replaced Readme.txt with README.md

README.md

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+#SURPI-v1.0.7 (April 2014)
+
+**Note**: For the most up to date version of the SURPI source code, go to this website: [http://chiulab.ucsf.edu/surpi](http://chiulab.ucsf.edu/surpi "surpi").
+
+SURPI has been tested on Ubuntu 12.04. It will likely function properly on other Linux distributions, but this has not been tested.
+
+###Hardware Requirements:
+
+SURPI requires a machine with high RAM in order to run efficiently. This is mainly due to SNAP, which gains its speed by loading the reference databases completely into RAM. We’ve run SURPI successfully on machines with **60.5 GB** RAM. SURPI will use all cores on a machine by default, though the number of cores used can be adjusted within the config file. Much of SURPI is parallelized, so it benefits from using as many cores as possible.
+
+
+###Installation:
+
+
+#####Install all software dependencies
+
+* [fastQValidator](http://genome.sph.umich.edu/wiki/FastQValidator)
+* [Minimo (v1.6)](http://sourceforge.net/projects/amos/files/amos/3.1.0/)
+* [Abyss (v1.3.5)](http://www.bcgsc.ca/platform/bioinfo/software/abyss)
+* [RAPSearch (v2.12)](http://omics.informatics.indiana.edu/mg/RAPSearch2/)
+* [seqtk (v 1.0r31)](https://github.com/lh3/seqtk)
+* [SNAP (v0.15)](http://snap.cs.berkeley.edu)
+* [gt (v1.5.1)](http://genometools.org/index.html)
+* [fastq](https://github.com/brentp/bio-playground/tree/master/reads-utils)
+* [fqextract](https://gist.github.com/drio/1168330)
+* [cutadapt (v1.2.1)](https://code.google.com/p/cutadapt/)
+* [prinseq-lite.pl](http://prinseq.sourceforge.net)
+* [dropcache](http://stackoverflow.com/questions/13646925/allowing-a-non-root-user-to-drop-cache)
+
+#####Decompress SURPI package
+
+Decompress SURPI and place all files into a directory included in your $PATH. Something like the following should work:
+
+	tar xvfz SURPI.tar.gz
+
+#####Create the databases
+
+1. SNAP Databases:
+
+    * Human DB
+    * NCBI nr DB (Comprehensive Mode)
+    * Viral protein DB (Comprehensive Mode)
+    * NCBI nt DB (Comprehensive Mode)
+    * Viral nt DB (Fast Mode)
+    * Bacterial DB (Fast Mode)
+
+2. Taxonomy Databases (generated with `create_taxonomy_db.sh`)
+    * gi_taxid_prot.db
+    * gi_taxid_nucl.db
+    * names_nodes_scientific.db
+
+#####Customize certain SURPI files
+
+Below are some notes on files that may need to be modified to run
+SURPI:
+
+* `cutadapt_quality.csh`: specify location of /tmp folder
+
+    cutadapt_quality.csh defaults to using /tmp for temporary file
+    storage. If using a system with limited space in this location,
+    change the location to a directory with more storage space
+    available.
+
+* `taxonomy_lookup_embedded.pl`
+
+    Set database_directory to the location of the taxonomy
+    databases created below.
+
+* `tweet.pl`
+
+    SURPI has the ability to send out notifications via Twitter
+    at various stages within the pipeline. If this feature is
+    desired, you will need to set up a Twitter application within
+    your account for this purpose. See
+    [https://dev.twitter.com/apps](https://dev.twitter.com/apps)
+    for more details.
+
+    Once an application has been set up, fill in the below parameters
+    to the `tweet.pl` program.
+
+    * consumer_key
+    * consumer_secret
+    * oauth_token
+    * oauth_token_secret
+
+* perl modules to install
+
+    * Net::Twitter::Lite::WithAPIv1_1
+    * Net::OAuth
+
+#####Run SURPI
+
+
+To run SURPI, execute the following in a directory containing
+your FASTQ input file.
+
+1. This command will create the necessary config file to run SURPI:
+
+        SURPI.sh -z <INPUTFILE>
+
+    After typing the above line, a config file and a “go” file will
+    be created. The config file will contain default values for many
+    parameters - these parameters may need to be modified depending
+    on your environment. The config file has descriptions of the
+    options allowed by SURPI.
+
+2. Once the config file has been customized, the SURPI pipeline
+can be initiated by typing in the name of the go file that was
+created. Below is an example (boldfaced text is inputted by the
+user):
+
+	    sfederman@tribble:/data/inputfile/test$ ls -laF
+	    total 750212
+	    drwxrwxr-x  2 sfederman sfederman      4096 Jan 20 16:45 ./
+	    drwxrwxr-x 11 sfederman sfederman     61440 Jan 20 16:45 ../
+	    -rw-rw-r--  1 sfederman sfederman 768143660 Jan 20 16:45 inputfile.fastq
+
+        sfederman@tribble:/data/inputfile/test$ SURPI.sh -z inputfile.fastq
+        inputfile.config generated. Please edit it to contain the proper parameters for your analysis. go_ inputfile generated. Initiate the pipeline by running this program. (./go_inputfile)
+
+	    sfederman@tribble:/data/inputfile/test$ ls -laF
+	    total 750220
+	    drwxrwxr-x  2 sfederman sfederman      4096 Jan 20 16:47 ./
+	    drwxrwxr-x 11 sfederman sfederman     61440 Jan 20 16:45 ../
+	    -rw-rw-r--  1 sfederman sfederman      1976 Jan 20 16:47 inputfile.config
+	    -rw-rw-r--  1 sfederman sfederman 768143660 Jan 20 16:45 inputfile.fastq
+	    -rwxrwxr-x  1 sfederman sfederman        84 Jan 20 16:47 go_inputfile*
+
+	    sfederman@tribble:/data/inputfile/test$ ./go_inputfile &
+
+	    Progression of the pipeline can be followed by monitoringthe log file (titled inputfile.SURPI.log, in the above example). We have also find it useful to monitor the status of the pipeline with the program htop.
+

compare_multiple_sam.py

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-#!/usr/bin/python
+#!/usr/bin/env python
 #
 #	compare_multiple_sam.py
 #

compare_sam.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/env python
 #
 #	compare_sam.py
 #

coveragePlot.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/env python
 #
 #	coveragePlot.py
 #

create_taxonomy_db.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/env python
 #
 #	create_taxonomy_db.py
 #

mapPerfectBLASTtoGenome.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/env python
 #
 # Simple script to iterate over the -m 8 results from a
 # BLAST and spits out the number of hits at each base of the

update_sam.py

@@ -1,4 +1,4 @@
-#!/usr/bin/python
+#!/usr/bin/env python
 #
 #	update_sam.py
 #       this script reannotates the SAM file based on the better hit identified in "compare_sam.py"