Sentence examples for all data transformation from inspiring English sources

It is important to note that for 10% of conditions, the prevalence estimates after standardization were less consistent; this finding underscores the need for the research community to gain a complete understanding and provide full transparency to all data transformation activities that occur from the source through analyses, as these manipulations can materially impact study results.

All data transformation and statistical analysis were carried out in R 2.0.1 (http://www.r-project.org/), BioConductor 1.5 (http://www.bioconductor.org/), making extensive use of modified versions of the package aCGH in particular (Paris et al, 2004; Natrajan et al, 2006) and S-Plus (version 6.2.1).

All data transformations and statistical analyses were performed using SAS® version 9.4 (SAS Institute, Cary, NC, USA).

All data transformations and statistical analyses were performed using SAS version 9.2 (SAS Institute, Cary, NC).

All data transformations, set operations, and comparisons were performed in the R statistical environment (http://www.r-project.org), and visualized using the ggplot graphical package (http://ggplot2.org) and d3.js graphical library (http://d3js.org/).org/

All data transformations were performed using the contributed R package SMA (Statistical Microarray Analysis), available from 'Terry Speed's Microarray Data Analysis Group Page': http://www.stat.berkeley.edu/users/terry/zarray/Html/index.html.html

Differences in Fq'/ Fm'max, Ek and rETRmax between the three algal morphotypes at 07 h00 and 12 h00 were identified using an ANOVA general linear model (test assumptions for normality [Anderson-Darling test] and homogeneity of variance [Bartlett's test] were met without data transformation; all samples were from independent thalli).

It applies g-log transform (generalised log transformation) for data transformation to stabilise variance [ 18, 19].

All analyses were pre-specified with distribution-based data transformation.

Data transformation was applied to set all the negative raw values at 1.0, followed by Quantile normalization and log2 transformation.

Data transformation and quality filtering were then performed and all control features were excluded from subsequent analyses [ 12].