SYNOPSIS

minimap [-lSOV] [-k kmer] [-w winSize] [-I batchSize] [-d dumpFile] [-f occThres] [-r bandWidth] [-m minShared] [-c minCount] [-L minMatch] [-g maxGap] [-T dustThres] [-t nThreads] [-x preset] target.fa query.fa > output.paf

DESCRIPTION

Minimap is a tool to efficiently find multiple approximate mapping positions between two sets of long sequences, such as between reads and reference genomes, between genomes and between long noisy reads. Minimap has an indexing and a mapping phase. In the indexing phase, it collects all minimizers of a large batch of target sequences in a hash table; in the mapping phase, it identifies good clusters of colinear minimizer hits. Minimap does not generate detailed alignments between the target and the query sequences. It only outputs the approximate start and the end coordinates of these clusters.

OPTIONS

Indexing options

-k INT

Minimizer k-mer length [15]

-w INT

Minimizer window size [2/3 of k-mer length]. A minimizer is the smallest k-mer in a window of w consecutive k-mers.

-I NUM

Load at most NUM target bases into RAM for indexing [4G]. If there are more than NUM bases in target.fa, minimap needs to read query.fa multiple times to map it against each batch of target sequences. NUM may be ending with k/K/m/M/g/G.

-d FILE

Dump minimizer index to FILE [no dump]

-l

Indicate that target.fa is in fact a minimizer index generated by option -d, not a FASTA or FASTQ file.

Mapping options

-f FLOAT

Ignore top FLOAT fraction of most occurring minimizers [0.001]

-r INT

Approximate bandwidth for initial minimizer hits clustering [500]. A minimizer hit is a minimizer present in both the target and query sequences. A minimizer hit cluster is a group of potentially colinear minimizer hits between a target and a query sequence.

-m FLOAT

Merge initial minimizer hit clusters if FLOAT or higher fraction of minimizers are shared between the clusters [0.5]

-c INT

Retain a minimizer hit cluster if it contains INT or more minimizer hits [4]

-L INT

Discard a minimizer hit cluster if after colinearization, the number of matching bases is below INT [40]. This option mainly reduces the size of output. It has little effect on the speed and peak memory.

-g INT

Split a minimizer hit cluster at a gap INT-bp or longer that does not contain any minimizer hits [10000]

-T INT

Mask regions on query sequences with SDUST score threshold INT; 0 to disable [0]. SDUST is an algorithm to identify low-complexity subsequences. It is not enabled by default. If SDUST is preferred, a value between 20 and 25 is recommended. A higher threshold masks less sequences.

-S

Perform all-vs-all mapping. In this mode, if the query sequence name is lexicographically larger than the target sequence name, the hits between them will be suppressed; if the query sequence name is the same as the target name, diagonal minimizer hits will also be suppressed.

-O

Drop a minimizer hit if it is far away from other hits (EXPERIMENTAL). This option is useful for mapping long chromosomes from two diverged species.

-x STR

Changing multiple settings based on STR [not set]. It is recommended to apply this option before other options, such that the following options may override the multiple settings modified by this option.

ava10k

for PacBio or Oxford Nanopore all-vs-all read mapping (-Sw5 -L100 -m0).

Input/output options

-t INT

Number of threads [3]. Minimap uses at most three threads when collecting minimizers on target sequences, and uses up to INT+1 threads when mapping (the extra thread is for I/O, which is frequently idle and takes little CPU time).

-V

Print version number to stdout

OUTPUT FORMAT

Minimap outputs mapping positions in the Pairwise mApping Format (PAF). PAF is a TAB-delimited text format with each line consisting of at least 12 fields as are described in the following table:

When the alignment is available, column 11 gives the total number of sequence matches, mismatches and gaps in the alignment; column 10 divided by column 11 gives the alignment identity. As minimap does not generate detailed alignment, these two columns are approximate. PAF may optionally have additional fields in the SAM-like typed key-value format. Minimap writes the number of minimizer hits in a cluster to the cm tag.