In jgockley62/UW_RNASeq: Identify differentially expressed genes counts data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

A configuration file defines the inputs for the RNA-seq workflow. Update the default parameters to the Synapse ID where your data is stored and to the factor and continuous variables you want to test in the covariate model selection. The full list of configurable options are:

counts:
  synID: Synapse ID to counts data frame with identifiers to the metadata as column names and gene ids in a column.
  version: Optionally, include Synapse file version number (e.g. 3).
  gene id: Column name that corresponds to the gene ids (e.g. feature).
metadata:
  synID: Synapse ID to cleaned metadata file with sample identifiers in a column and variables of interest as column names.
  version: Optionally, include Synapse file version number (e.g. 3).
  sample id: Column name that corresponds to the sample ids (e.g. donorid).
biomart:
  synID: This input is optional. If left blank, Ensembl will be queried with the gene ids provided in the counts. Otherwise, you may provide the Synapse ID to gene metadata from Ensembl. This must include gene length and GC content in order to implement Conditional Quantile Normalization. 
  version: Optionally, include Synapse file version number (e.g. 3).
  gene id: Column name that corresponds to the gene ids (e.g. ensembl_gene_id)
factors: List of factor variables in brackets. Variables must be present in the metadata as column names (e.g. [ "donorid", "source"]).
continuous: List of continuous variables in brackets. Variables must be present in the metadata as column names (e.g. [ "rin", "rin2"]).
conditions: Filtering low-expression genes is a common practice to improve sensitivity in detection of differentially expressed genes. Low count genes that have less than 1 counts per million (cpm) in 50% of the samples per the conditions provided here will be removed. (e.g. ["diagnosis", "sex"])