Here are the answers to the questions:

1. What tool was used for pathway enrichment analysis?
The tools used for pathway enrichment analysis were GOseq R package and KOBAS software.

2. Was a tool version number provided?
Yes, the version number of the DESeq R package (v1.18.0) was provided, but not for GOseq R package or KOBAS software.

3. What gene set library was queried (eg: GO, KEGG, Reactome or other)?
The gene set libraries queried were GO and KEGG.

4. Was a background gene list defined for pathway enrichment analysis?
Not described.

5. What statistical test was used for enrichment analysis?
Not described, but the DESeq R package uses a model based on the negative binomial distribution to identify differential gene expression.

6. Was false discovery rate correction used to control the number of false positives in the pathway enrichment analysis?
Yes, Benjamini and Hochberg’s approach was performed to adjust the obtained P-values for the differential gene expression analysis, but it is not explicitly stated if this was also applied to the pathway enrichment analysis. However, a corrected P-value ≤0.5 was used as the cutoff for GO enrichment analysis, and an adjusted P-value ≤0.01 was used for DEG identification.