
 @0. B 1 @MEP
  This is a program  for analysing families of nucleotide sequences in
  order  to find common motifs and potential binding sites.  The ideas
  in  this  program  were  described  in  Staden,  R.   "Methods   for
  discovering  novel  motifs  in  nucleic  acid  sequences".  Computer
  Applications in the Biosciences, 5, 293-298, (1989).

        The program  can  read  sequences  stored  in  either  of  two
  formats: 1) all sequences aligned in a single file; 2) all sequences
  in separate files and accessed through a file of file names.

        The  program  contains  functions  that  can  answer   several
  questions about a set of sequences:

  Which words are most common?
  Which words occur in the most sequences?
  Which words contain the most information?
  Which words occur in equivalent positions in the sequences?
  Which words are inverted repeats?
  Which words occur on both strands of the sequences?
  Where are the inverted repeats?
  Where are the fuzzy words?

        Most of the program is concerned with analysing what it  terms
  "fuzzy words" within the set of sequences. The analysis is explained
  below. Note that the standard version of the programs is limited  to
  words of maximum length 8 letters, and a maximum fuzziness of 2.

        The following analyses (preceded by their option numbers)  are
  included:
    ? = Help
    ! = Quit
    3 = Read new sequences
    4 = Redefine active region
    5 = List the sequences
    6 = List text file
    7 = Direct output to disk
   10 = Clear graphics
   11 = Clear text
   12 = Draw ruler
   13 = Use cross hair
   14 = Reset margins
   15 = Label diagram
   16 = Draw map
   17 = Search for strings
   18 = Set strand
   19 = Set composition
   20 = Set word length
   21 = Set number of mismatches
   22 = Show settings
   23 = Make dictionary Dw
   24 = Make dictionary Ds
   25 = Make fuzzy dictionary Dm from Dw
   26 = Make fuzzy dictionary Dm from Ds
   27 = Make fuzzy dictionary Dh from Dm
   28 = Examine fuzzy dictionary Dm
   29 = Examine fuzzy dictionary Dh
   30 = Examine words in Dm
   31 = Examine words in Dh
   32 = Save or restore a dictionary
   33 = Find inverted repeats

        Some of these methods produce graphical  results  and  so  the
  program  is  generally used from a graphics terminal (a vdu on which
  lines and points can be drawn as well as characters).

  The positions of each of the plots is defined relative  to  a  users
  drawing board which has size 1-10,000 in x and 1-10,000 in y.  Plots
  for each  option  are  drawn  in  a  window  defined  by  x0,y0  and
  xlength,ylength. Where x0,y0 is the position of the bottom left hand
  corner of the window, and xlength is the width  of  the  window  and
  ylength the height of the window.
     --------------------------------------------------------- 10,000
     1                                                       1
     1       --------------------------------------   ^      1
     1       1                                    1   1      1
     1       1                                    1   1      1
     1       1                                    1 ylength  1
     1       1                                    1   1      1
     1       1                                    1   1      1
     1       --------------------------------------   v      1
     1  x0,y0^                                               1
     1       <---------------xlength-------------->          1
     ---------------------------------------------------------      1
     1                                                   10,000

  All values are in drawing board  units  (i.e.  1-10,000,  1-10,000).
  The default window positions are read from a file "MEPMARG" when the
  program is started. Users can have their own file if required.

        The options for the program are accessed from  3  main  menus:
  general,  screen  control  and dictionary analylsis.  Both menus and
  options are selected by number.

        The most important and novel part of the program is its use of
  "fuzzy dictionaries" and an information theory measure, to help show
  the most interesting motifs.  Central to the method is the idea of a
  fuzzy   dictionary   of  word  frequencies.  A  dictionary  of  word
  frequencies is an ordered list of all the words in the sequences and
  a  count  of the number of times that they occur. A fuzzy dictionary
  is an equivalent list but which contains instead, for each  word,  a
  count  of  the number of times similar words occur in the sequences.
  We term words that are similar "relations". The fuzziness is defined
  by the number of letters in a word that are allowed to be different.
  So if we had a fuzziness of 1 we allow 1 letter to be different. For
  example,  with  a  fuzziness of 1, the entry in the fuzzy dictionary
  for the word TTTTTT would contain a count of the  numbers  of  times
  TTTTTT  occured  plus  the  number  of  times all words differing by
  exactly one letter from TTTTTT occured.

