Final paper supplementary version

README.md

@@ -13,6 +13,7 @@ All scripts from this package can be found in src/pgmpy, updated from [github](
 * regex 
 * GhostScript
 * BioPython
+* wrapt
 
 ## Software requirements
 
@@ -22,8 +23,12 @@ All scripts from this package can be found in src/pgmpy, updated from [github](
 
 # Installation
 
+All the code and files required for the downloadable version of the software can be found in the git repository : http://jwgitlab.cs.mcgill.ca/sarrazin/rnabayespairing.git
+
+We also have a webserver on which you can annotate sequences for module signal with our two main datasets: http://bayespairing.cs.mcgill.ca/
+
 * Clone the git repository and execute the following commands:
-* cd bayespairing
+* cd rnabayespairing
 * pip install .
 
 This will install the dependencies and allow you to use some of the scripts outside of the directory.
@@ -34,6 +39,9 @@ Three python scripts found in `/src` can be used to run `BayesPairing`.
 
 # Predicting module likelihood from sequence
 
+We provide a basic overview of the main functions of the software with the following examples, which use dummy sequences. For biologically relevant applications, please consult the python notebooks in the *test* directory
+
+
 The main script for predicting the likelihood of a module in an input sequence is `parse_sequences.py`.
 
 For manual:
@@ -62,9 +70,9 @@ The following arguments can be used to call it. only -seq is required.
   -m M                number of folded candidates, must be larger than n
   -n N                number of outputted candidates
   -seq SEQ            sequences to parse, FASTA file
-  -ss SS              facultative secondary structures, FASTA file
+  -ss SS              facultative secondary structures in the commandline as a string. If your input comes within a fasta file, write "infile"
   -d D                Dataset, as a pickle. Default will be the dataset
-                      presented in the paper
+                      presented in the paper, rna3dmotif.
   -mod MOD [MOD ...]  If you only want to parse specific modules, list them.
                       ex -mod 1 4 12
   -p P                Number of times the Bayes Net should be sampled
@@ -72,8 +80,9 @@ The following arguments can be used to call it. only -seq is required.
                       Default:25
   -w W                Window Length [50 to 300]. Default:200
   -s S                Step size between windows [10 to 200]. Default:100
-  -k K                weight of the secondary structure analysis [0.8 to 2].
+  -sw SW              weight of the secondary structure analysis [0.8 to 2].
                       Default:1
+  -o O                The name of the output pickle file.
 ```
 
 To test `parse_sequences.py`, you can try the following command, which will run 4 modules from the default dataset on two sequences in the example fasta file :