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Normalizing read counts between samples can also be problematic.
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At the same time, differential levels of amino acid modification between the samples can also seriously affect protein quantification, as each differently modified peptide should be quantified independently.
The expression between two samples can also be assessed with the FDR False Discovery Ratee) method, which is a statistical method used in multiple hypothesis testing to correct for P-value [ 87].
But the techniques we use today in making the samples can also be challenging.
The samples can also be dried under nitrogen gas.
Multiple samples can also be simultaneously sequenced by barcoding (multiplexing).
Cryptic relatedness, i.e., unknown genetic relationships between individuals in a sample, can also confound the association analysis due to nonindependence and larger than expected phenotypic variance (Voight and Pritchard 2005; Cheng et al. 2010).
A close relationship between samples can be seen.
Similarities and differences between samples can be visualized by plotting.
Concentration differences can be observed between arterial and venous sampling and can also be dependent on the location of the specific vessels within the body as reviewed by Chiou (7, 8) as early as 1989.
The relatively small sample size can also be considered a limitation however trends were consistent between specimens and only significant changes were discussed here.
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