The MUMmer 3 examples

## Table of Contents

1. Introduction
2. Examples
   1. mapview
      1. Running promer
      2. Running mapview
      3. Viewing the output
   2. mummer
      1. Running mummer
      2. Running mummerplot
      3. Viewing the output
   3. nucmer
      1. Running nucmer
      2. Running show-coords
      3. Running show-snps
      4. Running show-tiling
      5. Viewing the output
   4. promer
      1. Running promer
      2. Running show-coords
      3. Running show-aligns
      4. Viewing the output
   5. run-mummer1
      1. Running run-mummer1
      2. Viewing the output
   6. run-mummer3
      1. Running run-mummer3
      2. Viewing the output
3. Contact information

## 1. Introduction

Because of its breadth MUMmer can, at first glance, be an overwhelming sea of scripts and subroutines. This document attempts to walk the user through some of the more useful modules of the package, and provides example data and expected outputs to assure the correct and productive operation of MUMmer. All example data is real DNA sequence from various eukaryotic and prokaryotic organisms, and can be found in its entirety in the data directory. Although the input sequences are only subsections of their respective genomes, they have been carefully selected to permit speedy and informative walk-throughs. It is not necessary to download all of the data at once, as each subsection will have separate links to the relevant files.

For further information regarding any of the MUMmer programs or their output formats, please refer to the online MUMmer manual.

## 2. Examples

### 2.1. mapview

MapView is a utility script for displaying sequence alignments as provided by NUCmer or PROmer. It takes the output from `show-coords` and converts it to a FIG, PDF or PS image file. By default, it produces FIG files which can be viewed with the common system utility `xfig` or converted to PDF or PS with the `fig2dev` utility (neither programs are included with MUMmer). `mapview` is useful for mapping multiple query contigs (e.g. from a draft sequencing project) against an annotated reference sequence. Exons and other features can also be plotted with the NUCmer or PROmer alignments, aiding in exon refinement and analysis. Individual MUMmer hits are plotted according to their percent identity, making regions of high or low similarity easily distinguishable.

In the following sections, a short example is given that demonstrates how to use `mapview`. Since `nucmer` and `promer` have a near identical user interface, the alignments for this example will be generated using `promer`. This example aligns a few query sequences to a single reference sequence using `promer`, and then uses `mapview` to plot the resulting areas of conservation and the reference sequence annotation.

##### The following input files will be used to demonstrate this example:

- `D_melanogaster_2Rslice.cds`
- `D_melanogaster_2Rslice.fasta`
- `D_melanogaster_2Rslice.utr`
- `D_pseudoobscura_contigs.fasta`

##### The following output files will be generated by this example:

- `mapview_0.fig`
- `mapview_0.pdf`
- `promer.coords`

#### 2.1.1. Running promer

Please complete the PROmer walk-though in order to generate the alignment between the Drosophila melanogaster chromosome 2R segment and the 2 contigs from Drosophila pseudoobscura. The PROmer walk-through will generate the `.coords` file that is necessary to continue with the rest of this tutorial. If already familiar with the `promer` alignment script, simply continue this tutorial using the supplied `promer.coords` file. Note that when generating the `.coords` file with `show-coords` it is important to use the `-l -r` options (and optionally the `-k` option) in order to generate the proper input format for `mapview`.

#### 2.1.2. Running mapview

The output of `show-coords` is then used by MapView to create a FIG, PDF or PS file.

`mapview -n 1 -p mapview promer.coords`

The `-n` option is used to set the number of output files to 1. By default, MapView partitions its output among 10 files in order to keep the figures for large comparisons small. Since we are only comparing a small slice of the actual chromosome, only 1 file will be needed. The output of this command will be a single file named `mapview_0.fig`. A more informative plot can be generated by supplying a UTR and CDS coordinate file in GFF format. These files contain annotation information that will be plotted along side the PROmer alignments, thus making it possible to compare the conserved regions with annotated exon positions.

`mapview -n 1 -p mapview promer.coords D_melanogaster_2Rslice.utr D_melanogaster_2Rslice.cds`

This will generate a single file, `mapview_0.fig`, that will have the annotation information displayed above the blue reference rectangle. Below, you can see this file displayed with the xfig viewer. The only difference between this file and the file produced without the UTR and CDS files are the annotation rectangles above the blue rectangle at the very top of the figure.