        Once the fuzzy dictionary has been created we can  examine  it
  in  several  ways  to find candidate control sequences. The simplest
  question we can ask is which word in  the  dictionary  is  the  most
  common.   Sometimes  this  simple  criterion of "most common" may be
  adequate to discover a new motif but in general we would not  expect
  it  to  be  sufficient. For example some words will be common simply
  because of a base composition bias in the sequences being  analysed.
  In  addition  a  word  can be the most frequent and yet not be "well
  defined". This last point is best explained by an example.

        Suppose we were looking at  two letter words and allowing  one
  mismatch,  and  that  there were 10 occurences of TT and 5 of AC. We
  could align the 10 words that were one letter different from TT  and
  the  5  that  were  related to AC. Then we could count the number of
  times each base occured in each position for each of these two  sets
  of words. Suppose we got the two base frequency tables shown below.
     TT                  AC
         T 6 4               T 1 0
         C 1 3               C 0 4
         A 1 2               A 4 1
         G 2 1               G 0 0

  These tables show that although TT occurs (with one letter mismatch)
  more often than AC, the ratio of base frequencies for AC at 4/5, 4/5
  is higher than those for TT at 6/10, 4/10. Hence we would  say  that
  AC was better defined than TT.  Expressing this another way we would
  say that the definition of AC contained more information  than  that
  for TT. The program calculates the information content in a way that
  takes into account both the sequence composition and  the  level  of
  definition of the motif.

        Definitions

        Here we deal only with the dictionary  analysis.   Suppose  we
  are dealing with a set of sequences and are examining them for words
  that are six characters in length.

        Dictionary Dw contains a count of the  number  of  times  each
  word  occurs  in  the  set  of  sequences. For example the entry for
  TTTTTT contains a value equal to the number of times the word TTTTTT
  occurs in the set of sequences.

        Dictionary Ds contains a count  of  the  number  of  different
  sequences  in  which  each word occurs. For example if the entry for
  word TTTTTT contains the value 10, it denotes that the  word  TTTTTT
  occurs  in  ten  different sequences. Unlike Dw it only counts words
  once for each  sequence.  For  example  if  we  had  a  set  of  100
  sequences, the maximum possible value that Ds could take is 100, and
  this would only happen if a word occurred in every sequence. However
  for  the same set of sequences, Dw could contain values greater than
  100, and this would show that a word had occurred more than once  in
  at least one sequence.

        From either of the two dictionaries Dw or Ds we can  calculate
  a  fuzzy  dictionary  Dm.  For  each  word,  the  entry in the fuzzy
  dictionary Dm contains the sum of the dictionary values (taken  from
  either  Dw  or  Ds)  for  all  words  that differ from it by up to m
  letters. For example if m=2 the entry for TTTTTT contains the number
  of  times  that TTTTTT occurs in the dictionary, plus the counts for
  all words that differ from TTTTTT by 1 or 2 letters.  Obviously  the
  interpretation  of  the  values  in  Dm  depends on which of the two
  dictionaries Dw or Ds they were derived from. When derived  from  Dw
  the entry for any word in Dm gives the total number of times it, and
  its relations, occur in the set of sequences. When derived  from  Ds
  the  entry  for  any  word in Dm gives the total number of different
  sequences that contain a word and each of its relations.

