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JoinMap ® List of frequently asked questions

Last modified: 31 January 2017.

1. My map has more than 100 loci; which parameters do I adjust for the ML mapping algorithm?

2. My population has more than 4000 loci. What settings do I adjust to let JoinMap v4/v4.1 run more responsive?

3. How do I install my individual license file 'JOINMAP.LIC'?

4. Why do I get the message 'JoinMap is using an evaluation license'?

5. I appear to have problems installing my individual license under Windows 7 or Vista, how do I solve this?

6. Under Windows 7 or Vista I get the successive error messages:

'Access violation at address ... in module 'uxtheme.dll' ...',
'The instruction at ... referenced memory at '0x00000000' ...',
'Runtime error 216 at ...';

what is the problem?

7. On which versions of MS-Windows runs JoinMap?

8. I have lost sight of the navigation panel; how do I get it back?

9. Why do I get the message 'insufficient linkage in data to complete the map'?

10. What is the best approach to integrating maps from several populations?

11. How is the modified LOD score calculated for the recombination between two loci?

12. How is the chi-square test for heterogeneity calculated?

13. How do I code loci in a CP population that have two alleles (heterozygous)in one parent and one allele (homozygous) in the other?

14. JoinMap does not accept genotypes 'c' or 'd' in my backcross population (BC1). Why?

15. Against what ratio is tested in the 'Locus genot. freq.' tabsheet with RIx populations?


1. My map has more than 100 loci; which parameters do I adjust for the ML mapping algorithm?

The spatial sampling thresholds seem to work more efficient with the next set of values: 0.100, 0.0300, 0.010, 0.003, 0.001. The map order optimization needs longer chains (e.g. chain length > 10,000) and a more stringent stopping criterion (e.g. Stop after # chains > 20,000). Experiment with the values and observe any differences.

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2. My population has more than 4000 loci. What settings do I adjust to let JoinMap v4/v4.1 run more responsive?

JoinMap v4 and v4.1 were not developed to deal with such large numbers of loci. Basically, the program has problems with displaying the very large tables obtained with so many records. First, you should load the data using a loc-file, as the JoinMap Dataset tabsheet will be slow and sometimes act strange. Next, uncheck the checkbox 'Load Data tabsheets' on the right hand side of the toolbar (if you occasionaly wish to inspect the genotypes, then check the box temporarily). Of the Calculation Options you can uncheck the checkboxes 'Show weak linkages' and 'Show strong linkages' and reduce the 'Number of maximum linkages' to 1 or 0 if you are not interested in them.

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3. How do I install my individual license file 'JOINMAP.LIC'?

JoinMap reads its license file 'JOINMAP.LIC' in its program file directory, which is typically 'C:\Program Files\JoinMapX' (X=version number 3 or 4). After installation of the JoinMap software the installed copy of the license file is an evaluation license. Replace that copy with your individual copy, make sure that it is called 'JOINMAP.LIC', and the JoinMap software will become fully functional. Under Windows 7 and Vista this can only be done if you are logged on as a user with 'Administrator' privileges. The easiest way is to start JoinMap from within the installation procedure (by placing the appropriate checkmark in the final screen of the installation), and next use the 'Install License' option of the JoinMap Help-menu.

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4. Why do I get the message 'JoinMap is using an evaluation license'?

When you get this message it means that JoinMap is using a license file 'JOINMAP.LIC' that only allows an evaluation of the software, with limited functionality. When you obtained a individual license file (on your installation CDROM or by e-mail), you must replace this evaluation license file with your individual license file. This individual license file usually has a file name with the extension '.JM4win' (or '.JM3win'). In the replacement of the evaluation license it should become called 'JOINMAP.LIC' (see 1.).

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5. I appear to have problems installing my individual license under Windows 7 or Vista, how do I solve this?

The problem may be caused by the fact that your individual license is installed in the so-called 'Virtual Store', which is a personal 'shadow' copy of protected Windows directories like the 'Program Files' directory. Windows uses the 'Virtual Store' for users without 'Administrator' privileges. You should place your individual license file under the name 'JOINMAP.LIC' in the directory where the executable file 'JoinMap4.exe' resides, which is typically the proper 'C:\Program Files\JoinMap4' directory. This can only be done if you are logged on as a user with 'Administrator' privileges. Make sure that you set the Windows Explorer option to see all file name extensions, otherwise you might think your file is called 'JOINMAP.LIC' whereas in reality it might be called 'JOINMAP.LIC.JM4win' and as such is not found by JoinMap.