In order to generate a PDF format, use the same command plus the `-f pdf` option.

`mapview -n 1 -f pdf -p mapview promer.coords D_melanogaster_2Rslice.utr D_melanogaster_2Rslice.cds`

This will generate the same image, `mapview_0.pdf`, but in PDF format.

#### 2.1.3. Viewing the output

The above MapView FIG shows a 220 kbp slice of D. melanogaster chromosome 2L and its alignment to D. pseudoobscura. The alignment, generated by PROmer, shows all regions of conserved amino acid sequence. The blue rectangle spanning the figure represents the reference (D. melanogaster), with annotated genes shown above it and the PROmer alignments shown below it. Alternative splice variants of the same gene are stacked vertically. Exons are shown as boxes, with intervening introns connecting them. The 5' and 3' UTRs are colored pink and blue to indicate the gene's direction of translation. PROmer matches are shown twice, once just below the reference genome, where all matches are collapsed into red boxes, and in a larger display showing the separate matches within each contig, where the contigs are colored differently to indicate contig boundaries. The vertical position of the matches indicates their percent identity, ranging from 50% at the bottom of the display to 100% just below the red rectangles. Percent identity is of the amino acid translations used by PROmer. Matches from the same query sequence are connected by lines of the same color.

### 2.2. mummer

`mummer` is a suffix tree algorithm designed to find maximal exact matches of some minimum length between two input sequences. The match lists produced by `mummer` can be used alone to generate alignment dot plots, or can be passed on to the clustering algorithms for the identification of longer non-exact regions of conservation. These match lists have great versatility because they contain huge amounts of information and can be passed forward to other interpretation programs for clustering, analysis, searching, etc.

In the following sections, a short example is given that demonstrates how to use `mummer`. This example compares a single query sequence to a single reference sequence using `mummer`, and then uses `mummerplot` to generate a dot plot representation of the comparison.

##### The following input files will be used to demonstrate this example:

- `H_pylori26695_Eslice.fasta`
- `H_pyloriJ99_Eslice.fasta`

##### The following output files will be generated by this example:

- `mummer.gp`
- `mummer.mums`
- `mummer.fplot`
- `mummer.rplot`
- `mummer.ps`

#### 2.2.1. Running mummer

`mummer` can handle multiple reference and multiple query sequences, however a dotplot of more that two sequences can be confusing, so for the case of this example we will be dealing with a single reference and a single query sequence.

`mummer -mum -b -c H_pylori26695_Eslice.fasta H_pyloriJ99_Eslice.fasta > mummer.mums`

This command will find all maximal unique matches (`-mum`) between the reference and query on both the forward and reverse strands (`-b`) and report all the match positions relative to the forward strand (`-c`). Output is to `stdout`, so we will redirect it into a file named `mummer.mums`. This file lists all of the MUMs of the default length or greater between the two input sequences.

#### 2.2.2. Running mummerplot

A dotplot of all the MUMs between two sequences can reveal their macroscopic similarity.

`mummerplot -x "[0,275287]" -y "[0,265111]" -postscript -p mummer mummer.mums`

This command will plot all of the MUMs in the `mummer.mums` file in postscript format (`-postscript`) between the given ranges for the X and Y axes. When plotting `mummer` output, it is necessary to use the lengths of the input sequences to set the plot ranges, otherwise the plot will be automatically scaled around the minimum and maximum data points. The four output files are prefixed by the string specified with the `-p` option. The `plot` files contains the data points, `mummer.gp` is a gnuplot script for plotting the data points in the `plot` files, and `mummer.ps` is the postscript plot generated by the gnuplot script. Below, you can see the `mummer.ps` file displayed with ghostview. Note that with newer versions of `mummerplot` the color and thickness of the plot lines may be different.

Most image manipulation programs can edit the postscript output, or it can be sent directly to a printer with the `lpr` command. If you would rather use the default terminal for gnuplot, simply remove the `-postscript` option from the `mummerplot` call.

