Gerwien F, Safyan A, Wisgott S, et al. A Novel Hybrid Iron Regulation Network Combines Features from Pathogenic and Nonpathogenic Yeasts. mBio. 2016;7(5):e01782-16. Published 2016 Oct 18. doi: 10.1128/mBio.01782-16
In this study, the authors performed transcriptome analyses in the WT strain (Candida glabrata) and strains deleted for AFT1, SEF1 and FTR1 genes using microarrays. They compared the compositions of transcriptomes between the deleted strains and the WT strain at 4 hours after iron depletion. Primary datasets were downloaded from GEO under accession number GSE84816.
Differential analyses were performed comparing deleted strains to the WT strain at 4 h time point. The tool GEO2R was applied to generate R code with LIMMA method.
The following table is a the Supp Data S2 table (DE genes) with logFC and Pvalue find in this dataset.
Gerwien F, Safyan A, Wisgott S, et al. A Novel Hybrid Iron Regulation Network Combines Features from Pathogenic and Nonpathogenic Yeasts. mBio. 2016;7(5):e01782-16. Published 2016 Oct 18. doi: 10.1128/mBio.01782-16
In this study, the authors performed transcriptome analyses in the WT strain (Candida glabrata) using microarrays. They compared the compositions of transcriptomes at different time points (0.5 h, 1h, 2h, 4h) after iron depletion, to 0 h. Primary datasets were downloaded from GEO under accession number GSE84816.
Differential analyses were performed comparing 0.5, 1, 2 or 4 h to the 0 h time point. The tool GEO2R was applied to generate R code with LIMMA method.
The following table is a the Supp Data S2 table (DE genes) with logFC and Pvalue find in this dataset.
Lelandais G, Denecker T, Garcia C, Danila N, Léger T, Camadro JM. Label-free quantitative proteomics in Candida yeast species: technical and biological replicates to assess data reproducibility. BMC Res Notes. 2019;12(1):470. Published 2019 Aug 1. doi:10.1186/s13104-019-4505-8
In these experiments, mass spectrometry analyses were performed in the yeast Candida glabrata. Technical and biolocal replicates were done in order to evaluate the variability associated to each type of data reproduction. Primary datasets were downloaded from PRIDE under accession number PXD014125.
Protein abundances obtained in two cell growth conditions (alkaline pH or standard) were compared, in order to identify differentially expressed proteins. LIMMA method was applied with default parameters, in order to calculate p-values.
The following table is a the Supp Data S2 table (DE genes) with logFC and Pvalue find in this dataset.
Linde J, Duggan S, Weber M, et al. Defining the transcriptomic landscape of Candida glabrata by RNA-Seq. Nucleic Acids Res. 2015;43(3):1392–1406. doi: 10.1093/nar/gku1357
RNAseq experiments were performed to identify differentially expressed genes during pH alkaline shift in the pathogenic yeast Candida glabrata. Primary datasets were downloaded from GEO under accession number GSE61606.
Differential expression measurements together with statistical p-values were obtained from the Supplementary Table S1 in Linde et al. article. In this file we considered information in the spreadsheet named "Expression_pH_change". Note that logFC represent the ratio between pH4 and pH8 conditions, i.e. log(pH4/pH8). This values were modified to rather represent log(pH8/pH4).
The following table is a the Supp Data S2 table (DE genes) with logFC and Pvalue find in this dataset.