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DaPars2: Dynamitic analysis of Alternative PolyAdenylation from RNA-seq Using Multiple Samples
============================================






Introduction
================================
The dynamic usage of the 3’untranslated region (3’UTR) resulting from alternative polyadenylation (APA) is emerging as a pervasive mechanism for regulating mRNA diversity, stability and translation. Though RNA-seq provides the whole-transcriptome information and a lot of tools for analyzing gene/isoform expression are available, very few tool focus on the analysis of 3’UTR from standard RNA-seq. DaPars2 is the next generation of DaPars that directly infers the dynamic alternative polyadenylation (APA) usage by comparing standard RNA-seq from multiple samples. Given the annotated gene model, DaPars2 can infer the de novo proximal APA sites as well as the long and short 3’UTR expression levels. Finally, the dynamic APA usages of each samples will be identified.


Installation
===================================

Prerequisite: `python2.7 <http://www.python.org/getit/releases/2.7/>`_;  `numpy <http://numpy.scipy.org/>`_; `scipy <http://www.scipy.org/>`_; `R <http://www.r-project.org/>`_
 

Install DaPars::
 
 tar zxf DaPars2-VERSION.tar.gz
  
 cd DaPars2-VERSION


Input format
=============================

DaPars requires the following two file formats as input:

* `BED <http://genome.ucsc.edu/FAQ/FAQformat.html#format1>`_ file is tab separated, 12 column, plain text file to represent gene model. The gene model can be downloaded from `UCSC <http://genome.ucsc.edu/cgi-bin/hgTables?command=start>`_. 
* `Wiggle <http://genome.ucsc.edu/goldenPath/help/wiggle.html>`_ files store the reads alignment result, which can be generated from BAM file from RNA-seq alignment tool such as TopHat or STAR.

Usage Information
================================
Step 1: Generate region annotation: DaPars_Extract_Anno.py
-------------------------------
DaPars2 will use the extracted distal polyadenylation sites to infer the proximal polyadenylation sites based on the alignment wiggle files of all samples. The output in this step will be used by step 3.

Options:
  -h, --help            show this help message and exit
  -b GENE_BED_FILE, --bed=GENE_BED_FILE
                        The gene model in BED format. The BED file can be downloaded from `UCSC <http://genome.ucsc.edu/cgi-bin/hgTables?command=start>`_ 
  -s Gene_Symbol_FILE, --gene_symbol_map=Gene_Symbol_FILE
			The mapping of transcripts to gene symbol.
  -o OUTPUT_FILE, --out-prefix=OUTPUT_FILE
                        The extracted annotation region will be stored into this file.

Step 2: Generate Sequencing Depth file for all Samples
-------------------------------
DaPars2 will use sequencing depth of each samples to normalize library sizes. The output in this step will be used by step 3.

The format of the sequencing depth file is:

.. image:: images/Result_example.jpg
   :height: 170 px
   :width: 500 px



Step 3: Run DaPars2: DaPars2_main.py
-------------------------------
Dapars2 uses multiple threads and analyzes each chromosome separately to save time and memory.

Run the following commands to perform DaPar2 analysis:

python Dapars2_main.py Dapars2_configure_file current_processing_chrmosome

The configure file contains most of the parameters for DaPars2_main.py.

The format of the configure is:

#The following file is the result of step 1.

Annotated_3UTR=hg19_refseq_extracted_3UTR.bed

#A comma-separated list of Wiggle files of all samples

Aligned_Wig_files=wig/STAR_output_SRR1436021_Aligned.sortedByCoord.out.wig,wig/STAR_output_SRR1434228_Aligned.sortedByCoord.out.wig,
wig/STAR_output_SRR1365013_Aligned.sortedByCoord.out.wig,wig/STAR_output_SRR1360056_Aligned.sortedByCoord.out.wig,
wig/STAR_output_SRR1308860_Aligned.sortedByCoord.out.wig,wig/STAR_output_SRR1399113_Aligned.sortedByCoord.out.wig,
wig/STAR_output_SRR1353418_Aligned.sortedByCoord.out.wig,wig/STAR_output_SRR1349809_Aligned.sortedByCoord.out.wig,
wig/STAR_output_SRR1312002_Aligned.sortedByCoord.out.wig,wig/STAR_output_SRR1310939_Aligned.sortedByCoord.out.wig

Output_directory=DaPars_Test_data/

Output_result_file=DaPars_Test_data

# Specify the Coverage_threshold

Coverage_threshold=10

# Specify the number of threads used to process the data

Num_Threads = 8

# Provide Sequencing_depth file for normalization

sequencing_depth_file=mapping_bam_location_with_depth.txt 


Output format
-------------------------------

Output format:

.. image:: images/Result_example.jpg
   :height: 70 px
   :width: 1400 px



Release history
===================
DaPars2

* DaPars2 is released.


Contact
================================
* Lei Li: lei.li@bcm.edu
* Wei Li: wl1@bcm.edu