De-biasing microbiome sequencing data: bacterial morphology-based correction of extraction bias and correlates of chimera formation
Abstract Introduction Microbiome amplicon sequencing data are distorted by multiple protocol-dependent biases from bacterial DNA extraction, contamination, sequence errors, and chimeras, hindering clinical microbiome applications. In particular, extraction bias is a major confounder in sequencing-ba...
Saved in:
Main Authors: | Luise Rauer, Amedeo De Tomassi, Christian L. Müller, Claudia Hülpüsch, Claudia Traidl-Hoffmann, Matthias Reiger, Avidan U. Neumann |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2025-02-01
|
Series: | Microbiome |
Subjects: | |
Online Access: | https://doi.org/10.1186/s40168-024-01998-4 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Active Inference Model of the Optimism Bias
by: Elizabeth L. Fisher, et al.
Published: (2025-01-01) -
Accounting for racial bias and social determinants of health in a model of hypertension control
by: Yang Hu, et al.
Published: (2025-02-01) -
Correction: Decision-Making, Pro-variance Biases and Mood-Related Traits
by: Wanjun Lin, et al.
Published: (2025-01-01) -
Faking the News: Intentional Guided Variation Reflects Cognitive Biases in Transmission Chains Without Recall
by: Stubbersfield Joseph, et al.
Published: (2018-07-01) -
Effects of Students' Bias on Poetry on Their Performance in Kanyantorogo Sub-County Kanungu District.
by: Mucunguzi, Remgious
Published: (2024)