###Jupyter Notebooks and data supplemental to the manuscript: "Up in arms: Immune and nervous system response to sea star wasting disease"

---

The repository includes jupyter notebooks (.ipynb file) that can be downloaded locally and interactively executed. The code in the jupyter notebook eimd_analysis.ipynb will process data such that analysis can be reproduced.

---

###Description of Files and Directories

• eimd_analysis.ipynb - Jupyter notebook that can be interactively executed locally or viewed online designed so that user can replicate analysis. Requires several dependancies.
• eimd_data-only.ipynb - Jupyter notebok that can be interactively executed locally or viewed online designed so that user can simply explore data files. Only requires IPython.
• data/Phel_transcriptome.fasta - P hel coelocytes transcriptome. Contains 29476 contigs from de novo assembly.
• data/Phel_countdata.txt - Tab-delimited text file with read count data from 6 P hel RNA-seq libraries, 3 treated and 3 control libraries.
• scripts/count_fasta.pl - Perl script: Author: Joseph Fass (modified from script by Brad Sickler) last revised: November 2010 - bioinformatics.ucdavis.edu.
• wd - subdirectory that serves as output directory (working directory) when the repository is downloaded and the notebook eimd_analysis.ipynb is executed locally.
• precompiled_wd - subdirectory that provides data that will be produced in wd by running commands in notebook. Used primarily for viewing data in eimd_data-only.ipynb
• misc/P_miniata-protein-comparison.ipynb - secondary analysis to better understand the relationship of contigs that have similar annotation.
• misc/Supplemental_File-01.tab - Copy of supplemental tab delimited file with annotation information for all contigs including annotations (protein and GO), differential expression statistics, and enrichment terms. Specific column headers include Contig spID e-value log2FoldChange padj Protein names Enriched GO Terms

---

#Instructions for data-only (interactive viewing) notebook

1. Download the repository zip file to a local directory and uncompress.

2. Launch IPython from the repository primary directory. For example, using Terminal on MacOSX.

$ cd /Desktop/eimd-sswd
$ ipython notebook

This will launch IPython in your web browser.

3. Open notebook by clicking on eimd_data-only.ipynb. This will open a new tab in your browser.

4. Execute code as written or modify to your likely. To execute cell type shift-enter.

---

#Instructions for analysis (interactive execution) notebook

1. Before you get started

To execute the eimd_analysis.ipynb IPython Notebook in its entirety you will need:

• IPython - install instructions
• NBCI Blast - install instructions
• R - install instructions
• rpy2 (interface to R from Python) - install instructions
• SQLShare-pythonclient install instructions

---

In addition you will need a local copy of the UniProt/SwissProt Blast Database. If you do not already have this database you can create it once you install NCBI Blast. Create a blast database first download a fasta file from http://www.uniprot.org/downloads that of Reviewed (Swiss-Prot) then run make blastdb commands. Below is an example code if you wanted to create the database in a subdirectory named blastdb. This will result in files > 300 MB.

$ mkdir blastdb

$ cd blastdb

$ curl -O ftp://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz

$ gunzip uniprot_sprot.fasta.gz

$ makeblastdb -in uniprot_sprot.fasta -dbtype prot -out uniprot_sprot

This will generate a Protein database that you can you to blast sequences.

---

2. Download the repository zip file to a local directory and uncompress.

3. Launch IPython from the repository primary directory. For example, using Terminal on MacOSX.

$ cd /Desktop/eimd-sswd
$ ipython notebook

This will launch IPython in your web browser.

4. Open notebook by clicking on eimd_analysis.ipynb. This will open a new tab in your browser.

5. Modify the cell near the top of the notebook …

#Variables user needs to modify accordingly
db="~/blastdb/uniprot_sprot"
sqls="~/sqlshare-pythonclient/tools/"
usr="user@gmail.com"

db refers to location of blastdb (instructions on bow to create database in step 1).
sqls refers to the location of your sqlshare-pythonclient tools subdirectory (instructions to install in step 1).
usr refers to your SQLshare user name (yep, see step 1 if need be)

6. Execute code as written or modify to your liking. To execute cell type shift-enter. Once variables are set, you should be able to run all cells.

---

We are actively trying to improve this realizing that we are likely missing dependancies, etc. Any suggestions and feedback is welcome.