Log-linear Model for Modeling for Biases in Microbiome Studies

C.E. Credits: P.A.C.E. CE Florida CE
Speaker

Abstract

Microbiome sequencing data are known to be biased; the measured taxa relative abundances can be systematically distorted from their true values at every step in the experimental/analysis workflow. If this bias is not accounted for, it can lead to spurious discoveries and invalid conclusions. Unfortunately, in order to measure bias it is necessary to have samples for which the true relative abundances are known, such as model or mock community samples.  In this chapter, we propose a log-linear model for the biases observed when analyzing model communities data.  Our model expands the recent work from McLaren, Willis and Callahan (MWC) [eLife, 8:e46923, 2019] that proposed a multiplicative bias structure for microbiome data. Our extension of the MWC model is general enough to allow testing of complex hypotheses, and readily handles situations in which samples have different number of bacteria present by design. An F-test with permutation-based hypothesis testing is proposed to assess statistical significance. We conduct simulations to show the validity and the power of our method, and also demonstrate the utility of our method through an analysis of a complex model communities dat=aset that allows us to directly test  the multiplicative bias assumption of the MWC model. An R package implementing the proposed work is publicly available at https://github.com/zhaoni153/MicroBias

Learning Objectives:

1. Understanding the multiplicative bias-generation procedure in microbiome sequencing.

2. Understanding how we can measure the sequencing bias as ratios of abundances.


Show Resources
You May Also Like
SEP 14, 2021 7:00 AM PDT
C.E. CREDITS
SEP 14, 2021 7:00 AM PDT
Date: September 14, 2021 Time: 7am PDT, 10am EDT, 4pm CEST A conventional thermal cycler has long been a commodity product in the lab and end-point PCR techniques can be completed almost wit...
SEP 17, 2021 12:00 PM CST
C.E. CREDITS
SEP 17, 2021 12:00 PM CST
Date: September 16, 2021 Time: 9:00pm (PDT), 12:00am (EDT) 3D cellular models like organoids and spheroids offer an opportunity to better understand complex biology in a physiologically rele...
NOV 09, 2021 11:00 AM PST
C.E. CREDITS
NOV 09, 2021 11:00 AM PST
Date: November 09, 2021 Time: 11:00am (PDT), 02:00pm (EDT) Clinical translation of human pluripotent stem cells (hPSCs) requires advanced strategies that ensure safe and robust long-term gro...
DEC 09, 2021 11:00 AM PST
C.E. CREDITS
DEC 09, 2021 11:00 AM PST
Date: December 09, 2021 Time: 11:00am (PDT), 2:00pm (EDT) The burden of antimicrobial resistance (AMR) has been acknowledged worldwide by leading health institutes. Besides the need for new...
JAN 13, 2022 9:00 AM PST
C.E. CREDITS
JAN 13, 2022 9:00 AM PST
Date: January 13, 2022 Time: 09:00am (PST), 12:00pm (EST) Recently, the Infectious Disease Society of America released guidance on how to approach treatment of infections caused by multidrug...
DEC 14, 2021 6:00 AM PST
C.E. CREDITS
DEC 14, 2021 6:00 AM PST
Date: December 14, 2021 Time: 6:00am (PST), 9:00am (EST) Hepatitis E virus (HEV) is a single-stranded positive-sense RNA virus and is a leading cause of acute viral hepatitis worldwide. The...
Loading Comments...
Show Resources