inst/extdata/datainput.md

In pcaExplorer: Interactive Visualization of RNA-seq Data Using a Principal Components Approach

• pcaExplorer accepts only text files, either comma, semicolon, or tab-separated. This avoids proprietary formats such as Excel, which can also inadvertently convert your gene identifiers to dates or floating point numbers (SEPT2, see more here)
• by default, tab-separated values are expected, but you can change this for each input file with the related radio buttons
• for count data: features are in the rows, samples are stored in the columns
• for the metadata: each row stores the relevant experimental variables of each sample
• for the gene annotation: each row relates to a feature (i.e. a gene), with its id in the row names, and at least a column called gene_name, containing a more readable format (e.g. HGNC gene symbols)
• it is important to have headers, as they are used in constructing the dds and dst objects and checking their validity: for example, the column names of the count matrix have to be identical to the row names of the sample metadata. This small constraint guarantees a higher degree of robustness for all the subsequent steps
• if your data in stored in Excel sheets, export them to csv format (specify the correct separator accordingly when loading the data - you can always open them in a text editor to check)
• general reminder: if you launch pcaExplorer directly from the terminal/RStudio IDE, you can pre-compute the objects, this can speed up

pcaExplorer documentation built on Nov. 8, 2020, 5:29 p.m.