The allele fractions of these SNPs deviated from the expected 0.5 by an average of 0.064 in the HaloPlex data, compared to 0.135 in the WGS data, demonstrating that the increased sequencing depth in the HaloPlex data is associated with increased precision of allele fractions (Additional file 1: Figure S1).
Since in prokaryotes the content of protein coding sequences (GCNAT) determines corresponding genomic GC, the same parameters are also applicable to genomic GC content (including RNA-coding genes and non-coding regions) without any significant loss of precision (Additional file 1: Table S3).
Our results showed that the per-gene regression normalization increase the precision of fold change estimates (Additional file 1: Figure S2) and the power for detecting differential expressions especially when the regression coefficient is far from 1 and the variation is not too large.
It is hard to manually annotate onsets in an audio file below a precision of around some tenths of milliseconds.
However, application of this method on a whole-genome scale, where the ratio of positive to negative examples is roughly 20 times smaller, would lead to an expected precision of just 11% (details in additional file 3: Supplementary discussion).
Articles with exceedingly long (> 1 Mb) or many (> 100) sequences were removed from further processing to increase the precision of our approach, since some supplementary files contain genome-wide sequence data (e.g. microarray probes).
Maximum width coverage for a single EST was 99.5% and 22 ESTs had coverage greater than 90% while 642 ESTs had coverage greater than 50% validating the precision of the sequence data obtained (Additional file 7).
Additional file 25: Regionality vs. precision of variation relative to the YJM strain.
Respective associations in the models adjusted only for age were all non-significant and the precision of the effect estimates was decreased (Additional file 2: Table S2).
The sampling duration has been standard for this instrumentation, partially due to the file sizes, statistical normality, and precision of measurement with respect to the experimental manipulation(s).
Optimization of parameters using this algorithm resulted in an increased precision of 99.9% and recall of 97.7% (File S1, Figure S1, Table S6).
