LAST Tutorial

LAST finds similar regions between sequences, and aligns them.

Example 1: Compare the human and fugu mitochondrial genomes

For our first example, we wish to find and align similar regions between the human and fugu mitochondrial genomes. You can find these sequences in the examples directory: humanMito.fa and fuguMito.fa. We can compare them like this:

lastdb -cR01 humdb humanMito.fa
lastal humdb fuguMito.fa > myalns.maf

The lastdb command creates several files whose names begin with "humdb". The lastal command then compares fuguMito.fa to the humdb files, and writes the alignments to a file called "myalns.maf".

The "-cR01" option suppresses alignments caused by simple sequence such as cacacacacacacacacacacaca.

Understanding the output

The output has very long lines, so you need to view it without line-wrapping. For example, with a Unix/Linux/MacOsX command line, you can use:

less -S myalns.maf

Each alignment looks like this:

a score=27 EG2=4.7e+04 E=2.6e-05

The score is a measure of how significant the similarity is. EG2 and E are explained at last-evalues.html. Lines starting with "s" contain: the sequence name, the start coordinate of the alignment, the number of bases spanned by the alignment, the strand, the sequence length, and the aligned bases.

The start coordinates are zero-based. This means that, if the alignment begins right at the start of a sequence, the coordinate is 0. If the strand is "-", the start coordinate is in the reverse strand.

This alignment format is called MAF (multiple alignment format). You can convert it to several other formats using maf-convert. You can make lastal produce a few other formats with option -f (see lastal.html).

Example 2: Compare vertebrate proteins to invertebrate proteins

Use the lastdb -p option to indicate that the sequences are proteins:

lastdb -p -cR01 invdb invertebrate.fa
lastal invdb vertebrate.fa

Example 3: Compare DNA sequences to protein sequences

Here we use the -F15 option, to specify translated alignment with a score penalty of 15 for frameshifts:

lastdb -p -cR01 protdb proteins.fa
lastal -F15 protdb dnas.fa

Example 4: Find short protein alignments

LAST uses a scoring scheme to find similarities. Some scoring schemes are good for long-and-weak similarities, others for short-and-strong similarities. If we seek very short similarities, weak ones are hopeless (statistically insignificant), so we had better focus on strong ones. The PAM30 scoring scheme may work well:

lastdb -p -cR01 invdb invertebrate.fa
lastal -pPAM30 invdb vertebrate.fa

(How short is "very short"? It depends on the amount of sequence data we are searching, but perhaps roughly less than 40 amino acids.)

Example 5: Align human DNA sequences to the human genome

We can align human DNA sequences to the human genome like this:

lastdb -uNEAR -R01 humandb human/chr*.fa
lastal humandb queries.fa | last-split > myalns.maf

This will use about 15 gigabytes of memory.

Example 6: Find very short DNA alignments

By default, LAST is quite strict, and only reports significant alignments that will rarely occur by chance. In the preceding example, the minimum alignment length is about 28 bases (less for smaller genomes). To find shorter alignments, we must down-tune the strictness:

lastdb -uNEAR -R01 humandb human/chr*.fa
lastal -D100 humandb queries.fa | last-split -m1 > myalns.maf

In this example, the minimum alignment length is about 20 bases (less for smaller genomes).

Example 7: Align human fastq sequences to the human genome

DNA sequences are not always perfectly accurate, and they are sometimes provided in fastq format, which indicates the reliability of each base. LAST can use this information to improve alignment accuracy. (It assumes the reliabilities reflect substitution errors, not insertion/deletion errors: if that is not true, it may be better to use fasta format.) Option -Q1 indicates fastq-sanger format:

lastdb -uNEAR -R01 humandb human/chr*.fa
lastal -Q1 -D100 humandb queries.fastq | last-split > myalns.maf

Fastq format confusion

Unfortunately, there is more than one fastq format (see Recently (2013) fastq-sanger seems to be dominant, but if you have another variant you need to change the -Q option (see lastal.html).

Paired reads

If you have paired reads, there are two options:

  1. Use last-pair-probs (see last-pair-probs.html).

  2. Ignore the pairing information, and align the reads individually (using last-split as above). This may be useful because last-pair-probs does not currently allow different parts of one read to match different parts of the genome, though it does allow the two reads in a pair to match (e.g.) different chromosomes.

Tuning speed, sensitivity, memory and disk usage

Example 8: Compare the cat and rat genomes

If you have ~50 GB of memory and don't mind waiting a few days, this is a good way to compare such genomes:

lastdb -uMAM8 -cR11 catdb cat.fa
lastal -m100 -E0.05 catdb rat.fa | last-split -m1 > out.maf

This looks for a unique best alignment for each part of each rat chromosome. Omitting -m100 makes it faster but somewhat less sensitive. Omitting -uMAM8 reduces the memory use to ~10 GB and makes it faster but considerably less sensitive.

This recipe aligns each rat base-pair to at most one cat base-pair, but not necessarily vice-versa. You can get strictly 1-to-1 alignments by swapping the sequences and running last-split again:

maf-swap out.maf | last-split -m1 > out2.maf

Example 9: Compare the human and chimp genomes

For strongly similar genomes (e.g. 99% identity), something like this is more appropriate:

lastdb -uNEAR -cR11 human human.fa
lastal -m50 -E0.05 human chimp.fa | last-split -m1 > out.maf

Example 10: Ambiguity of alignment columns

Consider this alignment:

|||||||| ||||||  |  ||  | |  |    || ||||||   |||||||||||

The middle section has such weak similarity that its precise alignment cannot be confidently inferred.

It is sometimes useful to estimate the ambiguity of each column in an alignment. We can do that using lastal option -j4:

lastdb -cR01 humdb humanMito.fa
lastal -j4 humdb fuguMito.fa > myalns.maf

The output looks like this:

a score=17 EG2=9.3e+09 E=5e-06
p                %*.14442011.(%##"%$$$$###""!!!""""&'(*,340.,,.~~~~~~~~~~~

The "p" line indicates the probability that each column is wrongly aligned, using a compact code (the same as fastq-sanger format):

Symbol Error probability Symbol Error probability
! 0.79 -- 1 0 0.025 -- 0.032
" 0.63 -- 0.79 1 0.02 -- 0.025
# 0.5 -- 0.63 2 0.016 -- 0.02
$ 0.4 -- 0.5 3 0.013 -- 0.016
% 0.32 -- 0.4 4 0.01 -- 0.013
& 0.25 -- 0.32 5 0.0079 -- 0.01
' 0.2 -- 0.25 6 0.0063 -- 0.0079
( 0.16 -- 0.2 7 0.005 -- 0.0063
) 0.13 -- 0.16 8 0.004 -- 0.005
* 0.1 -- 0.13 9 0.0032 -- 0.004
+ 0.079 -- 0.1 : 0.0025 -- 0.0032
, 0.063 -- 0.079 ; 0.002 -- 0.0025
- 0.05 -- 0.063 < 0.0016 -- 0.002
. 0.04 -- 0.05 = 0.0013 -- 0.0016
/ 0.032 -- 0.04 > 0.001 -- 0.0013

Note that each alignment is grown from a "core" region, and the ambiguity estimates assume that the core is correctly aligned. The core is indicated by "~" symbols, and it contains exact matches only.

LAST has options to find alignments with optimal column probabilities, instead of optimal score: see lastal.html.