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• Convert code to run using Biopython rather than exporting commands to the os.system? - this would be the more correct way of doing things
• Decide on an approach to manage the issue of Transcript to gene ID mapping redundancy
• Incorporate an E-value threshold into our analysis
• Discuss with Adrian the possibility of running blast remotely on Apocrita - If we can't we'll have to run it locally on a laptop & reduce the size of the input data
• Tackle the issue of transcripts not identified by Blast but present in multiple samples/at high FPKM?

See comments in module.py: the duplicates are being deleted without directly considering the reason as to why: the evalues are all the highest for each respective duplicate but this is another layer of optimising and may be supererogatory.

Hi,

I'm going to implement some changes to imrpove the functionality with apocrita; but James as we're using your apocrita access only you can change the script thats being called within apocrita.

for the BLAST job i've increased the number of threads to be in line with what's being asked for in apocrita -> to 4 threads.

Furthermore, the default for qsub jobs is 1 core,
I was reviewing the apocrita guide (http://docs.hpc.qmul.ac.uk/using/): you need to add this line to the script:

#$ -pe smp 4       # Request 4 CPU cores

and you can lower the RAM per core to 1 GB instead of 3 ( so we get 1 GB per core)

Oh yeah, the BLAST OS workaround is totally fine, but I would suggest maybe rescripting the FPKM implemntation part after the BLAST section to run in python and not use the cmd functions.

Could have raw_input from user for number of columns and use this object throughout so it overcomes the 3 groups barrier? Alternatively if this proves to be too difficult; to meet the deadline we can have a set of hardcoded R scripts for various group numbers and call the appropriate script according to the number of groups the end-user picks in FLASK

• Get the user to input the number of experimental groups and their names
• User login -> we can then email a pdf of the results to the user on completion of analysis
• make some sort of loading page/giff the show whilst the results are being computed
• how to manage multiple users?

Instead of it being limited to just Pteropus Alecto, we will give the user a choice of species from a drop down list: they can pick Pteropus Alecto or Mice or Human (Homo sapiens).

1. I will try and set up each major DB
2. We need a FLASK incorperated dropdown list
3. Once the user picks the species we then need to specify that THIS is the db we will carry out the BLAST against.

In order to enable this, we can incorporate the intrinsic session ID present in FLASK.

We just need to assign " user session " ID to each of the the files uploaded and carry this through each step of the temp files generated in the analysis etc.

Hi all,
google pandoc
Install pandoc.
Edit your Word document as needed.
Run pandoc from the linux or Windows command line. ...
Update the ChangeLog.
Commit both files with git git add file.docx file.md git commit

we can use this to collectively write the documentation :)

OR a group google doc I don't mind!

• make the script fully soft-coded
• derive names for graphs/variables etc from myArgs group list
• make work with different number of input groups?
• introduce new functionality? perhaps gene ontology visualisations