# dist.seqs

The dist.seqs command will calculate uncorrected pairwise distances between aligned DNA sequences. This approach is better than the commonly used DNADIST because the distances are not stored in RAM, rather they are printed directly to a file. Furthermore, it is possible to ignore “large” distances that one might not be interested in. The command will generate a column-formatted distance matrix that is compatible with the column option in the various cluster commands. The command is also able to generate a phylip-formatted distance matrix. There are several options for how to handle gap comparisons and terminal gaps. This tutorial uses the data files in amazondata.zip.

## Default settings

To run dist.seqs an alignment file must be provided in fasta format. By default an gap is only penalized once, terminal gaps are penalized, all distances are calculated, and only one processor is used. To save time, filter out the leading and trailing periods with the filter.seqs command. Running the following command will generate amazon.unique.dist

mothur > filter.seqs(fasta=amazon.unique.fasta, trump=.)
mothur > dist.seqs(fasta=amazon.unique.filter.fasta)


By default, dist.seqs will only count a string of gaps as a single gap and will penalize for terminal gaps

## Options

### calc

mothur has several ways of calculating a distance based on how gaps are treated. First, the default option - onegap - only counts a string of gaps as a single gap. For example:

SequenceA  ATGCATGCATGC
SequenceB  ACGC---CATCC


Would have two mismatches and one gap. The length of the shorter sequence is 10 nt, since the gap is considered as a single position. Therefore the distance would be 3/10 or 0.30. This is the distance calculating method employed by Sogin et al. (1995). The logic behind this type of penalty is that a gap represents an insertion and it is likely that a gap of any length represents a single insertion. This can be called within mothur by the command:

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, calc=onegap)


DNADIST actually ignores gaps. For example the two sequences above would have a distance of 2/9 or 0.2222. This type of distance calculation does not make much sense for sequences that are known to have a significant number of insertions. This can be used in mothur using the nogaps option. mothur can use this distance calculating method with the command:

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, calc=nogaps)


A another option is to penalize each gap. For the two sequences above, the distance would be 5/12 or 0.4167. This can be used in mothur using the eachgap option. mothur can use this distance calculating method with the command:

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, calc=eachgap)


#### Mothur also has several methods to calculate the distances between protein sequences.

jtt (Jones-Taylor-Thornton matrix):

mothur > dist.seqs(fasta=protein.fasta, calc=jtt)


pmb (Henikoff/Tillier PMB matrix)

mothur > dist.seqs(fasta=protein.fasta, calc=pmb)


pam (Dayhoff PAM matrix)

mothur > dist.seqs(fasta=protein.fasta, calc=pam)


kimura (Kimura formula)

mothur > dist.seqs(fasta=protein.fasta, calc=kimura)


Protein calculators are based on work by https://evolution.genetics.washington.edu/phylip/credits.html.

### countends

There is some discussion over whether to penalize gaps that occur at the end of sequences. For example, consider the following sequences:

Sequence1 ATGCATGCATGC
Sequence2 ---CAAGTA---


If terminal gaps are penalized, as is the default (and we are using the calc=onegap option), then the distance would be 4/8 or 0.5000. If they are not penalized, then the distance would be 2/6 or 0.3333. Ideally, all sequences would be aligned over the same region; however, if this is not possible or desired for some reason the ends option can be employed to tell mothur to ignore the penalization:

mothur > dist.seqs(fasta= amazon.unique.filter.fasta, countends=F)


The default is for countends to equal T.

### cutoff

If you know that you are not going to form OTUs with distances larger than 0.10, you can tell mothur to not save any distances larger than

0.10. This will significantly cut down on the amount of hard drive space required to store the matrix. This can be done as follows:

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, cutoff=0.10)


Without setting cutoff to 0.10 this command would have generated 4560 distances (i.e. 96x95/2 = 4560). With the cutoff only 56 distances are saved. The savings can be substantial when there are a large number of distances. The actual cutoff used by the command is 0.005 higher than the value that is set to allow for rounding in the clustering steps.

### processors

The processors option will allow you to multiple processors to calculate a distance matrix. Default processors=Autodetect number of available processors and use all available. Multiple processors can be called as follows:

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, cutoff=0.10, processors=2)


### output

The output option allows you specify the form of the matrix generated by dist.seqs. By default, dist.seqs will generate a column-formatted matrix. You can set the output to “lt”, for a phylip formatted lower triangle matrix, or to “square” for a phylip formatted square matrix. If output is set to lt or square the cutoff option is ignored.

mothur > dist.seqs(fasta=amazon.unique.filter.fasta, output=lt)


### oldfasta & column

These parameters are used to append to a column-formatted distance matrix. Given a column matrix, a new fasta file and a old fasta file we add distances to the original distance matrix calculated with the old fasta file.

mothur > dist.seqs(oldfasta=amazon.unique.fasta, column=amazon.unique.dist, fasta=esophagus.unique.fasta)


## Revisions

• 1.22.0 - Added processors option for Windows users.
• 1.39.0 - Removes cutoff adjust.
• 1.40.0 - Rewrite of threaded code. Default processors=Autodetect number of available processors and use all available.
• 1.43.0 - Improves speed of dist.seqs and pairwise.seqs.#653
• 1.46.0 - Adds jtt, pmb, pam and kimura calculators to dist.seqs to find distances between protein sequences. #776