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The variability in measurements of biological samples such as saliva can conceal real trends in datasets when sample sizes or numbers of data points are relatively few.
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For an arbitrary sequence in dataset, when a motif occurred once, the frequency value was recorded as "1"; if the motif occurred twice, the value would be 2, and so on; otherwise if the motif did not occur, the corresponding frequency value was recorded as "0".
Moreover, although the overall differences in relative expression levels of TWIST1 were small across different subtypes, TWIST1 expression was significantly elevated in the basal as well as the ERBB2 subtypes in both datasets when compared to luminal A subtype.
The three groups were re-identified in both datasets when changing the number of CpGs to be included in the clustering procedure (Additional file 1: Figure S1C).
The proportion of dinucleotide repeats was greater among genomic microsatellites than among EST-SSRs, and this proportion increased with longer SSRs, overtaking trinucleotide repeats in all datasets when the minimum length was set to 20 bp in gSSRs and 30 bp in EST-SSRs.
E-box containing motifs were significantly enriched in all datasets when analyzed by PscanChIP and MEME-ChIP (Additional file 4).
Although a large fraction of the contigs were assembled accurately, fragmentation of the contigs was more severe in metagenomic datasets when compared to the isolate assemblies.
Upon assembly, the Applied Biosystems and Illumina realignments of the B6 sequence reads differed from the B6 reference sequence for 41 and 60 residues (Table 1), respectively; 29 of these differences were consistent in both datasets when compared to the reference sequence.
The histogram not only highlights the increase in the percentage of reads 17to2626 nt in length in the NRL datasets when compared to the BRL datasets, but also shows a change in ratios between the different size groups, in particular when comparing the ratio between the 21 and 24 nt groups.
Seizure patterns are wide and complex resulting in a massive datasets when digitally acquired.
In addition, we found a correlation between mean April temperature and population differentiation (FST) in all three datasets (when DE-RUGEN was excluded).
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