Metadata-Version: 1.0
Name: riptide
Version: 1.7.2
Summary: Reaction Inclusion by Parsimony and Transcript Distribution (RIPTiDe)
Home-page: https://github.com/mjenior/riptide
Author: Matthew Jenior
Author-email: mattjenior@gmail.com
License: MIT
Description: RIPTiDe
        =======
        
        **R**eaction **I**nclusion by **P**arsimony and **T**ranscript **D**istribution
        
        Transcriptomic analyses of bacteria have become instrumental to our understanding of their responses to changes in their environment. While traditional analyses have been informative, leveraging these datasets within genome-scale metabolic network reconstructions can provide greatly improved context for shifts in pathway utilization and downstream/upstream ramifications for changes in metabolic regulation. Previous techniques for transcript integration have focused on creating maximum consensus with the input datasets. However, these approaches have collectively performed poorly for metabolic predictions even compared to transcript-agnostic approaches of flux minimization that identifies the most efficient patterns of metabolism given certain growth constraints. Our new method, RIPTiDe, combines these concepts and utilizes overall minimization of flux in conjunction with transcriptomic analysis to identify the most energy efficient pathways to achieve growth that include more highly transcribed enzymes. RIPTiDe requires a low level of manual intervention which leads to reduced bias in predictions. 
        
        
        Please cite when using::
        
            Jenior ML, Moutinho TJ, and Papin JA. (2019). Parsimonious transcript data integration improves context-specific predictions of bacterial metabolism in complex environments. BioRxiv.
        
        
        Installation
        ------------
        
        Installation is simply::
        
            pip install riptide
        
        .. 
        
        Other dependencies include both cobrapy and symengine which are automatically installed. 
        Cobrapy should be >=version 0.13
        
        .. _riptide: https://github.com/mjenior/riptide
        
        
        
        Example Use
        -----------
        
        The base use case of RIPTiDe is as follows:
        
        .. code-block:: python
        
            from riptide import *
        
            my_model = cobra.io.read_sbml_model('examples/genre.sbml')
        
            transcript_abundances_1 = read_transcription_file('examples/transcriptome1.tsv')
            transcript_abundances_2 = read_transcription_file('examples/transcriptome2.tsv')
        
            riptide_object_1 = riptide(my_model, transcript_abundances_1)
            riptide_object_2 = riptide(my_model, transcript_abundances_2)
        .. 
        
        Additional parameters for main RIPTiDe functions:
        
        **read_transcription_file()**::
        
            read_abundances_file : string
                User-provided file name which contains gene IDs and associated transcription values
            header : boolean
                Defines if read abundance file has a header that needs to be ignored
                default is no header
            replicates : boolean
                Defines if read abundances contains replicates and medians require calculation
                default is no replicates
            sep: string
                Defines what character separates entries on each line
                defaults to tab (.tsv)
        ..
        
        **riptide()**::
        
            model : cobra.Model
                The model to be contextualized
            transcription : dictionary
                Dictionary of transcript abundances, output of read_transcription_file()
            defined : False or File
                Text file containing reactions IDs for forced inclusion listed on the first line and exclusion 
                listed on the second line (both .csv and .tsv formats supported)
            samples : int 
                Number of flux samples to collect, default is 10000, If 0, sampling skipped
            percentiles : list of floats
                Percentile cutoffs of transcript abundance for linear coefficient assignments to associated reactions
                Default is [50.0, 62.5, 75.0, 87.5]
            coefficients : list of floats
                Linear coefficients to weight reactions based on distribution placement
                Default is [1.0, 0.5, 0.1, 0.01, 0.001]
            fraction : float
                Minimum percent of optimal objective value during FBA steps
                Default is 0.8
            conservative : bool
                Conservatively remove inactive reactions based on genes
                Default is False
            bound : bool
                Bounds each reaction based on transcriptomic constraints
                Default is False
        ..
        
        The resulting RIPTiDe object properties::
        
            model = contextualized genome-scale metabolic network reconstruction
            fluxes = Flux sampling or flux variability analysis pandas object
            quantile_range = percentile intervals by which to parse transcript abundance distribution
            linear_coefficient_range = linear coeeficients assigned to corresponding quantile
            fraction_of_optimum = minimum percentage of optimal allowable flux through the objective during contextualization
        
        .. 
        
        Thank you for your interest in RIPTiDe, for additional questions please email mljenior@virginia.edu.
        
        
Platform: UNKNOWN
