#!/usr/bin/env python
# coding: utf-8

# ## Identification and assembly practical

# How do we know what our sample is?

# There are a few easy ways ... 
# 
#    - BLASTing reads
#    - OneCodex
#    - Kraken (What's in my Pot?)
# 
# 
# 

# For E. coli we will use the file:
#     
# MAP006-1.pass.2D.poRe.fastq
# 
# For the new genome use:
# 
# pc1_shigella.tar
# 
# Start with E. coli!, then move onto Shigella.

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# ## miniasm

# We will start by assembling E. coli with miniasm.

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# Install minimap and miniasm (requiring gcc and zlib)
git clone https://github.com/lh3/minimap && (cd minimap && make)
git clone https://github.com/lh3/miniasm && (cd miniasm && make)
# Overlap
minimap/minimap -Sw5 -L100 -m0 -t8 MAP006-1.pass.2D.poRe.fastq MAP006-1.pass.2D.poRe.fastq | gzip -1 > reads.paf.gz
# Layout
miniasm/miniasm -f MAP006-1.pass.2D.poRe.fastq reads.paf.gz > contigs.gfa


# We need to convert the unitigs file into a FASTA file:

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awk '/^S/{print ">"$2"\n"$3}' contigs.gfa | fold > contigs.fa


# Let's use QUAST to explore the assembly quality

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wget "http://downloads.sourceforge.net/project/quast/quast-3.2.tar.gz?r=http%3A%2F%2Fsourceforge.net%2Fprojects%2Fquast%2Ffiles%2F&ts=1450193070&use_mirror=netcologne" -O quast.tar.gz


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tar xvfz quast.tar.gz


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sudo apt-get install python-matplotlib


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quast-3.2/quast.py -R NC_000913.3.fa contigs.fa


# Download the PDF report from ``quast_results/latest``

# ## Hybrid assembly

# Convert the FASTQ file to FASTA (of course, you could have output FASTA via poretools or poRe)

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seqtk seq -A MAP006-1.pass.2D.poRe.fastq > MAP006-1.pass.2D.poRe.fasta


# Run Spades using the nanopore data and Illumina data.

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spades.py --only-assembler -k 21,51,71 -1 MiSeq/SRR2627019_1.fastq.gz -2 MiSeq/SRR2627019_2.fastq.gz --nanopore MAP006-1.pass.2D.poRe.fasta -o SPADES &