CONDOP: Condition-Dependent Operon Predictions

An implementation of the computational strategy for the comprehensive analysis of condition-dependent operon maps in prokaryotes proposed by Fortino et al. (2014) <DOI:10.1186/1471-2105-15-145>. It uses RNA-seq transcriptome profiles to improve prokaryotic operon map inference.

AuthorVittorio Fortino <vittorio.fortino@ttl.fi>
Date of publication2016-02-24 15:47:51
MaintainerVittorio Fortino <vittorio.fortino@ttl.fi>
LicenseGPL-3
Version1.0

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Man pages

comp.gene.transc.levels: Compile the transcription levels for the coding regions.

comp.igr.transc.levels: Compile the transcription levels for the intergenic regions.

compile.confirmed.operons: Compile a set of coinfirmed operons.

CONDOP-package: Develop ensemble classifiers for condition-dependent operon...

ct1: Coverage Vector 1

detect.sid.points: Find strat/end transcription points.

getCondOperonMap: Build the condition-dependent operon map for a given RNA-seq...

get.info: Get generic info about the door operons that have been...

get.intergenic.regions: Build a data table containing generic information on...

get.NCBI.seq: Find and get a genome sequence by specifyng the accession...

get.operon.end.points: Determine operon end-points (OEPs).

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

join.genes.and.operons: Join gene(s) and operon(s) annotations.

pred.operon.status: Predict operon status of gene pairs (e.g., POPs, DOPs,...).

pre.proc: Prepare data inputs for the main function 'run.CONDOP()'.

pre.processing: Normalize the data before the classification step.

qcut: Determine cutoff values for a given RNA-seq expression...

read.annot.from.gff: Read a GFF file from NCBI and return a GRanges object.

read.door.annotations: Read the operon(s) data file downloaded from...

read.gff.annotations: Read gene annotations in GFF format

remove.cov.depth.from.aFeat: Remove the read coverage on a given feature (e.g. rRNA and...

run.CONDOP: Build condition-dependent operon maps.

select.nops: Define a set of NOPs which is used to train the operon...

select.ops: Define a set of OPs which is used to train the operon...

select.ops.indoor: Define the set of OPs annotated in DOOR.

select.pops: Define a set of gene pairs POPs with an "operon status" to...

sum.conf.matrix: Provide classification metrics.

test.corr: Statistical test to find a putative transcription start (or...

train.RFs: Train and validate the operon classifier and evaluate the...

tune.cls: Tune and build the classification models.

validate.cls: Validate the classification models.

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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