Additional file 1 of Phoenics: a novel statistical approach for longitudinal metabolomic pathway analysis

Supplementary file 1: Figure S1. Positive predictive value (PPV) and sensitivity for the test of the time effect in simulation SimulatedH1_ConditionTime. Figure S2. Percentage of differential metabolites for the time effect in the overlapping pathways in simulation SimulatedH1_ConditionTime. Table S1. Results of the test of the condition effect in simulation SimulatedH1_Condition. Table S2. Results of the test of the time effect in simulation SimulatedH1_Time. Table S3. Results of the test of the condition effect in simulation SimulatedH1_ConditionTime. Table S4. Results of the test of the time effect in simulation SimulatedH1_ConditionTime. Figure S3. Percentage of times the pathway “ABC transporters” is detected positive for the test of the time effect in simulation SimulatedVSize_ConditionTime. Figure S4. Percentage of differential metabolites for the condition effect in the overlapping pathways in simulation SimulatedH1_ConditionTime. Figure S5. Percentage of times the pathway “ABC transporters” is detected positive for the test of the condition effect in simulation SimulatedVSize_ConditionTime. (pdf file).

Institutions

Publication Details

Journal
Figshare
Published
2025-01-01
DOI
https://doi.org/10.6084/m9.figshare.28812393.v1
Primary Topic
Metabolomics and Mass Spectrometry Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Additional file 1 of Phoenics: a novel statistical approach for longitudinal metabolomic pathway analysis

Figshare
Metabolomics and Mass Spectrometry Studies
article

Additional file 1 of Phoenics: a novel statistical approach for longitudinal metabolomic pathway analysis

article en

Abstract

Supplementary file 1: Figure S1. Positive predictive value (PPV) and sensitivity for the test of the time effect in simulation SimulatedH1_ConditionTime. Figure S2. Percentage of differential metabolites for the time effect in the overlapping pathways in simulation SimulatedH1_ConditionTime. Table S1. Results of the test of the condition effect in simulation SimulatedH1_Condition. Table S2. Results of the test of the time effect in simulation SimulatedH1_Time. Table S3. Results of the test of the condition effect in simulation SimulatedH1_ConditionTime. Table S4. Results of the test of the time effect in simulation SimulatedH1_ConditionTime. Figure S3. Percentage of times the pathway “ABC transporters” is detected positive for the test of the time effect in simulation SimulatedVSize_ConditionTime. Figure S4. Percentage of differential metabolites for the condition effect in the overlapping pathways in simulation SimulatedH1_ConditionTime. Figure S5. Percentage of times the pathway “ABC transporters” is detected positive for the test of the condition effect in simulation SimulatedVSize_ConditionTime. (pdf file).

Figshare
Université Fédérale de Toulouse Midi-Pyrénées (FR), Université de Montpellier (FR), Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR), Metabo (Switzerland) (CH)
Openalex Percentile: Top 53%
Metabolomics and Mass Spectrometry Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Additional file 1 of Phoenics: a novel statistical approach for longitudinal metabolomic pathway analysis · Figshare (2025) | TGRS Research Map | TGRS