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Reaction Inclusion by Parsimony and Transcript Distribution (RIPTiDe)

Project description

RIPTiDe
=======
Reaction Inclusion by Parsimonious usage and Transcript Distribution


### 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. DOI

### Dependencies
cobrapy (>=version 0.13)

symengine

### Installation:
pip install riptide

### Example usage:
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)


read_transcription_file() parameters
----------
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() parameters
----------
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

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