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6. Under Windows 7 or Vista I get the successive error messages:

'Access violation at address ... in module 'uxtheme.dll' ...',
'The instruction at ... referenced memory at '0x00000000' ...',
'Runtime error 216 at ...';

what is the problem?

The errors are probably due to the Windows Desktop theme you are using. Some themes appear to be not entirely well programmed and then affect other programs functioning. You can modify your Windows Desktop theme by right-clicking on the Windows Desktop and choosing another theme on the Themes tabsheet.

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7. On which versions of MS-Windows runs JoinMap?

JoinMap 4 and 4.1 run on the 32-bit Windows platforms 7, 8, 8.1 and 10.
They will run as 32-bit software under the 64-bit versions of MS-Windows ® 7, 8, 8.1 and 10.
JoinMap 3.0 does not run properly under Vista and higher, but will run there fine under Windows XP compatibility mode. This can be achieved by right-clicking on the JoinMap3.exe-file, choosing Properties, checking on the Compatibility tab 'Run this program in compatibility mode for:' and select 'Windows XP' (any service pack).
Alternatively, the program can be run under Windows XP Mode of the Windows Virtual PC. Windows XP Mode is freely available from Microsoft for Windows 7 Professional.

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8. I have lost sight of the navigation panel; how do I get it back?

Move the mouse pointer to the left edge of the main window where the navigation panel should be. At some point the mouse pointer will change into the dragging shape; if that happens, drag the panel back into sight.
If you have difficulties with this approach, there is an alternative. You should close the program, remove the file 'JoinMap.ProgSetup' in the 'My Documents\JoinMap4' directory, and start the program again; it will restore all view settings of the program.

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9. Why do I get the message 'insufficient linkage in data to complete the map'?

The LOD grouping procedure uses linkage to any single locus already in a group to determine whether that locus belongs to that group. The mapping procedure first has LOD and REC thresholds determining what data are used, and next any marker fitted onto the map during the building process must have at least two distinct links (i.e. links to loci that themselves have r>0, so not r=0, between them) in order to establish a direction in the localization. So if there are not two distinct links due to the stringent thresholds then the program reports that there is insufficient linkage in the data, even though the locus is in the LOD grouping node.
You can set the LOD and REC thresholds for mapping to a lower stringency, so that all information necessary to obtain sufficient linkage will come available.

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10. What is the best approach to integrating maps from several populations?

First, read the previous question and answer about the more technical aspects of how to do this. Generally, the best approach is:
a) calculate maps for each population separately;
b) use fixed orders based on these separate maps to calculate the integrated map; when there are no conflicts between fixed orders, you are ready;
c) when there are conflicts between fixed orders, there are several things you can do to decide which order is the most acceptable:
1) remove the conflicting fixed orders when calculating the integrated map, and see which order is the dominant one;
2) impose the conflicting fixed orders on the separate populations, and see whether these result in acceptable solutions, i.e. reasonable chi-squares and no negative distances;
3) it may be impossible to resolve the conflicts; this can be caused by errors in the data (apply JMCHK), but also by a natural cause, i.e. there is a chromosome inversion. Of course, it is impossible to join maps in the latter case.

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11. How is the modified LOD score calculated for the recombination between two loci?

For each pair of loci a contingency table is produced of the genotypes. The dimensions of the table depend on the population type and the segregation types of the loci (unknown genotypes are ignored). From this table the G statistic (-2 times the logarithm of the likelihood ratio for the Poisson distribution, see e.g. Fienberg, 1979, The analysis of cross-classified categorical data, MIT Press) is calculated to test for independence; the expected number (E) in each cell is calculated from the row-total (R), the column-total (C) and the grand-total (T):

E = R*C/T .


The G statistic then is a summation (SUM) over all cells (O is the observed number, ln() is the natural logarithm):

G = 2 * SUM [ O*ln(O/E) ] .


