As for human CEACAM18, no cytoplasmic domain exon could be identified due to its small size and lack of corresponding EST sequences.
However, the fold changes between men and women of the sex-biased genes identified in the total sample were highly concordant between age ranges (Additional file 10), suggesting that the identified sex effects occur at all ages, but that some effects may be stronger at a certain age or may not have been identified due to reduced power in the smaller groups of selected ages.
Thus, to the extent that significant differences between family types were not identified due to insufficient power, these differences would have been small.
A small number of the FseI derived DG sequences were also not identified due to the close proximity of two FseI sites.
Experimentally, mini-proteins are difficult to isolate and identify due to their small sizes; likewise, in bioinformatic analyses, short genes are the most difficult to predict.
In the current study we specifically wanted to test the hypothesis that a meta-analysis of CAN/IFTA samples from different sources would confirm the role of specific growth factors and/or integrin pathways and potentially reveal new pathways correlative with the progression of CAN/IFTA, which individual studies failed to identify due to the limitations with small sample sizes.
The onset of the storm is difficult to identify due to the effects of a smaller CME ejected from the sun just three days prior to the very large eruption that caused the storm on 17.
The additional dentin/soft tissue border, which is likely more challenging anatomy than the tooth to surrounding bony support to identify, due to intricate pulpal canal architecture of small dimension, would require identification.
Associations from other genes in the region have also been reported [5] [11], however the extremely high linkage disequilibrium (LD) covering a large part of the HLA region makes it difficult to detect independent effects of individual genes [3] and these studies may have suffered from lack of statistical power to identify true effects due to small sample sizes and not dense enough genotyping.
BCM performed well in identifying several SNPs having evidence of involvement in the pathogenesis of LOAD that would not have been identified by univariate analysis due to small main effect.
