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In the first step, all reconstructed data sets were evaluated at different ECG-phases for diagnostic image quality and the optimal data set was then chosen for analysis.
Study design is a complex process that includes selection of the optimal population for study, data points for analysis, and analysis strategies.
Many of these biocuration tools are geared toward analysis of small-scale data such as small-number genes or proteins and therefore are not optimal for analysis of NGS data.
Thus, understanding microarray data processing steps becomes critical for performing optimal microarray data analysis.
To ensure optimal data quality, only RNA samples with RIN number ≥7.0 were included in the analysis as suggested by protocols for microarray experiments.
First, the parameters implemented in the configuration file are currently undergoing sweeps for a wide range of values to determine optimal settings for data analysis.
To determine the optimal tool for data analysis of the increased number of reads obtained with sequencing of short DNA, we compared LAST an alignment program recommended by MAP with two similar programs, Bowtie 2 and Blat (Kent 2002; Frith et al. 2010; Langmead and Salzberg 2012) using a training library generated through a MinION short-DNA-sequencing run (Table S3).
provided comments and data for the analysis.
Since most studies reviewed used a different input and/or output-encoding scheme, it is not clear at this point that there is an optimal way for encoding linkage data for a NN analysis.
Therefore, storing data in some "optimal" form for later analysis doesn't make any sense.
For example, optimal parameter values for qualitative analysis might not be optimal for quantitative analysis.
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