smartdenovo
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Ultra-fast de novo assembler using long noisy reads
Getting Started
# Download sample PacBio from the PBcR website
wget -O- http://www.cbcb.umd.edu/software/PBcR/data/selfSampleData.tar.gz | tar zxf -
awk 'NR%4==1||NR%4==2' selfSampleData/pacbio_filtered.fastq | sed 's/^@/>/g' > reads.fa
# Install SMARTdenovo
git clone https://github.com/ruanjue/smartdenovo.git && (cd smartdenovo; make)
# Assemble (raw unitigs in wtasm.lay.utg; consensus unitigs: wtasm.cns)
smartdenovo/smartdenovo.pl -c 1 reads.fa > wtasm.mak
make -f wtasm.mak
Introduction
SMARTdenovo is a de novo assembler for PacBio and Oxford Nanopore (ONT) data. It produces an assembly from all-vs-all raw read alignments without an error correction stage. It also provides tools to generate accurate consensus sequences, though a platform dependent consensus polish tools (e.g. Quiver for PacBio or Nanopolish for ONT) are still required for higher accuracy.
SMARTdenovo consists of several separate command line tools: wtzmo for read
overlapping, wtgbo to rescue missing overlaps, wtclp for identifying
low-quality regions and chimaera, and wtcns or wtmsa to produce better
unitig consensus. The smartdenovo.pl script provides a convenient interface
to call these programs in one go. If you do not care about the internal of
SMARTdenovo, you may simply run with:
/path/to/smartdenovo/smartdenovo.pl -p prefix -c 1 reads.fa > prefix.mak
make -f prefix.mak
It calls other SMARTdenovo executables in the same directory containing
smartdenovo.pl. After assembly, the raw unitigs are reported in file
prefix.lay.utg and consensus unitigs in prefix.cns. If you want to know
more about how SMARTdenovo works in detail, please see README-tools.md.
New development
Most time of assembly is spent on Smith-Waterm alignment, which might be not necessary to long reads assembly. We are developping a novel algorithm, called dot matrix alignment , which is smith-waterman free.
wtzmo now supports dot matrix alignment by add option -U -1 -m 0.1. run_dmo.sh works
well on E.coli, Yeast PacBio dataset, Bacteria ERS554120, and drosopila.