git clone https://github.com/jflot/PlayAssembly
cd PlayAssembly
./install.sh
Add the PlayAssembly and PlayAssembly/BRAW folder to your $PATH:
export PATH=~/PlayAssembly/:~/PlayAssembly/BRAW/:$PATH
To generate single reads 150-bp long with a 50X coverage and a 0.01 (=1%) error rate:
simulator ecoli.fa 150 50 0.01 ecoli_15_50_0.01 (the perfect reads are stored in a file named p.ecoli_15.50_0.01.fasta, and the simulated reads with errors in ecoli_15.50_0.01.fasta)
To generate paired reads 150-bp long with 700 bp fragment size (= read lengths + distance between the reads), a 50X coverage and a 0.01 (=1%) error rate in the PE (→ ←) orientation (for the ← → choose MP):
pairedSimulator random.fa 150 700 50 0.01 random_150_700_50_0.01 PE
To correct a read file using Bloocoo:
Bloocoo -file random_150_700_50_0.01.fasta (this outputs a file with name ending with *_corrected.fasta)
To check the result of the correction:
correctionEvaluator p.ecoli_15_50_0.01.fa ecoli_15_50_0.01.fa ecoli_15_50_0.01_corrected.fasta
To assemble a file of reads using minia
minia -in ecoli_15_50_0.01.fa
To assemble a file of reads using a specific k value
minia -in ecoli_15_50_0.01.fa -kmer-size 63
To check the statistics of the resulting assembly
n50 ecoli_15_50_0.contigs.fa
Compare the assembly of 150-bp reads without error, with 1% error or with 1% error but corrected with Bloocoo: what difference do you see? What happens with a higher (e.g. 5%) error rate? What is the effect of using paired-end reads rather than single reads? What difference do you see when using longer reads (250 bp)?
How does the N50 of the assembly by minia change according to the k value chosen (you can try e.g. k=21, k=31, k=41 etc. and plot the results using e.g. R or xmgrace)?
Compare the assembly of reads generated from the E. coli genome with the assembly of reads generated from the random sequence (of the same length): which one has the greater degree of continuity (i.e. the greater N50)? What could explain this?