        Finally,  from  fuzzy  dictionary  Dm  we  can  derive   fuzzy
  dictionary  Dh.  All  entries in Dh are zero except for the word(s),
  within each set of relations, that are most frequent. For example if
  TTTTTT  occurred  20  times  but  had  a relation that occurred more
  often, then the entry for TTTTTT would be zero.  However  if  TTTTTT
  did  not  have  a more frequently occurring relation, then the entry
  for TTTTTT would contain the value 20.
 @1. B 1 @Help
  This option gives online help. The user should select option numbers
  and  the  current  documentation  will  be given. Note that option 0
  gives an introduction to the program, and that ? will get help  from
  anywhere  in the program.  The following analyses (preceded by their
  option numbers) are included:
    ? = Help
    ! = Quit
    3 = Read new sequences
    4 = Redefine active region
    5 = List the sequences
    6 = List text file
    7 = Direct output to disk
   10 = Clear graphics
   11 = Clear text
   12 = Draw ruler
   13 = Use cross hair
   14 = Reset margins
   15 = Label diagram
   16 = Draw map
   17 = Search for strings
   18 = Set strand
   19 = Set composition
   20 = Set word length
   21 = Set number of mismatches
   22 = Show settings
   23 = Make dictionary Dw
   24 = Make dictionary Ds
   25 = Make fuzzy dictionary Dm from Dw
   26 = Make fuzzy dictionary Dm from Ds
   27 = Make fuzzy dictionary Dh from Dm
   28 = Examine fuzzy dictionary Dm
   29 = Examine fuzzy dictionary Dh
   30 = Examine words in Dm
   31 = Examine words in Dh
   32 = Save or restore a dictionary
   33 = Find inverted repeats
 @2. B 1 @Quit
  This function stops the program.
 @3. B 1 @Read a new sequence.

        It can read sequences stored in either of two formats: 1)  all
  sequences  aligned  in  a  single file; 2) all sequences in separate
  files and accessed through a file of file  names.  Typical  dialogue
  follows:

  X 1 Read file of aligned sequences
    2 Use file of file names
  ? 0,1,2 =

  ? File of aligned sequences=F1
  Number of files           88

 @4. B 1 @Define active region
  For its analytic functions the program always works on a  region  of
  the  sequence called the active region. When  new sequences are read
  into the program the active region is automatically set to start  at
  the  beginning  of the sequences and go up to the end of the longest
  one.
 @5. B 1 @List a sequence.
  The sequence can be listed with line lengths of 50 bases  with  each
  sequence  numbered in the order in which they were read.  Output can
  be directed to a disk file by first selecting disk  output.  Typical
  dialogue follows.

  ? Menu or option number=5

                10        20        30        40        50
     1  TAGCGGATCCTACCTGACGCTTTTTATCGCAACTCTCTACTGTTTCTCCA
     2  CAAATAATCAATGTGGACTTTTCTGCCGTGATTATAGACACTTTTGTTAC
     3  TAATTTATTCCATGTCACACTTTTCGCATCTTTGTTATGCTATGGTTATT
     4  ACTAATTTATTCCATGTCACACTTTTCGCATCTTTGTTATGCTATGGTTA
     5  AGGCACCCCAGGCTTTACACTTTATGCTTCCGGCTCGTATGTTGTGTGGA
     6  TAATGTGAGTTAGCTCACTCATTAGGCACCCCAGGCTTTACACTTTATGC
     7  ACACCATCGAATGGCGCAAAACCTTTCGCGGTATGGCATGATAGCGCCCG
     8  GGGGCAAGGAGGATGGAAAGAGGTTGCCGTATAAAGAAACTAGAGTCCGT
     9  AGGGGGTGGAGGATTTAAGCCATCTCCTGATGACGCATAGTCAGCCCATC
    10  AAAACGTCATCGCTTGCATTAGAAAGGTTTCTGGCCGACCTTATAACCAT

                60
     1  TACCCGTTTTT
     2  GCGTTTTTGT
     3  TCATACCATAAG
     4  TTTCATACC
     5  ATTGTGAGC
     6  TTCCGGCTCG
     7  GAAGAGAGT
     8  TCAGGTGT
     9  ATGAATG
    10  TAATTACG
 @6. B 1 @List a text file.
  Allows the user to have a text file displayed on the screen. It will
  appear one page at a time.
 @7. B 1 @Direct output to disk

        Used to direct output that would normally appear on the screen
  to a file.

        Select redirection of either text or graphics, and supply  the
  name of the file that the output should be written to.

