If you encounter any issue, please feel free to directly contact me at kklam@eecs.berkeley.edu My name is Ka-Kit Lam.

Our paper is located at http://biorxiv.org/content/early/2014/10/14/010215

Here is the command to run the tool:

python finisherSC.py destinedFolder mummerPath

Note that it is assumed that you have "contigs.fasta" , "raw_reads.fasta" in the destinedFolder and mummerPath is your path to Mummer. Therefore, please rename the files in the destinedFolder if needed. For "finisherSC.py", the key output file is improved3.fasta in destinedFolder.

Here is an example run with the pre-installed data files and softwares(e.g. Mummer, Gepard) [Please go to https://www.dropbox.com/sh/xjpt8xf5g1xf0ek/bGmZvt9Zfd to Download the EColi-Data set as test cases coz it is too big for GitHub].

1. You may run the test cases as python finisherSC.py EcoliTestRun/ MUMmer3.23/
2. After the processing, take the file whose name is improved3.fasta in destinedFolder and this is your output file.
3. If you want to visualize the output against the reference, you can use software like Gepard.

a)Fast mode (e.g. for large and complex genomes , you may want to use this mode to get results faster; However, there will be a bit of computation vs quality trade-off if you want to use this mode; We suggest that you use this mode only when you got stuck in the standard mode):

python finisherSC.py destinedFolder mummerPath -f True 

[It means that you want to use the fast mode ]

b)Pick from previous jobs (e.g. you have got improved2.fasta but the cluster node timeout and you want to start from improved2.fasta instead of from scratch)

python finisherSC.py destinedFolder mummerPath  -p improved2.fasta

c)Mapping between old contigs and new contigs(e.g. you want to know how the contigs from contigs.fasta are mapped to improved3.fasta )

python finisherSC.py destinedFolder mummerPath -o contigs.fasta_improved3.fasta

[It will then output the alignment of improved3.fasta against contigs.fasta. The output will be shown in the terminal and in mappingResults.txt at the destinedFolder]

d)There is an experimental improvement based on repeat phasing and the further improved file is improved4.fasta. An illustration of that part is given in Fig. 7 of http://arxiv.org/abs/1402.6971 . To experiment with that, first run finisherSC.py as before. After that, you can issue the following command:

python experimental/xPhaser.py destinedFolder mummerPath

e) There is also an experimental improvement resolving tandem repeat. The further improved file is tademResolved.fasta. To experiment with that, first run finisherSC.py as before. After that, you can issue the following command:

python experimental/tSolver.py destinedFolder mummerPath

f)Help. You can always use -h to get the usage suggestion.

python finisherSC.py -h

1. After passing through the finishingTool, it is advised to use a polishing tool(e.g. Quiver) to polish the improved contigs( i.e. improved3.fasta )
2. If you have problem running scipy.weave, try to remove ~/.python27_compiled