malacology/staden-lg
1
0
Fork 0
Code Issues Pull requests Projects Releases Wiki Activity
staden-lg/help/MEP.RNO

860 lines
30 KiB
Text
Raw Normal View History

init
2021-12-04 13:07:58 +08:00
.NPA
.SP 1
.left margin1
@-1. TX 0 @General
.sp
@-2. T 0 @Screen control
.sp
@-2. X 0 @Screen
.sp
@-3. TX 0 @Dictionary analysis
.sp
@0. TX -1 @MEP
.left margin2
.para
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).
.PARA
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.
.PARA
The program contains functions that can answer several questions
about a set of sequences:
.SK1
.left margin2
Which words are most common?
.left margin2
Which words occur in the most sequences?
.left margin2
Which words contain the most information?
.left margin2
Which words occur in equivalent positions in the sequences?
.left margin2
Which words are inverted repeats?
.left margin2
Which words occur on both strands of the sequences?
.left margin2
Where are the inverted repeats?
.left margin2
Where are the fuzzy words?
.para
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.
.para
The following analyses (preceded by their option numbers) are included:
.lit
? = 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
.end lit
.para
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).
.para
.LEFT MARGIN2
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.
.lit
--------------------------------------------------------- 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
.end lit
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.
.para
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.
.para
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.
.para
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.
.para
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.
.lit
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
.end lit
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.
.para
Definitions
.para
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.
.para
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.
.para
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.
.para
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.
.para
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.
.LEFT MARGIN1
@1. T 0 @Help
.LEFT MARGIN2
.para
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:
.lit
? = 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
.end lit
.left margin1
@2. T 0 @Quit
.left margin2
.para
This function stops the program.
.left margin1
@3. TX 1 @Read a new sequence
.LEFT MARGIN2
.para
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:
.lit
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
.end lit
.left margin1
@4. TX 1 @Define active region
.LEFT MARGIN2
.para
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.
.left margin1
@5. TX 1 @List a sequence
.LEFT MARGIN2
.para
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.
.lit
? 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
.end lit
.left margin1
@6. TX 1 @List a text file
.LEFT MARGIN2
.para
Allows the user to have a text file displayed on the screen. It will appear
one page at a time.
.left margin1
@7. TX 1 @Direct output to disk
.LEFT MARGIN2
.para
Used to direct output that would normally appear on the screen to a file.
.para
Select redirection of either text or graphics, and
supply the name of the file that the output should be written to.
.para
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.
.left margin1
@10. TX 2 @Clear graphics
.LEFT MARGIN2
.para
Clears the screen of both text and graphics.
.left margin1
@11. TX 2 @Clear text
.LEFT MARGIN2
.para
Clears only text from the screen.
.left margin1
@12. TX 2 @Draw a ruler
.LEFT MARGIN2
.para
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.
.left margin1
@13. TX 2 @Use crosshair
.LEFT MARGIN2
.para
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.
.para
If instead,
you hit a , the position will be displayed but the cross will remain on
the screen.
.para
If a letter s is hit the sequence around the cross hair is displayed and
the cross remains on the screen.
.left margin1
@14. TX 2 @Reposition plots
.LEFT MARGIN2
.para
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.
.lit
--------------------------------------------------------- 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
.end lit
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.
.LEFT MARGIN1
@15. TX 2 @Label a diagram
.LEFT MARGIN2
.para
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.
.left margin1
@16. TX 2 @Display a map
.LEFT MARGIN2
.para
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.
.left margin1
@17. TX 1 @Search for strings
.left margin2
.para
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.
.lit
? 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
.end lit
.left margin1
@18. TX 3 @Set strand
.left margin2
.para
Set strand allows the user to define which strand(s) of the sequences to
analyse: input stand, complement of input, or both.
.left margin1
@19. TX 3 @Set composition
.left margin2
.para
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.
.left margin1
@20. TX 3 @Set word length
.left margin2
.para
Set word length sets the length of word for which dictionaries will be made.
.left margin1
@21. TX 3 @Set number of mismatches
.left margin2
.para
Set number of mismatches sets the level of fuzziness for the creation of
dictionary Dm.
.left margin1
@22. TX 3 @Show settings
.left margin2
.para
Show settings show the current settings for all parameters associated with
dictionary analysis. A typical diaplsy follows:
.lit
? 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
.end lit
.left margin1
@23. TX 3 @Make dictionary Dw
.left margin2
.para
Make dictionary Dw creates a dictionary that contains a count of the
frequency of occurrence of each word in the collected sequences.
.left margin1
@24. TX 3 @Make dictionary Ds
.left margin2
.para
Make dictionary Ds creates a dictionary that contains a count of the
number of different sequences that contain each word.
.left margin1
@25. TX 3 @Make dictionary Dm from Dw
.left margin2
.para
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.
.left margin1
@26. TX 3 @Make dictionary Dm from Ds
.left margin2
.para
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.
.left margin1
@27. TX 3 @Make dictionary Dh from Dm
.left margin2
.para
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.
.left margin1
@28. TX 3 @Examine fuzzy dictionary Dm
.left margin2
.para
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:
.lit
? 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) =!
.end lit
.left margin1
@29. TX 3 @Examine fuzzy dictionary Dh
.left margin2
.para
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:
.lit
? 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) =!
.end lit
.left margin1
@30. TX 3 @Examine words in Dm
.left margin2
.para
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:
.lit
? 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=
.end lit
.left margin1
@31. TX 3 @Examine words in Dh
.left margin2
.para
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:
.lit
? 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=
.end lit
.left margin1
@32. TX 3 @Save or restore a dictionary
.left margin2
.para
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.
.left margin1
@33. TX 1 @Find inverted repeats
.left margin2
.para
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.
.lit
? 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 lit
.left margin1
@ End of help
Reference in a new issue Copy permalink