FAQs
LexicMap is mainly designed for sequence alignment with a small number of queries (gene/plasmid/virus/phage sequences) longer than 100 bp by default.
If you just want to search long (>1kb) queries for highly similar (>95%) targets, you can build an index with a bigger -D/--seed-max-desert (default 100) and -d/--seed-in-desert-dist (default 50), e.g.,
--seed-max-desert 300 --seed-in-desert-dist 150
Bigger values decrease the search sensitivity for distant targets, speed up the indexing speed, decrease the indexing memory occupation and decrease the index size. While the alignment speed is almost not affected.
Yes. LexicMap mainly supports small genomes including prokaryotic, viral, and plasmid genomes.
Fungi can also be supported, just remember to increase the value of -g/--max-genome when running lexicmap index,
which is used to skip genomes larger than 15Mb by default.
-g, --max-genome int ► Maximum genome size. Extremely large genomes (e.g., non-isolate
assemblies from Genbank) will be skipped. (default 15000000)
Maximum genome size is about 268 Mb (268,435,456). More precisely:
$total_bases + ($num_contigs - 1) * 1000 <= 268,435,456
as we concatenate contigs with 1000-bp intervals of N’s to reduce the sequence scale to index.
For big and complex genomes, like the human genome (chr1 is ~248 Mb) which has many repetitive sequences, LexicMap would be slow to align.
- For index building. See details hardware requirement.
- For seaching. See details hardware requirement.
How to resume the indexing as Slurm job time limit is almost reached while lexicmap index is still in the merging step?
Use lexicmap utils remerge (available since v0.5.0), which reruns the merging step for an unfinished index.
When to use this command?
- Only one thread is used for merging indexes, which happens when there are a lot (>200 batches) of batches (
$inpu_files / --batch-size) and the value of--max-open-filesis not big enough.- The Slurm/PBS job time limit is almost reached and the merging step won’t be finished before that.
- Disk quota is reached in the merging step.
So you can stop the indexing command by press Ctrl + C (make sure it is in the merging step, see example below), and run lexicmap utils remerge -d index.lmi,
where index.lmi is the output index directory in lexicmap index.
Optionally, you might set bigger values of
flag --max-open-files and -J/--seed-data-threads if you have hundreds of thousands of input genomes or have set
a small batch size with -b/--batch-size. E.g.,
22:54:24.420 [INFO] merging 297 indexes...
22:54:24.455 [INFO] [round 1]
22:54:24.455 [INFO] batch 1/1, merging 297 indexes to xxx.lmi.tmp/r1_b1 with 1 threads...
There’s only one thread was used for seed data merging, it would take a long time.
So we can set a larger --max-open-files, e.g., 4096,
and it would allow 4096 / (297+2) = 13.7 threads for merging, let’s set --seed-data-threads 12.
# specify the maximum open files per process
ulimit -n 4096
lexicmap utils remerge -d index.lmi --max-open-files 4096 --seed-data-threads 12
Yes, lexicmap search has a flag
-a, --all ► Output more columns, e.g., matched sequences. Use this if you
want to output blast-style format with "lexicmap utils 2blast".
to output CIGAR string, aligned query and subject sequences.
21. cigar, CIGAR string of the alignment. (optional with -a/--all)
22. qseq, Aligned part of query sequence. (optional with -a/--all)
23. sseq, Aligned part of subject sequence. (optional with -a/--all)
24. align, Alignment text ("|" and " ") between qseq and sseq. (optional with -a/--all)
An example:
# Extracting similar sequences for a query gene.
# search matches with query coverage >= 90%
lexicmap search -d gtdb_complete.lmi/ b.gene_E_faecalis_SecY.fasta -o results.tsv \
--min-qcov-per-hsp 90 --all
# extract matched sequences as FASTA format
sed 1d results.tsv | awk -F'\t' '{print ">"$5":"$15"-"$16":"$17"\n"$23;}' \
| seqkit seq -g > results.fasta
seqkit head -n 1 results.fasta | head -n 3
>NZ_JALSCK010000007.1:39224-40522:-
TTGTTCAAGCTATTAAAGAACGCCTTTAAAGTCAAAGACATTAGATCAAAAATCTTATTT
ACAGTTTTAATCTTGTTTGTATTTCGCCTAGGTGCGCACATTACTGTGCCCGGGGTGAAT
And lexicmap util 2blast can help to convert the tabular format to Blast-style format,
see examples.
lexicmap utils subseq can extract subsequencess via genome ID, sequence ID and positions. So you can use these information from the search result and expand the region positions to extract flanking sequences.
It happens if there are some degenerate bases (e.g., N) in the query sequence.
In the indexing step, all degenerate bases are converted to their lexicographic first bases. E.g., N is converted to A.
While for the query sequences, we don’t convert them.
LexicMap is mainly designed for sequence alignment with a small number of queries against a database with a huge number (up to 17 million) of genomes.
There are some ways to improve the search speed of lexicmap search:
http://bioinf.shenwei.me/LexicMap/tutorials/search/#improving-searching-speed
to read more detail of the usage.