Startup possibilities

UniMoG can be started in console modus or with a graphical user interface.
For using the console modus two parameters have to be provided:

1. The scenario: 1 = DCJ, 2 = rDCJ, 3 = HP, 4 = Inversion, 5 = Translocatin, 6 = All scenarios at once
2. The path to a single file containing all genomes which should be analyzed

Genome Representation

The loaded files have to contain at least two, but can contain several genomes.
Every genome starts with a > followed by the genome name.
In the following line(s) come the genes. 'Newlines' are ignored.
Each chromosome is concluded by a closing parenthesis ')' or a vertical bar '|'. A ) concludes a circular chromosome, a | concludes a linear chromosome and can be omitted for the last chromosome of a genome, leaving it linear. The gene names can contain all signs except whitespaces. A - before a gene name means that the gene direction is reverse.
Each pairwise comparison takes into account only genes that occur in both genomes of the pair.
Every line that starts with '//' has no function and is treated as a comment. Everything before the first genome is a comment and leading whitespaces of a genome name are ignored.

As an input example consider the three genomes:

>Genome A 2 -1 3 | 5 -4 6 )
> Genome B 2 1 3 | 6 5 4 |
>Genome C 2 3 1 | 5 6 4 7 8 |

A simple example file can be found here.
A more complex example file that shows the possibilities can be found here.

Optimal DCJ, rDCJ, HP, Inversion and Translocation Distance and Sorting

The program can compute five different genomic distances and optimal sorting scenarios: The DCJ, restricted DCJ, HP (Hannenhalli & Pevzner), Inversion and Translocation distance and an optimal corresponding sorting. All five distance and sorting algorithms were implemented under the aspect of efficiency and in most cases feature the most efficient algorithms known until today. Links to the corresponding papers can be found below.

Output example:

The output consists of the three tabs 'Genomes', 'Adjacencies' and 'Graphics'.
The 'Genomes' tab either starts with informative messages, if a genome comparison fails or singleton genes have to be removed from a genome, or directly starts with the distance results as a distance matrix, if the input consists of more than two genomes. Otherwise the distances are returned in their context:

or if only Genome B and Genome C are compared with the HP model:

A '-' in the distance results means that the distances for this pair could not be calculated. Certain rules for the different distance models, explained below under 'Rules', have to be obeyed.

The graphical output will look like this for each pairwise comparison:

The fragments emerging from the two cuts (red vertical ticks in the chromosome) of each step are highlighted by colored lines, each with a different color. The lines for the current step are located below the chromosome, while the lines depicting the fragments of the previous step are located above the chromosome of the current step.

Detailed explanations of the DCJ model and how it can be used for calculating the rDCJ, HP, inversion and translocation distances are given in the following papers:

• The DCJ model is explicated in [13] and improved and simplified in [3].
• The restricted DCJ model is introduced in [9].
• How DCJ serves as a basis for HP, inversion and translocation distances is explained in [4], while [5] provides the correct distance formula. The running time of all distance computations is thus linear.

The other models and the sorting algorithms are described here:

• The HP model was first introduced in [6] and further studied in [10]. The sorting algorithm used in this implementation is composed of: [12] as a basis for the preprocessing including the correction provided by [8]. As suggested in [12] the sorting itself is then carried out by the inversion sorting algorithm referred to in the next item. Therefore, the sorting process runs in quadratic time, which is determined by the used inversion sorting algorithm.
• The inversion model was first solved in polynomial time in [7] and the most efficient, subquadratic sorting algorithm is described in [11]. Here, we implement the second most efficient, quadratic time algorithm, also described in [11], with the aid of the data structures from [1].
• The translocation model and the implemented cubic sorting algorithm are described in [2]. This algorithm was chosen because in practice its running time is almost always linear.

Rules

For a successful genome comparison the following rules have to be obeyed:

• The DCJ distance calculation can handle all kinds of genomes without restrictions
• The restricted DCJ model works for linear chromosomes and directly reincoporates all emerging circular chromosomes in the next step (modelling block interchanges and transpositions).
• The HP distance calculation requires linear chromosomes
• The translocation distance requires linear chromosomes with the same telomeres.
• The inversion distance requires one linear chromosome with the same telomeres in both genomes.

Program Usage - Step by Step

• First click on and choose at least one file that contains at least two genomes. Or alternatively click to work with a small example file.
• Then choose the genomes to compare in the lists below and select one of the five possible scenarios. The 'All' scenario means that all four scenarios are calculated at once, if applicable.
• By pressing the Button the genomes will be compared. The results are shown in the tabs in the lower part of the window.
• • The first tab first shows the distance in a matrix for more than two genomes or otherwise in context with the chosen scenario and afterwards the stepwise transformation for all pairs of genomes.
  • The second tab shows the adjacencies (junctions) between the genes. The suffix '_h' represents the head of a gene and '_t' the tail of a gene. Chromosomes are separated by '{content1} , {content2}' including the whitespaces for an easier localization of a chromosome end.
  • The third tab contains a graphical representation of the transformation of all pairs of genomes with highlighted operations.
• Before running the comparison:
• • You can decide if only the distances are of interest and the sorting scenarios are not needed (makes the calculation also much faster). In this case deselect the checkbox, otherwise keep it selected.
  • You can choose a coloring method for the graphic:
    If you select each chromosome has a distinct color, otherwise they have a white background.
• You can also adjust the size of the output using the size slider with three different sizes.
• A graphic result can be saved as jpg image by clicking on .
• The whole textual results can be saved in a txt file by clicking on .
• All values and results can be cleared by the button.
• The button terminates the program.
• If you want to look at the help directly from the program, click on .