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MEET (version 5.1.1)

MEET: Motif Elements Estimation Toolkit

Description

MEET (Motif Elements Estimation Toolkit) is a R-package that integrates a set of computational algorithms for the detection of Transcription Factor Binding Sites (TFBS).

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Version

Install

install.packages('MEET')

Monthly Downloads

19

Version

5.1.1

License

GPL (>= 2)

Maintainer

Joan Maynou

Last Published

February 22nd, 2013

Functions in MEET (5.1.1)

detector_1rOrdre_diff

Detection of Transcription Factor Binding Sites Through Differential Renyi Entropy
writeMEME

Write a training matrix in a MEME/MAST format
Prob

Probabilities of each nucleotide in the Homo sapiens organism according to Thakurta et al.
CalculSimilarity

Similarity Score between a Sequence and a PSSM model
readMEME

Read MEME motifs and consensus sequences
CalculPWM

CalculPWM: To calculate Position Weight Matrix
EntropyRATTUS

EntropyRATTUS: Given a Transcription factor chooses the model for a specific organism and method.
DivergenceMUS

DivergenceMUS: Given a Transcription factor chooses the model for a specific organism and method.
iicc

A set of initial conditions
standardout

Standard output detector
scoreMDscan

Output MDscan method
joint.probability

Joint Probability
CalculRedundancy

CalculRedundancy: To calculate the redundancy
Hmemory

Library of entropy values
ModelMATCH

Match algorithm to detect TFBS in a sequence
ModelDivergence

To create Model Divergence
MImemory

Library of PredictDivergence values
run.read.MDscan

Run and read MDscan on validation
PredictMATCH

MATCH algorithm to detect TFBS in a sequence
PredictMEME

MEME algorithm to detect TFBS in a sequence
EntropyMUS

EntropyMUS: Given a Transcription factor chooses the model for a specific organism and method.
PredictPCA

Q-residuals detection of TFBS, using a principal components model
TFlogodds

Logodds matrix
DivergenceDROSOPHILA

DivergenceDROSOPHILA: Given a Transcription factor chooses the model for a specific organism and method.
CalculInformation

Information content in each position of a set of aligned DNA sequences
Hread

To read Entropy values
QresidualsMUS

QresidualsMUS: Given a Transcription factor chooses the model for a specific organism and method.
ReadSequence

Convert a DNA sequence in a numerical DNA matrix
align.clustalw

Multiple sequence alignment by means of ClustalW
DivergenceRATTUS

DivergenceRATTUS: Given a Transcription factor chooses the model for a specific organism and method.
Models

To create Detection Model
align.muscle

Multiple sequence alignment by means of Muscle (MUltiple Sequence Comparison by Log-Expectation)
ModelPCA

PCA model for a set of TFBS
Read.aligned

Read nucleotide sequences
correction.entropy

Correction entropy from the Finite Sample Size Effect
entropy.Renyi

Renyi Entropy
kfold.PCA

PCA
Sequence

A sequence with binding evidence.
Model-class

A set of Models for the detection
kfold.MATCH

MATCH validation process
ModelEntropy

To create Model Entropy
probability.couple

Background joint probability
QtoJackson

Q to Jackson: transform a Q-residual into a confidence interval
divergence.Shannon

Divergencia.Shannon: Mutual Information
EntropyDROSOPHILA

EntropyDROSOPHILA: Given a Transcription factor chooses the model for a specific organism and method.
divergence.Renyi

Renyi divergence
detection

Detection: A set of functions for detection of TFBS
entropy.corrected

Correction of the Finite Sample Size Effect
JacksonParameters

JacksonParameters: To calculates the parameters needed to transform a Q-residual to a confidence interval
q

Renyi Order
ModeltransMEME

To create Model transMEME
classMODEL

classMODEL: To choose the model
numericalDNA

Conversion of nucleotides to numerical vectors
PredictMDscan

MDscan algorithm to detect TFBS in a sequence
EntropyHOMO

EntropyHOMO: Given a Transcription factor chooses the model for a specific organism and method.
ModelMDscan

MDscan algortihm to detect TFBS within a sequence
QresidualsRATTUS

QresidualsRATTUS: Given a Transcription factor chooses the model for a specific organism and method.
organism

Probability for each nucleotide according to different organism
BackgroundOrganism

Probabilities of each nucleotide in the Homo sapiens organism according to Thakurta et al.
detector_2nOrdre_init

Detection of Transcription Factor Binding Sites Through Parametric PredictDivergence
DivergenceHOMO

DivergenceHOMO: Given a Transcription factor chooses the model for a specific organism and method.
correctionaprox

Correction Entropy Approximate from the Finite Sample Size Effect.
PredictDivergence

A set of functions for detection of Transcription Factor Binding Sites by means of Divergence
diffInstructions

The measurement of the variation of the total redundancy
read.mast

Read output mast
ROCmodel

To choose the best paramater for a model
ModelMEME

MEME algortihm to detect TFBS within a sequence
correction.redundancy

Correction redundancy from the Finite Sample Size Effect
entropy.Shannon

Shannon Entropy
kfold.transMEME

Leave-one-out cross-validation for MEME/MAST through training.matrix aligned with MUSCLE or CLUSTALW.
motif.mast

MEME format to training matrix
align.MEME

Multiple sequence alignment by means of MEME.
PredicttransMEME

MAST algorithm to detect TFBS in a sequence
MIread

To read PredictDivergence values
probability

Probability
CreateConsensus

Consensus Sequence for a DNA motif
kfold.MEME

Leave-one-out cross-validation for MEME
correction-class

Correction for finite sample effect
CalculPSSM

Position Specific Scoring Matrices from a set of aligned sequences
PredictEntropy

PredictEntropy: Detection of Transcription Factor Binding Sites by means of Renyi entropy
kfold.MDscan

Leave-one-out cross-validation for MDscan.
CalculScores

Calcul Score of a Sequence, using a loggods matrix
redundancy

To calculate redundancy
QresidualsHOMO

QresidualsHOMO: Given a Transcription factor chooses the model for a specific organism and method.
PCanalysis

PC analysis on numerical DNA sequences
Prediction

To detect Transcription Factor Binding sites by means of a model
Alignment

To line up Transcription Factor Binding sites through Multiple Sequence Alignment (MSA)
ConstructModel

A set of functions for training of motif discovery algorithms.
kfold.Divergence

Leave-one-out cross-validation for parametric divergence (ITEME).
entropy.joint

To calculate joint entropy
QresidualsDROSOPHILA

QresidualsDROSOPHILA: Given a Transcription factor chooses the model for a specific organism and method.
detector_2nOrdre

Detection of Transcription Factor Binding Sites Through Parametric PredictDivergence
TranscriptionFactor

A set of aligned binding sites sequences
writeResultsHTML

Writes the results of a MEET detection to HTML.
MEET

MEET: Motif Elements Estimation Toolkit
pvalue

P value
kfold.Entropy

Leave-one-out cross-validation for Renyi entropy (ITEME)
chooseModel

ChooseModel: Choose the best model