BOL

Here’s the quick and dirty of what was done:

1 Run minimap:

This uses a pre-built set of defaults (the ava-pb in the code below) for analyzing PacBio data. Minimap only accepts two FASTQ files and you need to map your FASTQ file against itself. So, if you have multiple FASTQ sequencing files, you have to concatenate them into a single file prior to running minimap.

minimap2 -x ava-pb -t 23 \
20170911_oly_pacbio_cat.fastq \
20170911_oly_pacbio_cat.fastq \
> 20170911_minimap2_pacbio_oly.paf

2 Run miniasm:

This uses your concatenated FASTQ file and the PAF file output from the miniasm step. The code below is taken from the example provided in the miniasm documentation; there are other options available.

miniasm \
-f \
/home/data/20170911_oly_pacbio_cat.fastq /home/data/20170911_minimap2_pacbio_oly.paf > /home/data/20170918_oly_pacbio_miniasm_reads.gfa

3 Convert miniasm output GFA to FASTA

The FASTA file is needed to re-run minimap in Step 4 below.

awk '$1 ~/S/ {print ">"$2"\n"$3}' 20170918_oly_pacbio_miniasm_reads.gfa > 20170918_oly_pacbio_miniasm_reads.fasta

4 Run minimap with default settings

Using the default settings maps the FASTQ reads back to the contigs (the PAF file) created in the fist step. These mappings are required for Racon assembly (Step 5).

minimap2 \
-t 23 \
20170918_oly_pacbio_miniasm_reads.fasta 20170905_minimap2_pacibio_oly.paf > 20170918_minimap2_mapping_fasta_oly_pacbio.paf

5 Run racon

The output file is the FASTA file listed below.

racon -t 24 \
20170911_oly_pacbio_cat.fastq \
20170918_oly_pacbio_minimap_mappings.paf \
20170918_oly_pacbio_miniasm_assembly.gfa \
20170918_oly_pacbio_racon1_consensus.fasta

from Sam’s Notebook http://ift.tt/2fKBPUN

Must read paper https://genome.cshlp.org/content/27/5/737.full

minimap2 –x ava-ont \
 ../../trimming_practical/nanofilt/nanofilt_trimmed.fastq \ 
 ../../trimming_practical/nanofilt/nanofilt_trimmed.fastq \
| gzip -1 > ./minimap.paf.gz

miniasm -f \
../../trimming_practical/nanofilt/nanofilt_trimmed.fastq \
./minimap.paf.gz > miniasm.gfa

awk ’/^S/{print “>”$2”\n”$3}’ miniasm.gfa > miniasm.fasta

assembly-stats ./miniasm.fasta

dnadiff -p dnadiff ~/course_data/precompiled/chr17.fasta miniasm.fasta

➜ mashmap-Linux64-v2.0 git:(master) ✗ ./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 <value>, --ref <value>
an input reference file (fasta/fastq)[.gz]

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

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

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

-s <value>, --segLength <value>
mapping segment length [default : 5,000]
sequences shorter than segment length will be ignored

--noSplit
disable splitting of input sequences during mapping [enabled by default]

--perc_identity <value>, --pi <value>
threshold for identity [default : 85]

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

-o <value>, --output <value>
output file name [default : mashmap.out]

-k <value>, --kmer <value>
kmer size <= 16 [default : 16]

-f <value>, --filter_mode <value>
filter modes in mashmap: 'map', 'one-to-one' or 'none' [default: map]
'map' computes best mappings for each query sequence
'one-to-one' computes best mappings for query as well as reference sequence
'none' disables filtering