MashMap: a fast adaptive algorithm for computing whole-genome homology maps
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MashMap is an approximate algorithm for computing local alignment boundaries between long DNA sequences. Given a minimum alignment length and an identity threshold, it computes the desired alignment boundaries and identity estimates using kmer-based statistics, and maintains sufficient probabilistic guarantees on the output sensitivity.

Reference:

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Important Notes

Interactive job
Interactive jobs should be used for debugging, graphics, or applications that cannot be run as batch jobs.

Allocate an interactive session and run the program. Sample session:

[user@biowulf]$ sinteractive --mem=8g --cpus-per-task=16
[user@cn3200 ~]$module load MashMap 
[+] Loading GSL 2.5 for GCC 7.2.0 ... 
[+] Loading MashMap  2.0 
[user@cn3200 ~]$ mashmap -h
-----------------
Mashmap is an approximate long read or contig mapper based on Jaccard
similarity
-----------------
Example usage:
$ mashmap -r ref.fa -q seq.fq [OPTIONS]
$ mashmap --rl reference_files_list.txt -q seq.fq [OPTIONS]

Available options
-----------------
-h, --help
    Print this help page

-r , --ref 
    an input reference file (fasta/fastq)[.gz]

--refList , --rl 
    a file containing list of reference files, one per line

-q , --query 
    an input query file (fasta/fastq)[.gz]

--ql , --queryList 
    a file containing list of query files, one per line

...

-t , --threads 
    count of threads for parallel execution [default : 1]

-o , --output 
    output file name [default : mashmap.out]
...
Download testing data from the PacBio's release of Human 54x long-read coverage dataset
(http://datasets.pacb.com/2014/Human54x/fastq.html ): 
[user@cn3200 ~]$ wget http://datasets.pacb.com/2013/Human10x/READS/2530572/0001/Analysis_Results/m130929_024849_42213_c100518541910000001823079209281311_s1_p0.1.subreads.fastq -O test_seq.fq

--2019-01-10 12:08:07--  http://datasets.pacb.com/2013/Human10x/READS/2530572/0001/Analysis_Results/m130929_024849_42213_c100518541910000001823079209281311_s1_p0.1.subreads.fastq
Resolving dtn04-e0 (dtn04-e0)... 10.1.200.240
Connecting to dtn04-e0 (dtn04-e0)|10.1.200.240|:3128... connected.
Proxy request sent, awaiting response... 200 OK
Length: 361764079 (345M) [application/octet-stream]
Saving to: ‘test_seq.fq’

100%[===============================================================>] 361,764,079 96.8MB/s   in 3.6s

2019-01-10 12:08:11 (96.2 MB/s) - ‘test_seq.fq’ saved [361764079/361764079]
Specify a human reference GRCh38 sequence: 
[user@cn3200 ~]$ ln -s /fdb/igenomes/Homo_sapiens/NCBI/GRCh38/Sequence/WholeGenomeFasta/genome.fa human_GRCh38.fa
Run the software on these data with 16 threads: 
[user@cn3200 ~]$ mashmap -r human_GRCh38.fa -q test_seq.fq -t 16
>>>>>>>>>>>>>>>>>>
Reference = [human_GRCh38.fa]
Query = [test_seq.fq]
Kmer size = 16
Window size = 111
Segment length = 5000 (read split allowed)
Alphabet = DNA
Percentage identity threshold = 85%
Mapping output file = mashmap.out
Filter mode = 1 (1 = map, 2 = one-to-one, 3 = none)
Execution threads  = 16
>>>>>>>>>>>>>>>>>>
INFO, skch::Sketch::build, minimizers picked from reference = 52513331
INFO, skch::Sketch::index, unique minimizers = 17607584
INFO, skch::Sketch::computeFreqHist, Frequency histogram of minimizers = (1, 9361370) ... (116827, 1)
INFO, skch::Sketch::computeFreqHist, With threshold 0.001%, ignore minimizers occurring >= 5534 times during lookup.
INFO, skch::main, Time spent computing the reference index: 58.0907 sec
INFO, skch::Map::mapQuery, [count of mapped reads, reads qualified for mapping, total input reads] = [11978, 13497, 25249]
INFO, skch::main, Time spent mapping the query : 21.6042 sec
INFO, skch::main, mapping results saved in : mashmap.out
The result will be stored in the file 'mashmap.out'.

End the interactive session: 
[user@cn3200 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$