Requirements
This program is designed to run on Windows XP SP3 or Vista SP1 systems that have the .NET 2.0 framework installed, which is freely available from Microsoft .
Genotyping should be performed using very high density SNP microarrays such as Affymetrix SNP5 or SNP6 chips. SNP6 data files must be annotated with chromosome and positional data, which can conveniently be done using SNPAnnotator.
Assumptions
The basic algorithm used by DominantMapper works on four assumptions:
- The disease is a dominant condition.
- All the affected individuals have the same mutation.
- All the carriers are affected and are not mosaic for a new germline mutation.
- If unaffected sib data is included in the analysis the mutation must demonstrate complete penetrance.
Data entry
The data shown in this user guide relates to the pedigree shown in Figure 1, where SNP data is available for the individuals marked with an asterisk. The family has been shown to contain a dominant mutation in the TSPAN12 gene at 120 Mb on Chromosome 7. While the pedigree contains a number of nuclear families, SNP data is only available for both parents in two families (parents 3 - 4, and 11 - 12). The affected children of the other families are not analysed separately as part of a distinct family, but rather as affected relatives of one of the other families.
Figure 1
Adding parents
Figure 2
Each family to be analysed is added sequentially and must include both parents, one of whom is affected, and have at least one affected child. To add the parents, press the appropriate button (Figure 2, underlined in blue for an affected parent and red for the unaffected parent) and select the correct SNP data file. The name of the file is then displayed by the program (underlined in Figure 2).
Adding children from affected families
Figure 3
Affected and unaffected children are added using the buttons on the Affected children and Unaffected children panels (highlighted by green and orange rectangles respectively in Figure 2). Data for an affected child is added using the button (underlined in red, Figure 3) and the name of the SNP data file is added to the drop-down list below the button. To remove a genotype file select its name in the drop-down list and press the button (underlined in blue in Figure 3). Similarly, the data for unaffected children is added and removed using the appropriate buttons in the Unaffected children panel.
Adding affected relatives
Figure 4
It is possible to include affected individuals who belong to the same pedigree, but whose parent data is incomplete or absent (e.g. individuals 5, 15 and 17 in Figure 1). These affected relatives are included by pressing the button on the Affected relatives panel (highlighted by the red line, Figure 4) and the file name appears in the drop-down list. Selecting a file name in the drop-down list and pressing the button removes the file.
Adding a family
Figure 5
Once the parents, children and affected relatives have been added, the family can be stored by the program by pressing the button (underlined in red, Figure 5) on the Add family panel. The family name is created by combining the affected and unaffected parents’ file names, and is added to the drop-down list in the Add family panel. Families can be removed by selecting their family name and pressing the button (underlined in blue, Figure 5). Pressing the button (underlined in green, Figure 5) removes the selected family from the drop-down list and re-populates the family data into the Parents, Affected children, Unaffected children and Affected relatives panels, from where the family data can be edited and then re-added to the family drop-down list by pressing the button again. Once a family has been added the process can be repeated for other nuclear families in the pedigree.
Viewing the analysis results
Analysing and viewing the data
Figure 6
To analyse the SNP genotype data, press the button (underlined by the red line, Figure 6) and choose which distance units you wish to use on the File details form. Only those distance units present in the affected parent’s SNP data file of the first family are available to be selected. In Figure 6 only the option is available, as the file contains no genetic map positions.
Once the mapping units have been selected, the program will load the SNP data and then test each SNP for missing genotypes (nocalls) and non-Mendelian inheritance. SNPs that fail these tests will be excluded from further linkage analysis. However these SNPs may hold important information regarding the location of large insertions and deletions in the patient's genome, consequently it is possible to view the location of SNPs with aberrant genotype patterns (Figure 14). The remaining SNPs are then tested against a set of rules to identify SNPs that can be excluded from linkage to the disease loci. Once this analysis is complete the and buttons (above the blue and green lines in Figure 6) will become active. Pressing the button displays the Text Output window, which allows regions showing linkage to the disease phenotype to be exported as a text file (Figure 12). While pressing the button will open a new window displaying the results of the analysis (Figure 7).
The results window displays data for one chromosome at a time, and is composed of two regions which display the analysis results (Figure 7). The upper region (orange bar to the right of Figure 7) shows the results of the rule-based analysis for each SNP, while the lower region (black bar to the right of Figure 7) shows a graph of an empirically derived score, plotted against chromosome position. The chromosomal map position is shown between the two regions; the units are either Mb or cM, according to the unit selection made at the start of the analysis. The discontinuous thick blue line below the scale represents the positions of the SNPs, with gaps identifying regions with no SNP coverage.
Figure 7
As with SAMPLE, IBDfinder and AutoSNPa, the results are intended to be assessed visually, and have not undergone statistical analysis. Rather, these programs perform comparisons of genotypes across large segments of the genome, in order to make inferences about common ancestry of such regions. Since these chromosomal fragments have undergone relatively few recombinational events, their size is very variable, and not of itself an indicator of the likelihood of harbouring a disease gene.
Results window – upper region
The upper region is composed of 5 horizontal ribbons on which vertical bars representing SNPs are displayed; the colour of the bar represents the linkage status of the SNPs as follows:
| Green: | Uninformative SNPs. |
|---|---|
| Orange: | SNPs excluded because an affected relative and an affected child are homozygous for different alleles. |
| Yellow: | SNPs excluded because an affected child and unaffected child are homozygous for the same allele, while their affected parent is heterozygous. |
| Red: | SNPs excluded because affected children are homozygous for different alleles. |
The lowest strip combines all the information for each exclusion criterion, with regions that show an extended run of green markers being consistent with linkage to the disease gene.
