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However, the inter-individual variability was much larger than the variability between different sample pools of the same line.
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Correspondence of bands between different samples was performed with 1% dynamic range settings.
This reduced the variation between different pools by dropping pools with poor PCR or sequencing quality.
RNA from the different samples was pooled into a BC and a BN library.
So in practice, different samples were pooled together to reduce the biological variation [ 29, 36- 38].
The bam files were also used to normalize read depth between samples, which was used to compare samples between different pools (Supplementary Table 2).
The statistical differences between both methods were obtained by analyzing 16 different plasma samples (pooled) and paired t-test was used for comparison between the mean values.
In case of the prostaglandin F receptor (Ptgfr), despite of very different mean expression levels between both lines, this difference was only significant when sample pools instead of individual samples were compared.
Differential transcriptome maps, based on the ratio between corresponding gene expression values from two 'A' and 'B' samples or sample pools, relative to two different biological conditions, may be easily generated.
However, in an actual association study, pooled DNA estimates are not compared within and between pools of the same individuals but rather between different pools consisting of different individuals.
Standing out were 28 different keratin proteins identified and quantified in our proteomics analysis, with the majority of these showing significant increases in abundance between the pre-malignant and malignant sample pools.
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