#### 2.2.3. Viewing the output

The above postscript plot represents the set of all MUMs between the two input sequences used in this example. Forward MUMs are plotted as red lines/dots while reverse MUMs are plotted as green lines/dots (blue may be used for reverse matches in newer versions). A line of dots with slope == 1 represents an undisturbed segment of conservation between the two sequences, while a line of slope == -1 represents an inverted segment of conservation between the two sequences. The green segment in the upper left quadrant of the graph shows both an inversion and translocation, as it is of negative slope and inconsistently located relative to the rest of the plot which falls on a line approximated by f(x) = x. However the green segment in the upper right quadrant of the graph shows only an inversion, as it is of negative slope but is consistent in location with the rest of the plot. Generally, the closer a plot is to an imaginary line f(x) = x (or -x) the fewer macroscopic differences exist between the two sequences.

### 2.3. nucmer

`nucmer` is the MUMmer's most user-friendly alignment script for standard DNA sequence alignment. It is a robust pipeline that allows for multiple reference and multiple query sequences to be aligned in a many vs. many fashion. For instance, a very common use for `nucmer` is to determine the position and orientation of a set of sequence contigs in relation to a finished sequence, however it can be just as effective in comparing two finished sequences to one another.

In the following sections, a short example is given that demonstrates how to use `nucmer`. This example aligns a set of draft sequence contigs to a finished sequence using `nucmer`; displays the alignment coordinates using `show-coords`; and tiles them across the reference using `show-tiling`.

##### The following input files will be used to demonstrate this example:

- `B_anthracis_Mslice.fasta`
- `B_anthracis_contigs.fasta`

##### The following output files will be generated by this example:

- `nucmer.cluster`
- `nucmer.coords`
- `nucmer.delta`
- `nucmer.snps`
- `nucmer.tiling`

#### 2.3.1. Running nucmer

Like `mummer`, `nucmer` can handle multiple reference and query sequences, however it is most commonly used to map a set of query sequences to a single reference sequence. This example will demonstrate that functionality, as a number of B. anthracis draft contigs will be mapped to the final assembly.

`nucmer -maxmatch -c 100 -p nucmer B_anthracis_Mslice.fasta B_anthracis_contigs.fasta`

To assure all contigs were mapped, all maximal matches were used as alignment anchors (`-maxmatch`) and because of the sequence similarity the minimum cluster size was bumped up to 100 (`-c 100`). The two output files are prefixed by the string specified with the `-p` option. `nucmer.cluster` lists all of the maximal exact match clusters that were used in generating the alignments, while `nucmer.delta` is an encoded file that represents the alignment between the two inputs. At this stage, the alignment of the two inputs is complete, however it is necessary to parse the `nucmer.delta` file with the provided utilities in order to extract useful information from the comparison.

#### 2.3.2. Running show-coords

To view a summary of all the alignments produced by NUCmer, we need to run the `nucmer.delta` file through the `show-coords` utility.

`show-coords -r -c -l nucmer.delta > nucmer.coords`

This command will list the coordinates, percent identities and other useful statistics of each alignment in a table. Each line of the table represents an individual pairwise alignment, and each line is sorted by its starting reference coordinate (`-r`). Additional information, like alignment coverage (`-c`) and sequence length (`-l`) can be added to the table with the appropriate options. Output is to `stdout`, so we have redirected it into the file, `nucmer.coords`.

#### 2.3.4. Running show-snps

To view a summary of all the SNPs and indels between the two sequence sets, we need to run the `nucmer.delta` file through the `show-snps` utility.

`show-snps -C nucmer.delta > nucmer.snps`

This will generate a report of all the SNPs internal to the alignments contained in the `nucmer.delta` file. Each line of the table represents a single mismatch in the pairwise alignment. With the `-C` option, only SNPs from uniquely aligned regions will be reported. Additional information can be added or removed with the command line switches described in the manual. Output is to `stdout`, so we have redirected it into the file, `nucmer.snps`.

#### 2.3.5. Running show-tiling

To produce a minimal tiling of contigs across the reference sequence, we need to run the `nucmer.delta` file through the `show-tiling` utility.

`show-tiling nucmer.delta > nucmer.tiling`

This command will list the contigs and positions that generate the maximal alignment coverage across the reference sequence using the fewest contigs possible. This output can aid the closure of a draft genome when a closely related organism has already be finished.

#### 2.3.6. Viewing the output

`nucmer` and `show-tiling` output can both be viewed with `mummerplot`, however these plots would offer little more information in regards to this example. `mapview` can also be used to display the output of `show-coords`, as is shown in the mapview walkthrough.

