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Cerulean Hybrid Genome Assembler v0.1.1 This software extends contigs assembled using short read datasets like Illumina paired-end reads using long reads like PacBio RS long reads. The method is fully described in: Deshpande, V., Fung, E. D., Pham, S., & Bafna, V. (2013). Cerulean: A hybrid assembly using high throughput short and long reads. arXiv preprint arXiv:1307.7933. A] Requirements: Ubuntu 12.04 (may run on other operating systems, but not tested) Python 2.7.1 (may run on older versions, but not tested) numpy, matplotlib libraries for Python ABySS assembler: SMRT Analysis tookit (for BLASR): PBJelly: B] Inputs and Pre-processing: i) Assembled contigs from ABySS short read assembler ii)Mapping of Pacbio reads to ABySS contigs using BLASR i) Assembly of Illumina paired-end reads: If the paired-end reads are stored in fastq format in the files reads1.fastq and reads2.fastq, then contigs may be assembled by: $ abyss-pe k=64 n=10 in='reads1.fastq reads2.fastq' name=<dataname> This will generate 2 files used for inputs to Cerulean: * <dataname>-contigs.fa #This contains the contig sequences * <dataname> #This contains the graph structure ii)Mapping PacBio reads to ABySS contigs using BLASR: Note: sawriter and blasr are part of SMRT Analysis toolkit Note: You need to set the environmental variables and path: $ export SEYMOUR_HOME=/opt/smrtanalysis/ $ source $SEYMOUR_HOME/etc/ Suppose PacBio reads are stored in <dataname>_pacbio.fasta $ sawriter <dataname>-contigs.fa $ blasr <dataname>_pacbio.fa <dataname>-contigs.fa -minMatch 10 \ -minPctIdentity 70 -bestn 30 -nCandidates 30 -maxScore -500 \ -nproc <numthreads> -noSplitSubreads \ -out <dataname>_pacbio_contigs_mapping.fasta.m4 Make sure the fasta.m4 file generated has the following format: qname tname qstrand tstrand score pctsimilarity tstart tend tlength \ qstart qend qlength ncells The file format may be verified by adding the option -header to blasr. C] Execute: Cerulean requires that all input files are in the same directory <basedir>: i) <basedir>/<dataname>-contigs.fa ii) <basedir>/<dataname> iii) <basedir>/<dataname>_pacbio_contigs_mapping.fasta.m4 To run: $ python src/ --dataname <dataname> --basedir <basedir> \ --nproc <numthreads> This will generate: i) <basedir>_cerulean.fasta ii) <basedir> Note: The dot does not have same contigs as fasta, but intermediate graph. D] Post-processing: Currently Cerulean does not include consensus sequence of PacBio reads in gaps The gaps may be filled using PBJelly. $ python $JELLYPATH/ <dataname>_cerulean.fasta <dataname>_cerulean.qual $ python $JELLYPATH/ <dataname>_pacbio.fasta <dataname>_pacbio.qual $ cp $JELLYPATH/lambdaExample/Protocol.xml . $ mkdir PBJelly Modify Protocol.xml as follows: Set <reference> to $PATH_TO_<basedir>/<dataname>_cerulean.fasta Set <outputDir> to $PATH_TO_<basedir>/PBJelly Set <baseDir> to $PATH_TO_<basedir> Set <job> to <dataname>_pacbio.fasta Set <blasr> option -nproc <numthreads> Note: PBJelly requires that the suffix be .fasta and not .fa Next run PBJelly: ($ source $JELLYPATH/ $ python $JELLYPATH/ <stage> Protocol.xml where <stage> has to be in the order: setup mapping support extraction assembly output The assembled contigs may be view in <basedir>/PBJelly/assembly/jellyOutput.fasta In case of any questions or errors please contact vdeshpan eng DT ucsd DT edu
Source: README, updated 2013-08-15