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With the purpose to identify variation patterns between two biological inputs, Berger et al. [ 291] applied an iterative procedure based on the GSVD, projecting CNA/GSE data into different decomposition directions.
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GSEA20 was used to analyze whether a previously defined gene sets show statistically significant, concordant differences between two biological states.
Correlation of RPKM distribution between two biological replicates.
One-way ANOVA uses those genes that have valid measurements (filtered intensities after normalization) across all experiments as input, and assigns a p-value to each gene indicating whether this specific gene displayed significantly varied expression levels between two biological replicates.
The error bars represent standard error between three biological replicates.
Error bars show the standard deviation between three biological replicate cultivations.
Reproducibility between the two biological replicates was assessed using Pearson correlation and correlation significance (t conversion).
The correlation between the two biological replicate experiments was 0.97.
Gene expression profiles were compared between the two biological replicates.
This enabled seamless temporal integration between the two biological scales.
Two biological ChIP-seq replicates and inputs were collected for AML1, AML1-ETO, p300, N-CoR, H3K4me3, and H3K27me3.
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