2016
DOI: 10.1016/j.chroma.2016.06.067
|View full text |Cite
|
Sign up to set email alerts
|

Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
36
0
1

Year Published

2018
2018
2022
2022

Publication Types

Select...
4
2
1

Relationship

0
7

Authors

Journals

citations
Cited by 31 publications
(37 citation statements)
references
References 37 publications
0
36
0
1
Order By: Relevance
“…Such metabolites are essential to living organisms and their levels are most of the time correlated to metabolism perturbations or disease states. Even though the derivatization protocols make the sample preparation more extensive, their utilization can be maximized in combination with GC×GC [47–55].…”
Section: Non‐targeted Analysis Applicationsmentioning
confidence: 99%
“…Such metabolites are essential to living organisms and their levels are most of the time correlated to metabolism perturbations or disease states. Even though the derivatization protocols make the sample preparation more extensive, their utilization can be maximized in combination with GC×GC [47–55].…”
Section: Non‐targeted Analysis Applicationsmentioning
confidence: 99%
“…The final m/z signals selected from the PLS-DA modeling were ranked individually according to their ability to distinguish between responder and non-responder patients, using one-way ANOVA F -test analysis. False discovery rates (FDR) were also estimated for the respective m/z signals according to a null distribution ANOVA F -test approach, as described previously in metabolomics studies ( 21 , 22 ). Next, PCA was performed to highlight the separation between responders and non-responders to each antipsychotic treatment when considering only the selected compounds in which FDR ≤ 0.05 (i.e., probability of type-I error ≤ 5%).…”
Section: Methodsmentioning
confidence: 99%
“…the wine vintage. Fisher ratio, however, highlighted the portions of the chromatograms that were statistically relevant by differentiating the pixels with large class-to-class variation (σ 2 cl ) and the within-class variation (σ 2 err ) [37,39,46,61,62]. Fisher ratio is calculated at every point in the separation space and may be calculated by the ratio of σ 2 cl of the detector signal and the sum of the σ 2 err of the detector signal.…”
Section: Discriminating Analysis Using Pixel-and Peak Table-based Datmentioning
confidence: 99%
“…Although comparative analysis using peak tables is a widespread practice among GC practitioners, important information may be lost or overlooked during univariate data processing. The application of chemometric techniques and computational tools to extract meaningful and context-oriented information is critical to provide reliable and unbiased assessments [36][37][38][39][40][41]. Two aspects of data generated by GC×GC-MS that challenges univariate processing are the enormous size and complex structure of the raw measurements.…”
Section: Introductionmentioning
confidence: 99%