        The results from the next options selected will not appear  on
  the  screen  but  will  be  written  to  the  file. When option 7 is
  selected again the file will be closed and output will again  appear
  on the screen.
 @10. B 1 @Clear graphics
  Clears the screen of both text and graphics.
 @11. B 1 @Clear text
  Clears only text from the screen.
 @12. B 1 @Draw a ruler.
  This option allows the user to draw a ruler or  scale  along  the  x
  axis  of  the  screen  to help identify the coordinates of points of
  interest. The user can define the position of the first  amino  acid
  to  be marked (for example if the active region is 1501 to 8000, the
  user might wish to mark every 1000th amino acid starting  at  either
  1501  or  2000  -  it depends if the user wishes to treat the active
  region as an independent unit with its own numbering starting at its
  left  edge,  or  as  part  of the whole sequence). The user can also
  define the separation of the ticks on the scale and their height. If
  required  the  labelling  routine  can be used to add numbers to the
  ticks.
 @13. B 1 @Use crosshair.
  This function puts a steerable cross on the screen that can be  used
  to find the coordinates of points in the sequence. The user can move
  the cross around using the directional keys; when he hits the  space
  bar  the  program  will  print  out  the coordinates of the cross in
  sequence units and the option will be exited.

        If instead, you hit a , the position will be displayed but the
  cross will remain on the screen.

        If a letter s is hit the sequence around  the  cross  hair  is
  displayed and the cross remains on the screen.
 @14. B 1 @Reposition plots
  The positions of each of the plots is defined relative  to  a  users
  drawing board which has size 1-10,000 in x and 1-10,000 in y.  Plots
  for each  option  are  drawn  in  a  window  defined  by  x0,y0  and
  xlength,ylength. Where x0,y0 is the position of the bottom left hand
  corner of the window, and xlength is the width  of  the  window  and
  ylength the height of the window.
     --------------------------------------------------------- 10,000
     1                                                       1
     1       --------------------------------------   ^      1
     1       1                                    1   1      1
     1       1                                    1   1      1
     1       1                                    1 ylength  1
     1       1                                    1   1      1
     1       1                                    1   1      1
     1       --------------------------------------   v      1
     1  x0,y0^                                               1
     1       <---------------xlength-------------->          1
     ---------------------------------------------------------      1
     1                                                   10,000

  All values are in drawing board  units  (i.e.  1-10,000,  1-10,000).
  The default window positions are read from a file "MEPMARG" when the
  program is started. Users can have their own file if  required.   As
  all  the  plots  start  at  the same position in x and have the same
  width, x0 and xlength are the same for all options. Generally  users
  will  only  want  to change the start level of the window y0 and its
  height ylength. This option allows users to change window  positions
  whilst  running  the  program.   The  routine  prompts first for the
  number of the option that the users wishes to reposition;  then  for
  the  y  start and height; then for the x start and length. Note that
  changes to the x values affect all options. If the user  types  only
  carriage  return  for any value it will remain unchanged. The cross-
  hair can be used to choose suitable heights.
 @15. B 1 @Label a diagram
  This routine allows users to label any diagrams they have  produced.
  They  are  asked  to  type  in a label. When the user types carriage
  return to finish typing the label  the  cross-hair  appears  on  the
  screen. The user can position it anywhere on the screen. If the user
  types R (for right justify) the label will be written on the diagram
  with  its  right end at the cross-hair position. If the user types L
  (for left justify) the label will be written on the diagram with its
  left  end  at  the  cross  hair  position.  The cross-hair will then
  immediately reappear. The user may put the  same  label  on  another
  part of the diagram as before or if he hits the space bar he will be
  asked if he wishes to type in another label.
 @16. B 1 @Display a map.
  It is often convenient to plot a map alongside graphed  analysis  in
  order to indicate features within the sequence. This function allows
  users to draw maps using files arranged in the form of EMBL  feature
  tables.  Of  course the EMBL table are usually only used for nucleic
  acid sequence annotation but, as long as the features are written in
  the correct format, they can be employed by this routine. The map is
  composed of a line representing the sequence and then further  lines
  denoting the endpoints of each feature the user identifies. The user
  is asked to  define  height  at  which  the  line  representing  the
  sequence  should be drawn; then for the feature height; then for the
  features to plot.
 @17. B 1 @Search for strings
  Search for  strings  perfoms  searches  of  all  the  sequences  for
  selected words and shows which sequences they are found in. The user
  types in a word and defines the allowed number  of  mismatches.  The
  results  are  listed  or plotted. If listed the display includes the
  sequence number, the position  in  the  sequence  and  the  matching
  string.  The results are plotted in the following way. The x axis of
  the plot represents the length of the aligned sequences  and  the  y
  direction  is  divided  into  sufficient  strips to accommodate each
  sequence. So if a match is found in the 3rd sequence at  a  position
  equivalent  to  halfway  along  the  longest of the sequences then a
  short vertical line will be drawn at the midpoint of the 3rd  strip.
  If  the  sequences are aligned it can be useful if the motifs happen
  to appear  in  related  positions.  For  example  see  the  original
  publication. Typical dialogue follows.