The G statistic (Gd) has an approximate chi-square distribution with the number of rows in the table minus 1 multiplied by the number of columns minus 1 as the degrees of freedom (d). When the loci have different numbers of genotypes in their segregation, this would present a problem, because this number affects the degrees of freedom in the G test and in the testing of linkage one would need to take account of the degrees of freedom. In order to remove this problem and to ensure the comparability of data coming from different population or segregation types the G statistic with d degrees of freedom, Gd, is transformed approximately to a G statistic, G1, that would have been obtained if there was just a single degree of freedom (as if in a backcross). This approximate transformation is an empirically determined formula (exp() is the exponential function):

e = exp( -Gd/(2*(d-1)) ) ,

G1 = ((4-e)*e - 3)*(d-1) + Gd .


Because in genetics one is used to LOD scores, which are likelihood ratio statistics using the 10-base logarithm instead of the natural logarithm multiplied by -2, the modified LOD score (mLOD) is simply derived from G1:

mLOD = G1 / (2*ln(10)) .

It can be shown that for the case of two loci each segregating in two genotypes (e.g. population types BC1 or DH1) when there is no segregation distortion this mLOD equals the 'normal' LOD score. The modified LOD score is not sensitive to segregation distortion, in contrast to the 'normal' LOD score.

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12. How is the chi-square test for heterogeneity calculated?

From the pwd-file the locus pairs occurring more than once are collected. The pwd-file contains for each pair the recombination frequency and the modified LOD score. In this modified LOD score essentially two important corrections are contained: (1) the segregation data are insensitive to segregation distortion, and (2) the segregation data are transformed as if obtained from a backcross (BC1) under no segregation distortion; this ensures the comparability of data coming from different population or segregation types. For each pair (with two identical loci) the hypothetical number of recombinant (Nr) and non-recombinant (Nn) plants in a backcross (BC1) are calculated based on the recombination frequency (r) and the LOD score (LOD) (r and LOD are read from the pwd-file for each pair) (Nt is the total number of plants, log() is the 10-base logarithm, the numbers Nr, Nn and Nt are treated as 'real's and not as 'integer's):

since:

LOD = Nt*log(2) + r*Nt*log(r) + (1-r)*Nt*log(1-r) ,


we get:

Nt = LOD/(log(2) + r*log(r) + (1-r)*log(r)) ,


and hence:

Nr = r*Nt


and

Nn = (1-r)*Nt.


This way a contingency table is created with for each pair a row with two columns, i.e. the number of recombinants and the number of non-recombinants. From this table the G statistic is calculated to test for independence; the expected number (E) in each cell is calculated from the row-total (R), the column-total (C) and the grand-total (T):

E = R*C/T .


The G statistic then is a summation (SUM) over all cells (O is the observed number, ln() is the natural logarithm):

G = 2 * SUM [ O*ln(O/E) ] .

The G statistic has an approximate chi-square distribution with the number of pairs minus 1 as degrees of freedom. For each pair the contribution to the G test is given in the output, so that it is sometimes possible to locate the most deviant pair.

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13. How do I code loci in a CP population that have two alleles (heterozygous)in one parent and one allele (homozygous) in the other?

Loci heterozygous in one parent and homozygous in the other must be coded as loci with a segregation type <lmxll> or <nnxnp>, depending on which of the parents is heterozygous. The allele in the homozygous parents does not need to be identical to either one of the alleles in the heterozygous parent, genetically these situations are identical.

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14. JoinMap does not accept genotypes 'c' or 'd' in my backcross population (BC1). Why?

In a backcross it is assumed that P1 and P2, the parents of the F1 are fully homozygous. Therefore, as you can see in the following scheme, if a marker is present you are always sure whether the genotype must be 'a' or 'h' in a BC1a (F1 backcrossed to P1), or 'b' or 'h' in a BC1b (F1 backcrossed to P2).

          P1 a  x  P2 b
                  |
                  v
         P1 a  x  F1 h  x  P2 b
               |        |
               v        v
              BC1a     BC1b
  

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15. Against what ratio is tested in the 'Locus genot. freq.' tabsheet with RIx populations?

Loci for which in the data file the classification type is not given, the program tests a:b against the ratio 1:1. Loci for which in the data file the classification type (a,h,b) is given, the program tests a:h:b against the ratio 1:f:1 in which 'f' depends on the generation 'x' given in the RIx code to calculate the expected segregation ratio. In a similar fashion this applies also to classification types (a,c) and (b,d). The classification type can be changed for loci selected in the tabsheet using the Population menu option 'Set X2-Test Classification for Selected Loci'.

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