### 2.4. promer

`promer` is a close relative to the NUCmer script. It follows the exact same steps as NUCmer and even uses most of the same programs in its pipeline, with one exception - all matching and alignment routines are performed on the six frame amino acid translation of the DNA input sequence. This provides `promer` with a much higher sensitivity than `nucmer` because protein sequences tends to diverge much slower than their underlying DNA sequence. Therefore, on the same input sequences, `promer` may find many conserved regions that `nucmer` will not, simply because the DNA sequence is not as highly conserved as the amino acid translation.

In the following sections, a short example is given that demonstrates how to use `promer`. This example aligns a few query sequences to single reference sequence using `promer`; displays the alignment coordinates using `show-coords`; and prints a pairwise alignment of one of the contigs using `show-aligns`.

##### The following input files will be used to demonstrate this example:

- `D_melanogaster_2Rslice.fasta`
- `D_pseudoobscura_contigs.fasta`

##### The following output files will be generated by this example:

- `promer.aligns`
- `promer.cluster`
- `promer.coords`
- `promer.delta`

#### 2.4.1. Running promer

Like `mummer`, `promer` can handle multiple reference and query sequences, however it is most commonly used to map a set of query sequences to a single reference sequence. This example will demonstrate that functionality, as two D. pseudoobscura draft contigs will be mapped to the final D. melanogaster assembly.

`promer -p promer D_melanogaster_2Rslice.fasta D_pseudoobscura_contigs.fasta`

Default parameters were used to align the two inputs, however if the alignment is too sensitive or not sensitive enough the minimum match length and cluster sizes can be adjusted accordingly. The two output files are prefixed by the string specified with the `-p` option. `promer.cluster` lists all of the maximal exact match clusters that were used in generating the alignments, while `promer.delta` is an encoded file that represents the alignment between the two inputs. At this stage, the alignment of the two inputs is complete, however it is necessary to parse the `promer.delta` file with the provided utilities in order to extract useful information from the comparison.

#### 2.4.2. Running show-coords

To view a summary of all the alignments produced by PROmer, we need to run the `promer.delta` file through the `show-coords` utility.

`show-coords -r -c -l -L 100 -I 50 promer.delta > promer.coords`

This command will list the coordinates, percent identities and other useful statistics of each alignment in a table. Each line of the table represents an individual pairwise alignment, and each line is sorted by its starting reference coordinate (`-r`). Additional information, like alignment coverage (`-c`) and sequence length (`-l`) can be added to the table with the appropriate options. And minimum length (`-L`) and minimum percent identity (`-I`) cutoffs can be specified to reduce poor alignments. Output is to `stdout`, so we have redirected it into the file, `promer.coords`. If this file is planned for input to `mapview`, it is important to always use the `-r` `-c` `-l` options.

#### 2.4.3. Running show-aligns

To view all the pairwise alignments between two of the input sequences, we need to run the `promer.delta` file through the `show-coords` utility.

`show-aligns promer.delta "D_melanogaster_2Rslice" "3214968" > promer.aligns`

This command will print all of the pairwise alignments stored in the `promer.delta` file for the sequences "D_melanogaster_2Rslice" and "3214968". Output is to `stdout`, so we have redirected it into the file, `promer.aligns`. If the alignments do not fit within your screen width, or you would like them to be printed on longer lines, the screen width can be adjusted with the `-w` option. Since `show-aligns` only displays the alignments between two sequences, it will have to be run separately for each desired pair of sequences.

#### 2.4.4. Viewing the output

`promer` and `show-tiling` output can both be viewed with `mummerplot`, however these plots would offer little more information in regards to this example. `mapview` can also be used to display the output of `show-coords`, as is shown in the mapview walkthrough which uses the `promer.coords` file generated in this example to generate a plot of the alignment.

### 2.5. run-mummer1

`run-mummer1` is a legacy script from the original MUMmer1.0 release. It has been updated to utilize the new suffix tree code of version 3.0, however all other programs called from this script are identical to the original MUMmer release back in 1999. Even though it is an outdated program, it still has some advantages over the newer alignment scripts (`nucmer`, `promer`, `run-mummer3`). Like all of the alignment scripts, `run-mummer1` is a three step process - matching, clustering and extension. However, unlike the newer alignment scripts, `run-mummer1` uses the `gaps` program for its clustering step. The `gaps` program does not allow for rearrangements like `mgaps`, instead if finds the single longest increasing subset of matches across the full length of both sequences. This makes it well suited for SNP and small indel identification between small (< 10 Mbp), very similar sequences with few to no rearrangements.

