Metadata-Version: 1.1
Name: EMIRGE
Version: 0.6.2a5
Summary: EMIRGE reconstructs full length sequences from short sequencing reads
Home-page: https://github.com/csmiller/EMIRGE
Author: Christopher Miller
Author-email: christopher.s.miller@ucdenver.edu
License: GPLv3+
Description: 
            EMIRGE: Expectation-Maximization Iterative Reconstruction of Genes
                    from the Environment
        
            EMIRGE reconstructs full length ribosomal genes from short read
            sequencing data.  In the process, it also provides estimates of the
            sequences' abundances.
        
            EMIRGE uses a modification of the EM algorithm to iterate between
            estimating the expected value of the abundance of all SSU sequences
            present in a sample and estimating the probabilities for each read
            that a specific sequence generated that read.  At the end of each
            iteration, those probabilities are used to re-calculate (correct) a
            consensus sequence for each reference SSU sequence, and the mapping is
            repeated, followed by the estimations of probabilities.  The
            iterations should usually stop when the reference sequences no longer
            change from one iteration to the next.  Practically, 40-80 iterations is
            usually sufficient for many samples.  Right now EMIRGE uses Bowtie
            alignments internally, though in theory a different mapper could be
            used.
        
            EMIRGE was designed for Illumina reads in FASTQ format, from pipeline
            version >= 1.3
        
            
Keywords: rRNA,EM
Platform: UNKNOWN
Classifier: Development Status :: 4 - Beta
Classifier: Environment :: Console
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: GNU General Public License v3 or later (GPLv3+)
Classifier: Operating System :: POSIX
Classifier: Programming Language :: Cython
Classifier: Programming Language :: Python :: 2.7
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
