
Wiki
The master copies of EMBOSS documentation are available at
http://emboss.open-bio.org/wiki/Appdocs on the EMBOSS Wiki.
Please help by correcting and extending the Wiki pages.
Function
Calculate the composition of unique words in sequences
Description
compseq calculates the composition of words of a specified length
(dimer, trimer etc) in the input sequence(s). The word length is
user-specified. The unique sequences (words), their observed count,
observed frequency, expected frequency and (observed / expected)
frequency are written to the output file. The (observed / expected)
frequency highlights any words with unusually high (or low) occurence
in the input sequences.
Algorithm
By default, compseq makes the (false) assumption that each word is
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). Similarly, the
expected frequency of any trimer is 1/64, etc. Clearly this is not the
case in real sequences where there will be bias in favour of some
monomers and words. There are ways around this (see "Notes").
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. The '-frame' 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.
Usage
Here is a sample session with compseq
To count the frequencies of dinucleotides in a file:
% compseq tembl:x65923 -word 2 result3.comp
Calculate the composition of unique words in sequences
Go to the input files for this example
Go to the output files for this example
Example 2
To count the frequencies of hexanucleotides, without outputting the
results of hexanucleotides that do not occur in the sequence:
% compseq tembl:x65923 -word 6 result6.comp -nozero
Calculate the composition of unique words in sequences
Go to the output files for this example
Example 3
To count the frequencies of trinucleotides in frame 2 of a sequence and
use a previously prepared compseq output to show the expected
frequencies:
% compseq tembl:x65923 -word 3 result3.comp -frame 2 -in prev.comp
Calculate the composition of unique words in sequences
Go to the input files for this example
Go to the output files for this example
Command line arguments
Calculate the composition of unique words in sequences
Version: EMBOSS:6.6.0.0
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
for a nucleotide sequence, you should enter
3 here. (Integer 1 or more)
[-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
-scircular1 boolean Sequence is circular
-squick1 boolean Read id and sequence only
-sformat1 string Input sequence format
-iquery1 string Input query fields or ID list
-ioffset1 integer Input start position offset
-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 first file to standard output
-filter boolean Read first file from standard input, write
first file to 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 and exit. 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
-version boolean Report version number and exit
Input file format
compseq reads a normal sequence(s) USA.
An optional second input file is the output from a previous compseq run
used to set the expected word frequencies.
The optional second input data file format is exactly the same as the
output file format.
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.
Input files for usage example
'tembl:x65923' is a sequence entry in the example nucleic acid database
'tembl'
Database entry: tembl:x65923
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 INSDC.
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 sequence in the Finkel-Biskis-Reilly murine sarcoma virus";
RL Oncogene 8(9):2537-2546(1993).
XX
DR Ensembl-Gn; ENSG00000149806; Homo_sapiens.
DR Ensembl-Tr; ENST00000279259; Homo_sapiens.
DR Ensembl-Tr; ENST00000434372; Homo_sapiens.
DR Ensembl-Tr; ENST00000525297; Homo_sapiens.
DR Ensembl-Tr; ENST00000526555; Homo_sapiens.
DR Ensembl-Tr; ENST00000527548; Homo_sapiens.
DR Ensembl-Tr; ENST00000529259; Homo_sapiens.
DR Ensembl-Tr; ENST00000529639; Homo_sapiens.
DR Ensembl-Tr; ENST00000531743; Homo_sapiens.
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="H-InvDB:HIT000322806.14"
FT /db_xref="HGNC:3597"
FT /db_xref="InterPro:IPR000626"
FT /db_xref="InterPro:IPR006846"
FT /db_xref="InterPro:IPR019954"
FT /db_xref="InterPro:IPR019955"
FT /db_xref="InterPro:IPR019956"
FT /db_xref="PDB:2L7R"
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
//
Input files for usage example 3
File: prev.comp
#
# 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
Output file format
The output format consists of:
Header information and comments are preceeded by a '#' character at the
start of the line.
The Word size and the Total count are then given on separate lines,
The headers of the columns of results are preceeded by a '#'
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.
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.
Output files for usage example
File: result3.comp
#
# 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
Output files for usage example 2
File: result6.comp
#
# 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
[Part of this file has been deleted for brevity]
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
Output files for usage example 3
File: result3.comp
#
# 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
Data files
None.
Notes
The maximum word size is limited to 4 for proteins, and 6 for
nucleotide sequences.
Large word sizes are not appropriate for the compseq algorithm. All
possible words will be stored and reported. The algorithm is designed
to generate useful information for word sizes expected to occur at
least once in the input sequence.
The results are held in an array in memory before being written to a
file. For large values of wordsize (over about 7 for nucleic, 5 for
protein), you may run out of memory or generate a very large output
file.
There is no way for compseq to guess what the true expected frequency
should be for each word. It can however read in the result of a
previous compseq analysis and use this to set the expected frequencies
of the subsequences. In this case, the input sequences under
investigation should be representative of those used for the previous
compseq analysis. It is down to your biological expertise to ensure the
sequences are genuinely "representative", for instance, you might
select a group of sequences belonging to the same taxonomic rank such
as genus or species.
The file of expected frequencies is specified by name with the -infile
qualifier. 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.
As an alternative to using -infile, the expected frequencies of words
may be calculated from the observed frequency of single bases or
residues in the sequences. To do this, specify the -calcfreq qualifier.
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.
References
None.
Warnings
Diagnostic Error Messages
"The word size is too large for the data structure available."
You chose a word size that cannot be stored by the program.
"Insufficient memory - aborting."
You do not have enough memory - use a machine with more memory.
"The word size you are counting (n) is different to the word size in
the file of expected frequencies (n)."
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.
"The 'Word size' line was not found, instead found:"
You appear to be trying to read a corrupted compseq results file
Exit status
It always exits with status 0 unless one of the above error conditions
is found
Known bugs
This program can use a large amount of memory is you were allowed to
specify a large word size (7 or above). This may impact the behaviour
of other programs on your machine.
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)
This is not a bug, it is a feature of the way this program grabs large
amounts of memory. The maximum word size is restricted to avoid this
problem.
See also
Program name Description
backtranambig Back-translate a protein sequence to ambiguous nucleotide
sequence
backtranseq Back-translate a protein sequence to a nucleotide sequence
banana Plot bending and curvature data for B-DNA
btwisted Calculate the twisting in a B-DNA sequence
chaos Draw a chaos game representation plot for a nucleotide sequence
dan Calculate nucleic acid melting temperature
density Draw a nucleic acid density plot
emowse Search protein sequences by digest fragment molecular weight
freak Generate residue/base frequency table or plot
isochore Plot isochores in DNA sequences
mwcontam Find weights common to multiple molecular weights files
mwfilter Filter noisy data from molecular weights file
oddcomp Identify proteins with specified sequence word composition
pepdigest Report on protein proteolytic enzyme or reagent cleavage
sites
pepinfo Plot amino acid properties of a protein sequence in parallel
pepstats Calculate statistics of protein properties
wordcount Count and extract unique words in molecular sequence(s)
Author(s)
Gary Williams formerly at:
MRC Rosalind Franklin Centre for Genomics Research Wellcome Trust
Genome Campus, Hinxton, Cambridge, CB10 1SB, UK
Please report all bugs to the EMBOSS bug team
(emboss-bug (c) emboss.open-bio.org) not to the original author.
History
Completed 2 March 2000
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.
Target users
This program is intended to be used by everyone and everything, from
naive users to embedded scripts.
Comments
None
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