PMID: 22174281Dec 17, 2011

Artificial functional difference between microbial communities caused by length difference of sequencing reads

Pacific Symposium on Biocomputing
Quan ZhangYuzhen Ye


Homology-based approaches are often used for the annotation of microbial communities, providing functional profiles that are used to characterize and compare the content and the functionality of microbial communities. Metagenomic reads are the starting data for these studies, however considerable differences are observed between the functional profiles-built from sequencing reads produced by different sequencing techniques-for even the same microbial community. Using simulation experiments, we show that such functional differences are likely to be caused by the actual difference in read lengths, and are not the results of a sampling bias of the sequencing techniques. Furthermore, the functional differences derived from different sequencing techniques cannot be fully explained by the read-count bias, i.e. 1) the higher fraction of unannotated shorter reads (i.e., "read length matters"), and 2) the different lengths of proteins in different functional categories. Instead, we show here that specific functional categories are under-annotated, because similarity-search-based functional annotation tools tend to miss more reads from functional categories that contain less conserved genes/proteins. In addition, the accuracy of function...Continue Reading

Related Concepts

Bacterial Proteins
Sequence Determinations
Computational Molecular Biology
Microbiota (plant)
Cell Count

Trending Feeds


Coronaviruses encompass a large family of viruses that cause the common cold as well as more serious diseases, such as the ongoing outbreak of coronavirus disease 2019 (COVID-19; formally known as 2019-nCoV). Coronaviruses can spread from animals to humans; symptoms include fever, cough, shortness of breath, and breathing difficulties; in more severe cases, infection can lead to death. This feed covers recent research on COVID-19.

Synthetic Genetic Array Analysis

Synthetic genetic arrays allow the systematic examination of genetic interactions. Here is the latest research focusing on synthetic genetic arrays and their analyses.

Congenital Hyperinsulinism

Congenital hyperinsulinism is caused by genetic mutations resulting in excess insulin secretion from beta cells of the pancreas. Here is the latest research.

Neural Activity: Imaging

Imaging of neural activity in vivo has developed rapidly recently with the advancement of fluorescence microscopy, including new applications using miniaturized microscopes (miniscopes). This feed follows the progress in this growing field.

Chronic Fatigue Syndrome

Chronic fatigue syndrome is a disease characterized by unexplained disabling fatigue; the pathology of which is incompletely understood. Discover the latest research on chronic fatigue syndrome here.

Epigenetic Memory

Epigenetic memory refers to the heritable genetic changes that are not explained by the DNA sequence. Find the latest research on epigenetic memory here.

Cell Atlas of the Human Eye

Constructing a cell atlas of the human eye will require transcriptomic and histologic analysis over the lifespan. This understanding will aid in the study of development and disease. Find the latest research pertaining to the Cell Atlas of the Human Eye here.

Femoral Neoplasms

Femoral Neoplasms are bone tumors that arise in the femur. Discover the latest research on femoral neoplasms here.

STING Receptor Agonists

Stimulator of IFN genes (STING) are a group of transmembrane proteins that are involved in the induction of type I interferon that is important in the innate immune response. The stimulation of STING has been an active area of research in the treatment of cancer and infectious diseases. Here is the latest research on STING receptor agonists.

Related Papers

Journal of Biomedicine & Biotechnology
Shruthi Prabhakara, Raj Acharya
Applied and Environmental Microbiology
Jeremy A Frank, Søren J Sørensen
Journal of Computational Biology : a Journal of Computational Molecular Cell Biology
Yu-Wei Wu, Yuzhen Ye
© 2021 Meta ULC. All rights reserved