  ? Menu or option number=17
  X 1 Plot match positions
    2 Plot histogram of matches
  ? 0,1,2 =
  ? Word to search for=TTGACA
  ? Minimum match (0-6) (6) =5
  ? (y/n) (y) Plot results N
       2    35 TAGACA
       5    14 TTTACA
       6    37 TTTACA
      11    14 TAGACA
      14    14 TTGACA
      17    14 GTGACA
      17    22 TTAACA
      20     1 TTGACA
 @18. B 1 @Set strand
  Set strand  allows  the  user  to  define  which  strand(s)  of  the
  sequences to analyse: input stand, complement of input, or both.
 @19. B 1 @Set composition
  Set composition  gives  the  user  three  choices  for  setting  the
  composition  of  the  sequences  for  use  in the calculation of the
  information content of  words.  The  user  can  select  the  overall
  composition  of  the  sequences as read, an even composition, or can
  type in any other 4 values.
 @20. B 1 @Set word length
  Set word length sets the length of word for which dictionaries  will
  be made.
 @21. B 1 @Set number of mismatches
  Set number of  mismatches  sets  the  level  of  fuzziness  for  the
  creation of dictionary Dm.
 @22. B 1 @Show settings
  Show  settings  show  the  current  settings  for   all   parameters
  associated with dictionary analysis. A typical diaplsy follows:
   ? Menu or option number=22
   Current word length  =   6
   Number of mismatches =   1
   Start position       =     1
   End position         =    63
   Input strand only
   Observed composition
   Dictionary Dw unmade
   Dictionary Ds unmade
   Dictionary Dm unmade
   Dictionary Dh unmade
 @23. B 1 @Make dictionary Dw
  Make dictionary Dw creates a dictionary that contains  a  count   of
  the frequency of occurrence of each word in the collected sequences.
 @24. B 1 @Make dictionary Ds
  Make dictionary Ds creates a dictionary that contains a count of the
  number of different sequences that contain each word.
 @25. B 1 @Make dictionary Dm from Dw
  Make dictionary Dm  from Dw creates a dictionary from dictionary  Dw
  that contains the frequency of occurrence of each word (say X) in Dw
  plus the frequency of occurrence of each word  in  Dw  that  differs
  from  X  by  up  to m letters. Dm is called a fuzzy dictionary as it
  contains the  frequencies  of  occurrence  of  all  words  plus  the
  frequencies of all the words that are similar to them.
 @26. B 1 @Make dictionary Dm from Ds
  Make dictionary Dm  from Ds creates a dictionary from dictionary  Ds
  that contains the frequency of occurrence of each word (say X) in Ds
  plus the frequency of occurrence of each word  in  Ds  that  differs
  from  X  by  up  to m letters. Dm is called a fuzzy dictionary as it
  contains the  frequencies  of  occurrence  of  all  words  plus  the
  frequencies of all the words that are similar to them.
 @27. B 1 @Make dictionary Dh from Dm
  Make dictionary Dh  creates a  dictionary  from  dictionary  Dm  and
  whose  entries are zero except for those words in any set of related
  words that are most frequent. It finds the dominant  words  in  each
  set of relations and stores their counts.
 @28. B 1 @Examine dictionary Dm
  Examine dictionary Dm  allows  users  to  analyse  the  contents  of
  dictionary  Dm  to  find  the  most common words or those words that
  contain the most information.  The  user  supplies  a  frequency  or
  information  cutoff and chooses to have the results sorted on either
  value. The program will find the top  100  words  that  achieve  the
  cutoff  values  and present them to the user sorted as selected. The
  information  content  will  be  calcutated  from  either  Dw  or  Ds
  depending  which  was  used  to  create  Dm,  and  using the current
  composition setting. Typical dialogue follows:

