使用data.table::fread()拉入每个tsv，只选择需要的列，使用rbindlist()，合并一次到metaMatrix以获取样本...
We can see here that, when accessing the column with single-square-bracket [1], we get a DataFrame but with one less column. If, however, we access it with the double-square-bracket [[1]], we get a numeric vector of heights. The data returned by using the single bracket stays the...
Note that replacing the 2 by a 1 applies check.if.NA to each row of the dataframe.## name height weight sex ## FALSE FALSE TRUE FALSE I know that there is a problem with weight. Let's check who is the problem: name[which(is.na(weight))] ...
# User / Session 1library(bigmemory)library(biganalytics)library(bigtabulate)#Create big.matrixsetwd("/Users/sundar/dev")school.matrix<-read.big.matrix("./numeric_matrix_SAT__College_Board__2010_School_Level_Results.csv",type="integer",header=TRUE,backingfile="school.bin",descriptorfile="school...
Missing data can be a real pain to manage in a dataframe that has just been created using read.csv. R for some reason has mulitple ways of indicating missing data, depending on the context. This includesNA NaN <NA> For some reaason when you're cleaning data - especially if you clean ...
("R is a great language","R has many uses","R is cool!"),stringsAsFactors=FALSE)# Create a DataframeSource on columns 2 and 3: df_sourcedf_source<-DataframeSource(example_text[,2:3])# Convert df_source to a corpus: df_corpusdf_corpus<-VCorpus(df_source)# Examine df_corpusdf_...
before– we can use this to recover and create a data.table, and add the rest of our data back on. Interestingly, to join together data and polygons to create a SpatialPolygonsDataFrame, you need the row names to match up. As such, we create a data.frame with the same row names....
# Add feature data (gene id's as column)featureData<-data.frame(gene=rownames(data))(mcols(dds)<-DataFrame(mcols(dds),featureData)) ## DataFrame with 51574 rows and 1 column ## gene ## <factor> ## 1 oystercontig_1 ## 2 oystercontig_2 ## 3 oystercontig_3 ## 4 oystercontig_...
# Access the plot and results dataframe for the first DA methodexample_plot<-results_file_input[[1]]$plotexample_results<-results_file_input[[1]]$results# Use the example data in ggpicrust2 packagedata(ko_abundance)data(metadata)results_file_input<-ggpicrust2(data =ko_abundance,metadata =...
modTOMSignificantes = which(modTOM>0.4)###warnings()#Organize the genes by importance inside the modulegenes = colnames(expression)#sum(is.na(genes))#It must return 0.#Create the dataframe since the beginninggeneInfo0 = data.frame(ESTs = genes, module...