Cargando…
Strain level microbial detection and quantification with applications to single cell metagenomics
Computational identification and quantification of distinct microbes from high throughput sequencing data is crucial for our understanding of human health. Existing methods either use accurate but computationally expensive alignment-based approaches or less accurate but computationally fast alignmen...
Autores principales: | Zhu, Kaiyuan, Schäffer, Alejandro A., Robinson, Welles, Xu, Junyan, Ruppin, Eytan, Ergun, A. Funda, Ye, Yuzhen, Sahinalp, S. Cenk |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9616933/ https://www.ncbi.nlm.nih.gov/pubmed/36307411 http://dx.doi.org/10.1038/s41467-022-33869-7 |
Ejemplares similares
-
Big data in basic and translational cancer research
por: Jiang, Peng, et al.
Publicado: (2022) -
Probabilistic Inference of Biochemical Reactions in Microbial Communities from Metagenomic Sequences
por: Jiao, Dazhi, et al.
Publicado: (2013) -
Altered gene expression in excitatory neurons is associated with Alzheimer's disease and its higher incidence in women
por: Garcia, A. Xavier, et al.
Publicado: (2023) -
ConStrains identifies microbial strains in metagenomic datasets
por: Luo, Chengwei, et al.
Publicado: (2015) -
The landscape of receptor-mediated precision cancer combination therapy via a single-cell perspective
por: Ahmadi, Saba, et al.
Publicado: (2022)