Sentence examples for for Cuffdiff output from inspiring English sources
Downstream analysis for Cuffdiff output was done using CummeRbund [ 34].
Gene IDs and log2 fold-change expression values for significant hits, that had FPKM values in both the control and the infected differential expression testing for transcripts (Cuffdiff output files), were then analyzed using the Ingenuity Pathway Analysis software.
The raw fragment alignments to each gene obtained from the "genes.read_group_tracking" file produced from the Cuffdiff output were used for differential analysis.
The Cuffdiff output contained normalized FPKM for comparison between libraries (Additional file 1).
Reads per KB per million (RPKM) values were calculated by an in-house script based on the count table of Cuffdiffs output.
A gene list for metascape analysis was generated using the output from the cuffdiff program, in which 72 genes judged as 'significantly differentially expressed' (p < 0.05) in cuffdiff output (gene_exp. diff, Supplementary Dataset S1) were contained (Supplementary Fig. S3a).
Genes that showed differential expression with log2 fold change ≥ 1.0 and a false discovery rate (FDR) value ≤ 0.01 from the Cuffdiff output were considered as differentially expressed genes in our study.
Genes containing Gene Ontology annotations ('canonical glycolysis' (GO 0061621) and 'hypoxia-inducible factor-1alpha signaling pathway' (GO 0097411)) were extracted using Ensembl Biomart49 and sorted by corresponding values (common logarithms of ([FPKM of RCC4-EV] + 1)/([FPKM of RCC4-VHL] + 1)) calculated from the same cuffdiff output file (Supplementary Fig. S3b).
Cuffdiff output files were further processed with the R package CummeRbund [ 71] to integrate the output from different accessions into a single data set for differential expression analysis and visualization.
Furthermore, the Cuffdiff output was utilized to determine the sex bias of all the genes in the study.
Lists of significantly differentially expressed genes were extracted from the Cuffdiff output using the CummbeRbund (version 2.8.2) package in R/Bioconductor [ 46]; see Table S2.
