man/*.Rd: update doc

man/build_count_matrices.Rd

@@ -5,28 +5,34 @@
 \title{Build matrices}
 \usage{
 build_count_matrices(
-  design,
+  design_table,
   path,
-  formula,
-  filter_file,
+  my_formula,
+  filter_list,
   min_expression,
   output_folder
 )
 }
 \arguments{
-\item{design}{A design file with the column count_files, sample and condition}
+\item{design_table}{A dataframe with the column count_files, sample and
+condition. Other columns corresponding to cofactors can be present}
 
 \item{path}{The path were the count file are stored}
 
-\item{formula}{The formula to use in DESeq2}
+\item{my_formula}{The formula to use in DESeq2}
 
-\item{filter_file}{A file containing genes}
+\item{filter_list}{A vector containing the list of genes to keep in the
+analysis. To keep all gene use a NULL object}
 
 \item{min_expression}{The minimum average required expression across
 all samples to keep the gene}
 
 \item{output_folder}{Folder were the matrices will be produced}
 }
+\value{
+The dds object corresponding to a DESeqDatase object obtained after
+running the DESeq function.
+}
 \description{
 Build matrices
 }

man/cli_run_deseq2.Rd

@@ -16,6 +16,6 @@ perform a complete DESeq2 analysis including:
 \item Sample loading
 \item Normalisation
 \item Figure creation
-\item Differential expression analysis for the hcosen contrasts
+\item Differential expression analysis for the chosen contrasts
 }
 }

man/de_analysis.Rd

@@ -23,8 +23,17 @@ de_analysis(dds, my_contrast, output_folder, basemean_threshold, lfc_threshold)
 \item{basemean_threshold:}{The minimum basemean of gene to be knameept}
 }
 \value{
-A dataframe indicating The number of differentially expressed genes
-and the number of up and down regulated genes
+A list containing:
+\enumerate{
+\item at \code{data} key: A dataframe indicating The number of differentially
+expressed genes and the number of up and down regulated genes
+\item at \code{dds} key: The dds object corresponding to a DESeqDatase object
+obtained after running the DESeq function.
+\item at \code{results} key: A dataframe containing the results of DEseQ2 analysis
+but for all gene
+\item at \code{de_results} key: A dataframe containing only differentially expressed
+genes
+}
 }
 \description{
 Perform a DESeq2 analysis with a given contrast

man/de_analyzes.Rd

@@ -13,14 +13,31 @@ de_analyzes(
 )
 }
 \arguments{
+\item{dds}{The dds object corresponding to a DESeqDatase object obtained
+after running the DESeq function.}
+
+\item{my_contrasts}{A list containing contrast vectors}
+
 \item{output_folder}{Folder where the result table will be created}
 
 \item{lfc_threshold}{The minimum fold change to consider a gene significant}
 
-\item{my_contrast}{A list containing contrast vectors}
-
 \item{basemean_threshold:}{The minimum basemean of genes to be kept}
 }
+\value{
+A list containing for each comparison given in my_contrasts
+(keys of the list) a sublist containing:
+\enumerate{
+\item at \code{data} key: A dataframe indicating The number of differentially
+expressed genes and the number of up and down regulated genes
+\item at \code{dds} key: The dds object corresponding to a DESeqDataSet object
+obtained after running the DESeq function.
+\item at \code{results} key: A dataframe containing the results of DEseQ2 analysis
+but for all gene
+\item at \code{de_results} key: A dataframe containing only differentially expressed
+genes
+}
+}
 \description{
 Perform multiple differential expression analysis
 }

man/filter_dds.Rd

@@ -4,19 +4,20 @@
 \alias{filter_dds}
 \title{Filter DESeq2 object on expressed gene if needed}
 \usage{
-filter_dds(dds, filter_file, min_expression, addition_col, formula)
+filter_dds(dds, filter_list, min_expression, addition_col, my_formula)
 }
 \arguments{
 \item{dds}{A dds object}
 
-\item{filter_file}{A file containing genes}
+\item{filter_list}{A vector containing the list of genes to keep in the
+analysis. To keep all gene use a NULL object}
 
 \item{min_expression}{The minimum average required expression across all
 samples to keep the gene}
 
 \item{addition_col}{Additional design columns}
 
-\item{formula}{The formula to use in DESeq2}
+\item{my_formula}{The formula to use in DESeq2}
 }
 \value{
 A DESeqDataset object filtered

man/hline.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/differiential_expression.R
+\name{hline}
+\alias{hline}
+\title{Function to draw a plotly horizontal line}
+\usage{
+hline(y = 0, color = "black")
+}
+\arguments{
+\item{y}{Location of horizontal line}
+
+\item{color}{Color of horizontal line}
+}
+\value{
+a list containing plotly parameters
+}
+\description{
+Function to draw a plotly horizontal line
+}

man/load_matrix.Rd

@@ -4,14 +4,15 @@
 \alias{load_matrix}
 \title{Build the deseq2 count matrix from design file}
 \usage{
-load_matrix(design, path, formula)
+load_matrix(design_table, path, my_formula)
 }
 \arguments{
-\item{design}{A design file with the column count_files, sample and condition}
+\item{design_table}{A dataframe with the column count_files, sample and
+condition. Other columns corresponding to cofactors can be present}
 
