This is the command minimap that can be run in the OnWorks free hosting provider using one of our multiple free online workstations such as Ubuntu Online, Fedora Online, Windows online emulator or MAC OS online emulator
PROGRAM:
NAME
minimap - fast mapping between long DNA sequences
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:
┌────┬────────┬─────────────────────────────────────────────────────────────┐
│Col │ Type │ Description │
├────┼────────┼─────────────────────────────────────────────────────────────┤
│ 1 │ string │ Query sequence name │
│ 2 │ int │ Query sequence length │
│ 3 │ int │ Query start coordinate (0-based) │
│ 4 │ int │ Query end coordinate (0-based) │
│ 5 │ char │ `+' if query and target on the same strand; `-' if opposite │
│ 6 │ string │ Target sequence name │
│ 7 │ int │ Target sequence length │
│ 8 │ int │ Target start coordinate on the original strand │
│ 9 │ int │ Target end coordinate on the original strand │
│ 10 │ int │ Number of matching bases in the mapping │
│ 11 │ int │ Number bases, including gaps, in the mapping │
│ 12 │ int │ Mapping quality (0-255 with 255 for missing) │
└────┴────────┴─────────────────────────────────────────────────────────────┘
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.
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