In the following sections, a short example is given that demonstrates how to use `run-mummer1`. This example aligns a single query sequence to a single reference sequence using `run-mummer1`.

##### The following input files will be used to demonstrate this example:

- `H_pylori26695_Bslice.fasta`
- `H_pyloriJ99_Bslice.fasta`

##### The following output files will be generated by this example:

- `mummer1.align`
- `mummer1.errorsgaps`
- `mummer1.gaps`
- `mummer1.out`

#### 2.5.1. Running run-mummer1

`run-mummer1` is only suited for a single reference and query sequence that have few to zero inversions or translocations. This example aligns two such sequences.

`run-mummer1 H_pylori26695_Bslice.fasta H_pyloriJ99_Bslice.fasta mummer1`

To adjust the minimum match length for the comparison, the user must manually edit the `run-mummer1` script. Output files are prefixed by the string specified at the end of the command line call. `mummer1.align` displays the alignments of each gap between adjacent MUMs, `mummer1.errorsgaps` lists each MUM and the number of errors between it and the previous MUM, `mummer1.gaps` lists the ordered set of MUMs and the gap distance to the previous MUM, and `mummer1.out` simply lists all of the MUMs greater than or equal to the minimum match length.

#### 2.5.2. Viewing the output

There are no visualization tools designed for `run-mummer1` output. To view a MUM dotplot, run `mummer` by itself on two individual sequence as demonstrated in the mummer walkthrough.

### 2.6. run-mummer3

`run-mummer3` is the simplest pipeline of the latest MUMmer3.0 programs. It runs the same matching and clustering algorithm as `nucmer` and `promer`, however it uses a different extension technique and does not perform the important pre- and post-processing steps of NUC/PROmer. Because of its simplistic form, `run-mummer3` can only handle a single reference sequence, but like `run-mummer1` its error-focused output makes it a handy tool for detecting SNPs and other small errors. The only major difference between `run-mummer3` and `run-mummer1` is the new version's ability to handle multiple query sequences and its tolerance of large rearrangements. This makes `run-mummer3` well suited for error detection between highly similar sequences that may have large rearrangements, inversions etc.

In the following sections, a short example is given that demonstrates how to use `run-mummer3`. This example aligns a single query sequence to a single reference sequence using `run-mummer3`.

##### The following input files will be used to demonstrate this example:

- `H_pylori26695_Eslice.fasta`
- `H_pyloriJ99_Eslice.fasta`

##### The following output files will be generated by this example:

- `mummer3.align`
- `mummer3.errorsgaps`
- `mummer3.gaps`
- `mummer3.out`

#### 2.6.1. Running run-mummer3

`run-mummer3` can only handle a single reference sequence, but it is capable of dealing with multiple query sequences. However, this example aligns a single query sequence to a single reference sequence. Unlike `run-mumer1`, `run-mummer3` can handle inversions and translocations, but not with the same grace as `nucmer`.

`run-mummer3 H_pylori26695_Bslice.fasta H_pyloriJ99_Bslice.fasta mummer3`

To adjust any of the alignment parameters, the user must manual edit the `run-mummer3` scripts. Do not, however, add the `-c` option to the `mummer` invocation, as it will confuse the next steps in the pipeline. It may be easier to reverse complement the sequence yourself and run the script twice (once for forward, second for reverse) with the `-b` option removed. Try adding the `-D` option to the `combineMUMs` command line in the script to output a format that is easier to parse for SNPs and small indels. Output files are prefixed by the string specified at the end of the command line call. `mummer3.align` displays the alignments of each gap between adjacent MUMs, `mummer3.errorsgaps` lists each MUM and the number of errors between it and the previous MUM, `mummer3.gaps` lists the ordered set of MUMs and the gap distance to the previous MUM, and `mummer3.out` simply lists all of the MUMs greater than or equal to the minimum match length.

#### 2.6.2. Viewing the output

The `mummer3.out` file is identical to the output of `mummer` on a 1 vs many search, so it may be plotted as demonstrated in the mummer walkthrough.

## 3. Contact information

Please address questions and bug reports via Email to:

VERSION 3.17 - May 2005