N.B. The data used to create Figure 7 does not contain any unaffected children; consequently there are no yellow markers in this figure.
Results window – lower region
The lower region may display either the linkage exclusion data or the occurrence of SNPs with missing or contradictory genotype data. Initially, linkage exclusion data is shown, with the and radio buttons used to toggle between the two views (underlined in grey in Figure 7)
Linkage exclusion graphical view
Due to the limited screen resolution, compared to the large number of SNPs per chromosome, multiple SNPs are likely to occupy the same pixel on the screen. It is consequently difficult to discern visually whether a region has been excluded by just a few or by many SNPs. To give an indication of the number of SNPs that exclude a region, the lower region of the display shows a graph of the number of non-excluding SNPs in a sliding SNP window. For a region to be identified as having possible linkage, no more than 3 SNPs in sliding SNP window can have an excluding genotype pattern. The size of this window is set using the drop-down list box (Figure 7, underlined in red). Since most SNPs are uninformative, the graph only shows regions that have 25 or fewer excluding SNPs. The horizontal gridlines indicate the number of excluding SNPs in the window, at intervals of 5 excluding SNPs. Figures 8–10 show the results for Chromosome 7 (which in this family is known to carry a dominant TSPAN12 mutation located at ~120 Mbp.
A
B
C
Figure 8
By default, this graph is plotted as a line graph, with the points positioned at the centre of each SNP window. However, since SNP density is not uniform along the chromosome, it is alternatively possible to view the graph as a series of or that indicate the extents of the windows (Figures 8B, C). While the view displays the width of a window, it is possible for regions to overlap, making them appear to be one wide region. To overcome this, the plot highlights points where regions overlap. These different plots are selected using the drop-down menu (underlined in green in Figure 7).
View options
Below the graph is a series of controls for changing the view options of the two display regions, and for saving the underlying data. These include the and controls described above, while the listbox (underlined in blue in Figure 7) allows selection of which used to select which chromosome is displayed. (The current chromosome is also indicated at the left-hand side of the title bar.) For example, to view Chr. 7, select 7 from the list (Figure 7, blue underlining).
A
B
C
Figure 9
The list controls the display of the plot of the number of non-excluding SNPs in the lower part of the display. The size of the sliding window can be set to 100, 200, 300 or 400 SNPs; the latter three settings are illustrated in Figure 9A-C respectively).
Export data
Figure 10
The data underlying a region of interest can be exported either to a colour-coded web page or to a tab-delimited text file. To select such a region, place the mouse cursor at the start of the region and while holding down the left mouse button, drag the cursor to the end of the region. The currently selected region will be delimited by two black vertical lines (Figure 10). To save the data, press (underlined in red, Figure 10) and enter the name of the output file and filename extension.
It is also possible to create a web page containing the image of the analysis for each of the chromosomes (Figure 11) by clicking the button (underlined in blue in Figure 10).
Figure 11
Exporting regions of linkage as a text file
Figure 12
Once the analysis is complete, pressing the button (Figure 6) displays the Text output window (Figure 12), which enables regions showing linkage to the disease phenotype to be exported as a text file. The Text output window contains two drop down lists, the first allows the user to export data from all the chromosomes (by selecting 'All') or from a single chromosome. As in the Graphical display window described above (Figure 7), for a region to be identified as having possible linkage, no more than 3 SNPs in a continuous run of SNPs can have an excluding genotype pattern. The minimum length of the run of SNPs is set using the drop down list. Once the chromosome(s) and window size has been selected, the linkage data is exported by pressing the button and entering the export file's name. This file contains a list of the files in the analysis followed by a table of regions sorted by chromosome and chromosomal position. The chromosome, start and end points as well as its length are given for each region, followed by the RS name of the SNPs that delimit the region (Figure 13).
Figure 13
Viewing the location of SNPs with missing or inconsistent genotype data
During the data entry process SNPs are discarded if they do not show non-Mendelian inheritance or contain a missing genotype (nocall). The underlying error may occur for a number of reasons, with the position of discarded SNPs randomly spread across the genome. However, if a comparatively high number of discarded SNP occur in a small region it may infer the presence of a copy-number variation (CNV). Since CNVs have been implicated as causes of both dominant and recessively inherited diseases, DominantMapper is also able to display the location of discarded SNPs by selecting the NoCalls option (underlined in grey in Figure 14).
Figure 14
For each pair of consecutive SNPs that are included in the final analysis, the number of discarded SNPs that occurred between them is noted. The average number of discarded SNPs across 10 overlapping pairs of SNPs is then displayed graphically. Positions that have an excess of discarded SNPs compared the background level can be seen as a number of elevated black dots (red rectangle in Figure 14). If the average number of discarded SNPs is greater than 5, the corresponding data point is shown as having a value of 5. Also, if an individual is incorrectly included in a nuclear family, many of the SNP will appear to display non-Mendelian inheritance, giving a characteristic profile in this view (Figure 15)
Figure 15
The underlying data can be exported has either a tab delimited text file (Figure 17) or a web page (Figure 16). As with the Linkage display, data is selected by placing the mouse cursor at the start of the region and while holding down the left mouse button, dragging the cursor to the end of the region. The currently selected region will be delimited by two black vertical lines. To save the data, press the button and enter the name of the output file and filename extension.
Figure 17
Figure 16
Last modified: Wed, 15th Apr 2020, at 10:53 pm