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For one time point, all six replicates were run together, reducing technical variability.
McIntyre, L. M. et al. RNA-seq: technical variability and sampling.
To overcome this technical variability correct experimental design is critical.
This maximizes assay efficiency and eliminates technical variability in both sample preparation and analysis.
Hansen, K. D., Irizarry, R. A. & Wu, Z. Removing technical variability in RNA-seq data using conditional quantile normalization.
Hansen, K. D., Irizarry, R. A. & Wu, Z. J. Removing technical variability in RNA-seq data using conditional quantile normalization.
This is not a concern here, however, as all sites for which the niche-association score was calculated were oral sites with similar technical variability (Fig. 1a).
However, the true technical variability cannot be accessed unless the same cell can be analyzed multiple times for RNAseq, which has not been practical.
The technical variability of the protocol was evaluated by processing 8 identical replicates in parallel, originating from the same total RNA batch.
Three independent hybridizations were performed on each sample to study technical variability.
For our experiment, we considered technical variability to be 20%.
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