  ? Menu or option number=28
  Looking for highest scoring words
  The highest word score =          115
  ? Minimum word score (0-115) (0) =60
  ? Minimum information (0.00-1.00) (0.00) =.62
  X 1 Sort on information
    2 Sort on word score
  ? 0,1,2 =

  ? Maximum number to list (0-100) (100) =

  The words are
   Total words=           9 Maximum information=  0.7385326
  TTGACA      60   0.73850
  AAAAAC      64   0.66460
  AAAAAA      90   0.64880
  GTTTTT      66   0.64300
  TTTTTG      73   0.64070
  TTTTGT      63   0.63820
  TTTTTC      65   0.63810
  AAAATA      63   0.62670
  TATAAT      65   0.62510
  The highest word score =          115
  ? Minimum word score (0-115) (0) =60
  ? Minimum information (0.00-1.00) (0.00) =.62
  X 1 Sort on information
    2 Sort on word score
  ? 0,1,2 =2
  ? Maximum number to list (0-100) (100) =

  The words are
   Total words=           9 Maximum information=  0.7385326
  AAAAAA      90   0.64880
  TTTTTG      73   0.64070
  GTTTTT      66   0.64300
  TTTTTC      65   0.63810
  TATAAT      65   0.62510
  AAAAAC      64   0.66460
  TTTTGT      63   0.63820
  AAAATA      63   0.62670
  TTGACA      60   0.73850
  The highest word score =          115
  ? Minimum word score (0-115) (0) =!

 @29. B 1 @Examine dictionary Dh
  Examine dictionary Dh  allows  users  to  analyse  the  contents  of
  dictionary   Dh  to  find  the most common words or those words that
  contain the most information.  The  user  supplies  a  frequency  or
  information  cutoff and chooses to have the results sorted on either
  value. The program will find the top  100  words  that  achieve  the
  cutoff  values  and present them to the user sorted as selected. The
  information  content  will  be  calcutated  from  either  Dw  or  Ds
  depending  which  was  used  to  create  Dh  and  using  the current
  composition setting. Typical dialogue follows:

  ? Menu or option number=29
  Looking for highest scoring words
  The highest word score =          115
  ? Minimum word score (0-115) (0) =60
  ? Minimum information (0.00-1.00) (0.00) =.6
  X 1 Sort on information
    2 Sort on word score
  ? 0,1,2 =

  ? Maximum number to list (0-100) (100) =

  The words are
   Total words=           4 Maximum information=  0.7385326
  TTGACA      60   0.73850
  AAAAAA      90   0.64880
  TATAAT      65   0.62510
  TTTTTT     115   0.60630
  The highest word score =          115
  ? Minimum word score (0-115) (0) =50
  ? Minimum information (0.00-1.00) (0.00) =.5
  X 1 Sort on information
    2 Sort on word score
  ? 0,1,2 =

  ? Maximum number to list (0-100) (100) =

  The words are
   Total words=           8 Maximum information=  0.7385326
  TTGACA      60   0.73850
  TCTTGA      54   0.66080
  AAAAAA      90   0.64880
  TATAAT      65   0.62510
  ACTTTA      57   0.61960
  TTTTTT     115   0.60630
  AGTATA      51   0.60540
  TTATAA      55   0.59300
  The highest word score =          115
  ? Minimum word score (0-115) (0) =50
  ? Minimum information (0.00-1.00) (0.00) =

  X 1 Sort on information
    2 Sort on word score
  ? 0,1,2 =

  ? Maximum number to list (0-100) (100) =

  The words are
   Total words=           8 Maximum information=  0.7385326
  TTGACA      60   0.73850
  TCTTGA      54   0.66080
  AAAAAA      90   0.64880
  TATAAT      65   0.62510
  ACTTTA      57   0.61960
  TTTTTT     115   0.60630
  AGTATA      51   0.60540
  TTATAA      55   0.59300
  The highest word score =          115
  ? Minimum word score (0-115) (0) =!

