Similar protocols

Pipeline publication

[…] false discovery rate (FDR) of less than 5%., To focus on consistent sulfate-responsive genes, we selected genes that were significantly regulated by sulfate in at least two different experiments. We then calculated the Pearson correlation coefficients between each gene pair across all selected experiments using the R package rsgcc (). For network construction, an absolute correlation threshold of 0.81 was selected based on the best fit of the scale-free topology, as described previously (). The gene co-expression network was visualized using Cytoscape v3.4 (), and the network topology parameters were calculated using the NetworkAnalyzer plugin (). Co-expression modules were identified using Dynamic Tree Cut software ()., Gene ontology (GO) enrichment analyses were performed using BiNGO software (). Hypergeometric tests with an FDR of 5% as a cutoff were used to select significantly enriched GO terms. REVIGO software () was then used to reduce the redundancy between GO terms. In addition, we filtered and removed the general GO terms (those containing more than 5% of A. thaliana genes) to focus on the more specific terms., Several transcriptomic analyses of the response of A. thaliana plants to S starvation have been reported in the past several years (; ; ; ; ). Additionally, microarray data from sulfate treatments after S-starvation periods have also been published (; ). Therefore, a good opportunity exists to perform an integrated analysis of the sulfate transcriptomic data to answer relevant questions related to sulfate assimilation, such as “Is there a group of conserved genes involve […]

Pipeline specifications

Software tools Dynamic Tree Cut, BiNGO, REViGO