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CONDOP (version 1.0)

Condition-Dependent Operon Predictions

Description

An implementation of the computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes proposed by Fortino et al. (2014) . It uses RNA-seq transcriptome profiles to improve prokaryotic operon map inference.

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Version

Install

install.packages('CONDOP')

Monthly Downloads

3

Version

1.0

License

GPL-3

Maintainer

Vittorio Fortino

Last Published

February 24th, 2016

Functions in CONDOP (1.0)

pred.operon.status

Predict operon status of gene pairs (e.g., POPs, DOPs,...).
read.annot.from.gff

Read a GFF file from NCBI and return a GRanges object.
comp.igr.transc.levels

Compile the transcription levels for the intergenic regions.
tune.cls

Tune and build the classification models.
join.genes.and.operons

Join gene(s) and operon(s) annotations.
ct1

Coverage Vector 1
get.NCBI.seq

Find and get a genome sequence by specifyng the accession number. Read gene annotations in GFF format
get.operon.start.points

Determine operon start-points (OSPs).
get.operon.end.points

Determine operon end-points (OEPs).
comp.gene.transc.levels

Compile the transcription levels for the coding regions.
read.gff.annotations

Read gene annotations in GFF format
run.CONDOP

Build condition-dependent operon maps.
select.pops

Define a set of gene pairs POPs with an "operon status" to (re)define represent used to train the operon classifier.
qcut

Determine cutoff values for a given RNA-seq expression profile.
read.door.annotations

Read the operon(s) data file downloaded from http://csbl.bmb.uga.edu/DOOR/displayspecies.php
get.info

Get generic info about the door operons that have been confirmed by using the ensemble operon classifier.
compile.confirmed.operons

Compile a set of coinfirmed operons.
CONDOP-package

Develop ensemble classifiers for condition-dependent operon predictions.
select.nops

Define a set of NOPs which is used to train the operon classifier.
pre.proc

Prepare data inputs for the main function run.CONDOP().
test.corr

Statistical test to find a putative transcription start (or end) point.
remove.cov.depth.from.aFeat

Remove the read coverage on a given feature (e.g. rRNA and tRNA).
pre.processing

Normalize the data before the classification step.
select.ops

Define a set of OPs which is used to train the operon classifier.
sum.conf.matrix

Provide classification metrics.
select.ops.indoor

Define the set of OPs annotated in DOOR.
validate.cls

Validate the classification models.
get.intergenic.regions

Build a data table containing generic information on intergenic regions.
detect.sid.points

Find strat/end transcription points.
train.RFs

Train and validate the operon classifier and evaluate the feature importance.
getCondOperonMap

Build the condition-dependent operon map for a given RNA-seq expression profile.