Select reads from a read collection
mirabait [-f <fromtype>] [-t <totype> [-t <totype> ...]] [-iklor] baitfile infile <basename_for_outfile(s)>
mirabait selects reads from a read collection which are partly similar or equal to sequences defined as target baits. Similarity is defined by finding a user-adjustable number of common k-mers (sequences of k consecutive bases) which are the same in the bait sequences and the screened sequences to be selected, either in forward or reverse complement direction.
-f <fromtype>
load this type of project files, where fromtype is:
caf
sequences from CAF
maf
sequences from MAF
phd
sequences from a PHD
gbf
sequences from a GBF
fasta
sequences from a FASTA
fastq
sequences from a FASTQ
-t <totype>
write the sequences to this type (multiple mentions of -t are allowed):
fasta
sequences to FASTA
fastq
sequences to FASTQ
caf
sequences to CAF
maf
sequences to MAF
txt
sequence names to text file
-k
k-mer, length of bait in bases (<32, default=31)
-n
Min. number of k-mer baits needed (default=1)
-i
Inverse hit: writes only sequences that do not hit bait
-r
No checking of reverse complement direction
-o
fastq quality Offset (only for -f = 'fastq') Offset of quality values in FASTQ file. Default: 33 A value of 0 tries to automatically recognise.
-f <fromtype>
load this type of project files, where fromtype is:
caf
sequences from CAF
maf
sequences from MAF
phd
sequences from a PHD
gbf
sequences from a GBF
fasta
sequences from a FASTA
fastq
sequences from a FASTQ
-t <totype>
write the sequences to this type (multiple mentions of -t are allowed):
fasta
sequences to FASTA
fastq
sequences to FASTQ
caf
sequences to CAF
maf
sequences to MAF
txt
sequence names to text file
-k
k-mer, length of bait in bases (<32, default=31)
-n
Min. number of k-mer baits needed (default=1)
-i
Inverse hit: writes only sequences that do not hit bait
-r
No checking of reverse complement direction
-o
fastq quality Offset (only for -f = 'fastq') Offset of quality values in FASTQ file. Default: 33 A value of 0 tries to automatically recognise.
Bastien Chevreux ([email protected])