title | author |
---|---|
analyze time course gene expression data in _C. glabrata_ under phosphate starvation |
Ananya Albrecht-Buehler, Amanda Caraballo, Bin He |
Goal
Identify temporal order of transcriptional response to phosphate starvation in the human commmensal and opportunistic pathogen C. glabrata
Data
The transcriptome profiling experiment was performed in 2017. For the present analysis, we will only consider the non pho80∆ samples. There are two genotypes: wild type (wt) and pho4∆. They should be analyzed separately to identify transcriptional responses that either depend on the transcription factor Pho4 or not.
There are two data files in the data
folder (see README.md therein). They can be directly read into R using the tidyr::read_tsv()
function, which will automatically decompress the zip files.
Here are some sample code
# assuming the R markdown is in the present (project root) folder.
library(tidyverse)
normalized <- read_tsv("data/Ex009_normalized_log2_read_counts.zip")
sampleinfo <- read_csv("data/Ex009_experiment_set_up_20171019.csv")
# to turn the data into a matrix
matrix.data <- as.matrix(normalized[,-1])
rownames(matrix.data) <- normalized$gene
Resource
- http://www.opiniomics.org/you-probably-dont-understand-heatmaps/
- Bin's take on gene expression clustering (a rendering of the
analysis/c_glabrata_timecourse_analysis_HB_20200801.nb.html
): https://rpubs.com/emptyhb/645504