 \item{path}{The path were the count file are stored}
 
-\item{formula}{The formula to use in DESeq2}
+\item{my_formula}{The formula to use in DESeq2}
 }
 \value{
 A DESeqDataset object filtered

man/make_html_pca.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plots.R
+\name{make_html_pca}
+\alias{make_html_pca}
+\title{Create plotly PCA plot}
+\usage{
+make_html_pca(pca_data, percent_var, output_folder, columns)
+}
+\arguments{
+\item{pca_data}{Object returned by DESeq2::plotPCA containing PCA table}
+
+\item{percent_var}{Vector containing the percentage of variance
+of PC1 and PC2}
+
+\item{output_folder}{Folder where the figure will be created}
+
+\item{columns}{The design columns}
+}
+\description{
+Create plotly PCA plot
+}

man/make_pca.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/plots.R
+\name{make_pca}
+\alias{make_pca}
+\title{Make ggplot PCA}
+\usage{
+make_pca(pca_data, percent_var, columns, dds)
+}
+\arguments{
+\item{pca_data}{Object returned by DESeq2::plotPCA containing PCA table}
+
+\item{percent_var}{Vector containing the percentage of variance
+of PC1 and PC2}
+
+\item{columns}{A vector containing the columns to display in PCA data}
+
+\item{dds}{a DESeqDataSet object}
+}
+\description{
+Make ggplot PCA
+}

man/run_deseq2.Rd

@@ -5,36 +5,55 @@
 \title{DESeq2 wrapper}
 \usage{
 run_deseq2(
-  design,
+  design_table,
   path,
-  formula,
-  filter_file,
-  min_expression,
-  output_folder,
   my_contrasts,
-  basemean_threshold,
-  lfc_threshold
+  my_formula = "~ condition",
+  filter_list = NULL,
+  min_expression = 2,
+  output_folder = ".",
+  basemean_threshold = 0,
+  lfc_threshold = 0
 )
 }
 \arguments{
-\item{design}{A design file with the column count_files, sample and condition}
+\item{design_table}{A dataframe with the column count_files, sample and
+condition. Other columns corresponding to cofactors can be present}
 
 \item{path}{The path were the count file are stored}
 
-\item{formula}{The formula to use in DESeq2}
+\item{my_formula}{The formula to use in DESeq2 (default '~ condition')}
 
-\item{filter_file}{A file containing genes}
+\item{filter_list}{A vector containing the list of genes to keep in the
+analysis. To keep all gene use a NULL object, (default NULL)}
 
 \item{min_expression}{The minimum average required expression across
-all samples to keep the gene}
+all samples to keep the gene (default 2)}
 
-\item{output_folder}{Folder were the matrices will be produced}
+\item{output_folder}{Folder were the matrices will be produced (default .)}
 
-\item{lfc_threshold}{The minimum fold change to consider a gene significant}
+\item{lfc_threshold}{The minimum fold change to consider a gene significant
+(default 0)}
 
-\item{my_contrast}{A list containing contrast vectors}
+\item{my_contrast}{A list containing contrast vectors: you can use
+list(c('condition', 'TEST', 'CTRL') to build it)}
 
-\item{basemean_threshold:}{The minimum basemean of genes to be kept}
+\item{basemean_threshold:}{The minimum basemean of genes to be kept
+(default 0)}
+}
+\value{
+A list containing for each comparison given in my_contrasts
+(keys of the list) a sublist containing:
+\enumerate{
+\item at \code{data} key: A dataframe indicating The number of differentially
+expressed genes and the number of up and down regulated genes
+\item at \code{dds} key: The dds object corresponding to a DESeqDatase object
+obtained after running the DESeq function.
+\item at \code{results} key: A dataframe containing the results of DEseQ2 analysis
+but for all gene
+\item at \code{de_results} key: A dataframe containing only differentially expressed
+genes
+}
 }
 \description{
 DESeq2 wrapper
@@ -45,6 +64,6 @@ perform a complete DESeq2 analysis including:
 \item Sample loading
 \item Normalisation
 \item Figure creation
-\item Differential expression analysis for the hcosen contrasts
+\item Differential expression analysis for the chosen contrasts
 }
 }

man/vline.Rd

+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/differiential_expression.R
+\name{vline}
+\alias{vline}
+\title{Function to draw a plotly horizontal line}
+\usage{
+vline(x = 0, color = "black")
+}
+\arguments{
+\item{x}{Location of vertical line}
+
+\item{color}{Color of vertical line}
+}
+\value{
+a list containing plotly parameters
+}
+\description{
+Function to draw a plotly horizontal line
+}