Metadata-Version: 1.0
Name: TEToolkit
Version: 1.2.1f
Summary: Tools for estimating differential enrichment of Transposable Elements or other highly repetetive regions
Home-page: http://www.example.org
Author: Ying Jin, Oliver Tam
Author-email: yjin@cshl.edu
License: MIT
Description: TEToolkit
        =========
        
        Created by Ying Jin, Eric Paniagua & Oliver Tam, February 2014
        
        Copyright (C) 2014 Ying Jin, Eric Paniagua & Oliver Tam
        Contact: Ying Jin (yjin@cshl.edu)
        
        
        Summary
        -------
        
            TEToolkit is composed of two tools, TEpeaks and TEtranscripts, each described in
            its own section below.
        
        NOTE! Both programs rely on specially curated GTF files, which are not
        packaged with this software due to their size. Please check back for an
        update to this package's homepage. Once it is up and running, the required
        GTFs will be downloadable from there.
        
            TEpeak takes ChIP-seq (and similar data) alignment files (BAM or BED),
            identiifes narrow peaks, and is also able to do differential analysis over
            peaks of two sets of libraries. It is an extension of MACS by adding the
            funcionality of taking into account multi-reads, another normalization
            method, bin correlation, and differential analysis. The differential
            analysis is performed using DESeq. 
        
            TEtranscripts takes RNA-seq (and similar data) and annotates reads to both
            genes & transposable elements. It then performs differential analysis using
            DESeq.
        
        
        Requirements
        ------------
        
            Python:     2.6.x or 2.7.x (not tested in Python 3.x)
            Samtools    (tested using version 0.1.19)
            HTSeq       (tested using version 0.5.4p3)
            R:          2.15.x or greater
            DESeq:      1.5.x or greater
        
        
        Copying & distribution
        ----------------------
        
            TEtranscripts and TEpeaks are part of TEToolKit.
        
            TEToolKit is free software: you can redistribute it and/or modify
            it under the terms of the GNU General Public License as published by
            the Free Software Foundation, either version 3 of the License, or
            (at your option) any later version.
        
            This program is distributed in the hope that it will be useful,
            but WITHOUT ANY WARRANTY; without even the implied warranty of
            MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
            GNU General Public License for more details.
        
            You should have received a copy of the GNU General Public License
            along with TEToolKit.  If not, see <http://www.gnu.org/licenses/>.
        
        
        ================================
        TEpeaks
        ================================
        
        Usage
        -----
        usage: TEpeaks -t treatment sample [treatment sample ...] 
                            -c control sample [control sample ...]
                            --tinput treatment input
                            --cinput control input
                            -s genome  
                            [optional arguments]
        
        Required arguments:
          -t | --treatment [treatment sample 1 treatment sample 2...]
             Sample files in group 1 (e.g. treatment/mutant), separated by space
             Sample files in group 2 (e.g. control/wildtype), separated by space
          --tinput    treatment input 
          -s genome  (hg: human19, mm: mouse9, dm: dm3)
        
        Optional arguments:
          -c | --control [control sample 1 control sample 2 ...]
          --cinput  control input
          --format [input file format]
             Input file format: BAM or BED. DEFAULT: BAM
          --project [name]      Name of this project. DEFAULT: TEpeak_out
          -p | --padj [pvalue]
             FDR cutoff for significance. DEFAULT: 1e-5
          -n | --norm [normalization]
             Normalization method : sd (library size),
                                    bc (bin correlation). DEFAULT: sd
          -r | --step           step size. DEFAULT: 100
          -a | --auto           auto detect shiftsize. DEFAULT: False
          -d | --diff           require differential analysis
          -g | --gap            maximum allowed gap. DEFAULT: 1000
          -f | --fragsize       fragment size. DEFAULT: 200
          --lmfold              lower bound of fold change for modeling shipsize.
                                DEFAULT: 10
          --umfold              upper bound of fold change for modeling shiftsize.
                                DEFAULT: 30
          --minread             minimal reads of a peak. DEFAULT: 5
          --mode                TE counting mode. 'uniq' consider uniq-reads only. 'multi' distribute to all alignments. DEFAULT: multi
          --wig                 generate wiggle file for peaks (normalize to
                                    10 million reads in total(library size))
          -h | --help           help info
        
        
        Example Command Lines
        ---------------------
        
        TEpeaks --format BAM -t S1.bam --tinput S1input.bam -s mm -n sd --mode multi
        
        TEpeaks --format BAM -t S1.bam S2.bam -c C1.bam C2.bam  --tinput S1input.bam  --cinput C1input.bam -s mm -n sd --diff --mode multi
        
        
        
        ================================
        TEtranscripts
        ================================
        
        Usage
        -----
        usage: TEtranscript -t treatment sample [treatment sample ...] 
                            -c control sample [control sample ...]
                            --GTF genic-GTF-file
                            --TE TE-GTF-file 
                            [optional arguments]
        
        Required arguments:
          -t | --treatment [treatment sample 1 treatment sample 2...]
             Sample files in group 1 (e.g. treatment/mutant), separated by space
          -c | --control [control sample 1 control sample 2 ...]
             Sample files in group 2 (e.g. control/wildtype), separated by space
          --GTF genic-GTF-file  GTF file for gene annotations
          --TE TE-GTF-file      GTF file for transposable element annotations
        
        Optional arguments:
          --format [input file format]
             Input file format: BAM or SAM. DEFAULT: BAM
          --stranded [option]   Is this a stranded library? (yes, no, or reverse).
                                DEFAULT: yes.
          --mode [TE counting mode]
             How to count TE:
                uniq        (unique mappers only)
                sameFam     (group TE by family)
                sameInst    (assign to dominant TE) 
                multi       (distribute among all alignments).
             DEFAULT: uniq
          --project [name]      Name of this project. DEFAULT: TEtranscript_out
          -p | --padj [pvalue]
             FDR cutoff for significance. DEFAULT: 0.05
          -f | --foldchange [foldchange]
             Fold-change ratio (absolute) cutoff for differential expression. 
             DEFAULT: 1
          -n | --norm [normalization]
             Normalization method : rpm (reads per million mapped),
                                    quant (quantile normalization). DEFAULT: rpm
          --no-sort             Input file is not sorted by chromosome position.
          -i | --iteration 
             maximum number of iterations used to optimize multi-reads assignment. DEFAULT: 0
        
        
        Example Command Lines
        ---------------------
        
        TEtranscripts --format BAM --mode uniq -t RNAseq1.bam RNAseq2.bam -c CtlRNAseq1.bam CtlRNAseq.bam
        
        TEtranscripts -t sample1.bam -c sample2.bam --format BAM --GTF sample_refgene.gtf --TE sample_rmsk.gtf --norm rpm --mode sameFam --project sample_test_rpm
        
Keywords: TE transposable element differential enrichment
Platform: UNKNOWN
