knitr::opts_chunk$set(echo = F, fig.path = "figures/")
We look forward to make the quantitative summary for some critical values and parameters, which are summaried as in the follwing table
# qunt.sammay <- data.frame( "recountID" = parameters$recountID, # "Descrip.dataset" = parameters$classColumn, # "no.runs" = length(loaded$runPheno$run), # "No.samples before filtering" = length(loaded$runPheno$sample), # "No.genes before filtering" = nrow(loaded$countsPerRuns), # "No.genes NA vlues" = loaded$filteredData$naGenes, # "No.genes zero.variance" = length(loaded$filteredData$zeroVarGenes), # "No.genes kept filtering" = length(loaded$filteredData$keptGenes), # "selected classes" = data.frame(loaded$filteredData$selectedClasses), # "No.classes" = length(unique(loaded$filteredData$classes)), # "Nosamp per.class"= table(loaded$samples.per.class) # ) #kable(qunt.sammay)
A summarized report about preprocessing process before we start to study the impact of classification methods on RNAseq count data.
| recountID | No.runs | No.features | No.samples after prerocessing | No.genes after preprocessing | unique samples | pheno Table dimensions | No. of classes | |---------------------------|--------|--------|--------|--------|--------|--------|--------| | "SRP042620"| 167 |58037 | 162 | 55506 | 167 | 162 X 22 | 5 | | "SRP057196"| 461 |58037 | 461 | 16941 | 461| 461 X 26 | 9 | | "SRP003611"| 52 |58037 | 0 | 51239 | 8| 0 X 17 | | "SRP061240"| 384 |58037 | 186 | 7056 | 192 | 186 X 19 | 3 | | "SRP062966"| 117 | 58037 | 117 | 45247 | 117 | 117 X 25 | 2 | | "SRP066834"| 729 | 58037 | 729| 15741 |729 | 729 X 23 | 3 | | "SRP056295"| 520 | 58037 | 259 | 43780 | 263 | 259 X 17 | 2 | | "SRP039694"| 15 | 58037 | 0 | 46858 | 0 | 0 X 25 | 0 |
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