DEGsEvidences           DEGsEvidences function returns for each DEG a
                        list of evidences that correlate it with the
                        studied disease.
DEGsExtraction          DEGsExtraction performs the analysis to extract
                        the Differentially Expressed Genes (DEGs) among
                        the classes to compare.
DEGsToDiseases          DEGsToDiseases obtains the information about
                        what diseases are related to the DEGs indicated
                        by parameter.
DEGsToPathways          The function uses the DEGs to retrieves the
                        different pathways in which those DEGs involve
                        any interaction.
RNAseqQA                RNAseqQA performs the quality analysis of an
                        expression matrix.
batchEffectRemoval      Corrects the batch effect of the data by using
                        the selected method.
calculateGeneExpressionValues
                        Calculates the gene expression values by using
                        a matrix of counts from RNA-seq.
countsToMatrix          countsToMatrix merges in a matrix the
                        information in the count files.
dataPlot                Plot different graphs depending on the current
                        step of KnowSeq pipeline.
downloadPublicSeries    Download automatically samples from NCBI/GEO
                        and ArrayExpress public databases.
featureSelection        featureSelection function calculates the
                        optimal order of DEGs to achieve the best
                        result in the posterior machine learning
                        process by using mRMR algorithm or Random
                        Forest. Furthermore, the ranking is returned
                        and can be used as input of the parameter
                        vars_selected in the machine learning
                        functions.
fileMove                This function is used to move files to other
                        locations.
gdcClientDownload       This function downloads a list of controlled
                        files from GDC Portal with the user token and
                        the manifest with the information about the
                        desired controlled files.
geneOntologyEnrichment
                        geneOntologyEnrichment obtains the information
                        about what Gene Ontology terms are related to
                        the DEGs.
getGenesAnnotation      getGenesAnnotation returns the required
                        information about a list of genes from Ensembl
                        biomart.
hisatAlignment          hisatAlignment allows downloading and
                        processing the fastq samples in a CSV file by
                        using hisat2 aligner.
knn_test                knn_test allows assessing the final DEGs
                        through a machine learning step by using k-NN
                        with a test dataset.
knn_trn                 knn_trn allows assessing the final DEGs through
                        a machine learning step by using k-NN in a
                        cross validation process.
knowseqReport           knowseqReport creates a report for a given set
                        of genes which their label.
plotConfMatrix          plotConfMatrix plots a confusion matrix with
                        some statistics.
rawAlignment            rawAlignment allows downloading and processing
                        the fastq samples in a CSV file.
rf_test                 rf_test allows assessing the final DEGs through
                        a machine learning step by using Random Forest
                        with a test dataset.
rf_trn                  rf_trn allows assessing the final DEGs through
                        a machine learning step by using Random Forest
                        in a cross validation process.
sraToFastq              sraToFastq downloads and converts the sra files
                        to fastq files. The function admits both gz and
                        sra formats.
svm_test                svm_test allows assessing the final DEGs
                        through a machine learning step by using SVM
                        with a test dataset.
svm_trn                 svm_trn allows assessing the final DEGs through
                        a machine learning step by using svm in a cross
                        validation process.