 @30. B 1 @Examine words in Dm
  Examine words  in  Dm  allows  users  to  analyse  the  contents  of
  dictonary  Dm  at  the  level  of  individual  words  to  find their
  frequency, information content, and  to  see  their  base  frequency
  table.  The user types in a word to examine and the program displays
  the values and table. The information  content  will  be  calcutated
  from  either  Dw  or  Ds  depending which was used to create Dm, and
  using the current composition setting. Typical dialogue follows:
  ? Menu or option number=30
  ? Word to examine=TTGACA
  TtgacA            60  0.7385326
      56    56     6     7     5    11
       4     3     2     1    52     1
       1     4     2    53     3    48
       3     1    54     3     4     4
  TTGACA
  ? Word to examine=TATAAT
  taTAat            65  0.6251902
      56     3    53     4     4    60
       6     1     5     5     5     3
       3    60     5    57    57     4
       4     5     6     3     3     2
  TATAAT
  ? Word to examine=

 @31. B 1 @Examine words in Dh
  Examine words  in  Dh  allows  users  to  analyse  the  contents  of
  dictonary  Dh  at  the  level  of  individual  words  to  find their
  frequency, information content, and  to  see  their  base  frequency
  table.  The user types in a word to examine and the program displays
  the values and table. The information  content  will  be  calcutated
  from  either  Dw  or  Ds  depending which was used to create Dm, and
  using the current composition setting. Typical dialogue follows:

   ? Menu or option number=31
  ? Word to examine=TTGACA
  TtgacA            60  0.7385326
      56    56     6     7     5    11
       4     3     2     1    52     1
       1     4     2    53     3    48
       3     1    54     3     4     4
  TTGACA
  ? Word to examine=TATAAT
  taTAat            65  0.6251902
      56     3    53     4     4    60
       6     1     5     5     5     3
       3    60     5    57    57     4
       4     5     6     3     3     2
  TATAAT
  ? Word to examine=GGGGGG
  gggggg             0  0.6199890
       3     1     1     2     3     4
       1     3     1     2     2     1
       2     1     1     1     1     1
      11    12    14    12    11    11
  GGGGGG
  ? Word to examine=

 @32. B 1 @Save or restore a dictionary
  Save or restore  dictionary  allows  users  to  write  or  read  any
  dictionary  to  and from disk files. The user is asked te define the
  dictionary and file. The function is useful  if  the  machine  being
  used  is  very  slow at calculating because the files can be handled
  quickly. However note that the files  cannot  be  processed  by  any
  other program.
 @33. B 1 @Find inverted repeats
  Find inverted repeats performs searches for simple  inverted  repeat
  sequences  in  each  sequence.  They  are defined by a range of loop
  sizes and a minimum number of potential basepairs. The  results  can
  be  plotted  or listed. The x axis of the plot represents the length
  of the aligned  sequences  and  the  y  direction  is  divided  into
  sufficient  strips  to  accommodate each sequence. So if an inverted
  repeat is found in the 3rd sequence  at  a  position  equivalent  to
  halfway  along  the  longest  of the sequences then a short vertical
  line will be drawn at the midpoint of the 3rd strip.  Alternatively,
  if  the  results  are  listed, the potential hairpin loops are drawn
  out, with the sequence number and the position of the loop.  Typical
  dialogue follows.

  ? Menu or option number=33
  Define the range of loop sizes
  ? Minimum loop size (0-10) (3) =0
  ? Maximum loop size (1-20) (3) =
  ? Minimum number of basepairs (1-20) (6) =
  ? (y/n) (y) Plot results N
   Searching

  Sequence     3    34
             C
            G.T
            T-A
            A-T
            T.G
            T.G
            G.T
       ATCTTT TATTTCA
           33

  Sequence     5    35
             T
            G.T
            T.G
            A-T
            T.G
            G.T
            C-G
            T.G
       TCCGGC AATTGTG
           34


 @ End of help
