Sentence examples for in downstream data from inspiring English sources

Utilizing ArrayAssist (Stratagene, La Jolla, CA), raw Affymetrix CEL files were processed by applying the MAS5 algorithm, to assign detection calls (Present/Marginal/Absent) for each probe set that were subsequently used in downstream data filtering.

Utilizing ArrayAssist (Stratagene), raw Affymetrix CEL files were processed by applying the MAS5 algorithm, to assign detection calls (Present/Marginal/Absent) for each probe set that were subsequently used in downstream data filtering.

Although it may be possible to compensate for such effects in downstream data analysis by appropriate statistical methods, this observation underlines the importance of recording these variables in biobanks.

During data pre-processing the replicate measurements are summarized to average values, by determining the mean, median or a trimmed mean, to reduce the influence of noise in downstream data analysis.

Approaches to exploit technical variance information to improve robustness and sensitivity in downstream data analyses have been developed in recent years for differential expression analysis (Liu et al., 2006), principal component analysis (PCA; Sanguinetti et al., 2005) and differential pathway analysis (Glaab and Schneider, 2012).

The simulation result showed 5 dB dispersion induced power penalty in the downstream data transmission and less than 0.3 dB for the upstream transmission over 25 km SMF at the BER of 10−9 for the double tone data modulation.

The transformed data matrix can subsequently be used in the downstream data analysis phases, using either the individual interaction scores or the rows of the score matrix (i.e. genetic profiles).

During these months, the flow in the Gabilan Creek at elevated areas can increase more than 1000-fold over base flow, resulting frequently in flooding downstream (data from water flow meter at location D, "Gabilan Creek", see [53]).

Pooled data with ~ 30 fold coverage from both sequencing runs were used in all downstream data analysis.

Thus, when analyzing a clinical NGS data set, it is critical to understand the analytical limitations of a given assay as represented in the downstream data analysis.

The generally short read lengths coupled to the enormous amount of data to be analyzed and reduced raw accuracy, compared to Sanger sequencing, has introduced many challenges in the downstream data analysis [ 18].