SummaryData

This function gives indices such as Observed richness, Shannon index, Inverse Simpson, ... of higher level such as levelily, order, phylum, ...

An approach to identify microbiome biomarker for time to event data by discovering microbiome for predicting survival and classifying subjects into risk groups.
Classifiers are constructed as a linear combination of important microbiome and treatment effects if necessary.
Several methods were implemented to estimate the microbiome risk score such as the LASSO method by Robert Tibshirani (1998) <doi:10.1002/(SICI)1097-0258(19970228)16:4%3C385::AID-SIM380%3E3.0.CO;2-3>, Elastic net approach by Hui Zou and Trevor Hastie (2005) <doi:10.1111/j.1467-9868.2005.00503.x>, supervised principle component analysis of Wold Svante et al. (1987) <doi:10.1016/0169-7439(87)80084-9>, and supervised partial least squares analysis by Inge S. Helland <https://www.jstor.org/stable/4616159>.
Sensitivity analysis on the quantile used for the classification can also be accessed to check the deviation of the classification group based on the quantile specified. Large scale cross validation can be performed in order to investigate the mostly selected microbiome and for internal validation.
During the evaluation process, validation is accessed using the hazard ratios (HR) distribution of the test set and inference is mainly based on resampling and permutations technique.

Thi Huyen Nguyen

MicrobiomeSurv

Biomarker Validation for Microbiome-Based Survival
Classification and Prediction

Olajumoke Evangelina Owokotomo

Ziv Shkedy

SummaryData function

<dl><dt>Micro.mat</dt>
<dd>an OTU matrix with OTUs in rows and subjects in columns.</dd>
<dt>info</dt>
<dd>A n x 2 matrix containing a column of OTU's names and a column of the corresponding information of the chosen level.</dd>
<dt>measure</dt>
<dd>The indices at chosen level that user wishes to use. It can be observed richness, Shannon index, inverse Simpson, ...</dd></dl>

Arguments

Thi Huyen Nguyen, <a href="/link/thihuyen.nguyen%40uhasselt.be?package=MicrobiomeSurv&version=0.1.0" data-mini-rdoc="MicrobiomeSurv::thihuyen.nguyen@uhasselt.be">thihuyen.nguyen@uhasselt.be</a>
Olajumoke Evangelina Owokotomo, <a href="/link/olajumoke.x.owokotomo%40gsk.com?package=MicrobiomeSurv&version=0.1.0" data-mini-rdoc="MicrobiomeSurv::olajumoke.x.owokotomo@gsk.com">olajumoke.x.owokotomo@gsk.com</a>
Ziv Shkedy

Author

This function gives indices such as Observed richness, Shannon index, Inverse Simpson, ... of higher level such as levelily, order, phylum, ... — SummaryData

<dl>

<dt>Micro.mat</dt>
<dd>an OTU matrix with OTUs in rows and subjects in columns.</dd>


<dt>info</dt>
<dd>A n x 2 matrix containing a column of OTU's names and a column of the corresponding information of the chosen level.</dd>


<dt>measure</dt>
<dd>The indices at chosen level that user wishes to use. It can be observed richness, Shannon index, inverse Simpson, ...</dd>

</dl>

Thi Huyen Nguyen, <a href='mailto:thihuyen.nguyen@uhasselt.be'>thihuyen.nguyen@uhasselt.be</a>
Olajumoke Evangelina Owokotomo, <a href='mailto:olajumoke.x.owokotomo@gsk.com'>olajumoke.x.owokotomo@gsk.com</a>
Ziv Shkedy

SummaryData: This function gives indices such as Observed richness, Shannon index, Inverse Simpson, ... of higher level such as levelily, order, phylum, ...

Description

Usage

Value

Arguments

Author

See Also

Examples