BugSigDB captures patterns of differential abundance across a broad range of host-associated microbial signatures [0.03%]
BugSigDB收录了与广泛宿主相关微生物特征的差异丰度模式
Ludwig Geistlinger,Chloe Mirzayi,Fatima Zohra et al.
Ludwig Geistlinger et al.
The literature of human and other host-associated microbiome studies is expanding rapidly, but systematic comparisons among published results of host-associated microbiome signatures of differential abundance remain difficult. We present Bu...
Direct measurement of engineered cancer mutations and their transcriptional phenotypes in single cells [0.03%]
单细胞中工程癌症突变及其转录表型的直接测量
Heon Seok Kim,Susan M Grimes,Tianqi Chen et al.
Heon Seok Kim et al.
Genome sequencing studies have identified numerous cancer mutations across a wide spectrum of tumor types, but determining the phenotypic consequence of these mutations remains a challenge. Here, we developed a high-throughput, multiplexed ...
Michael Eisenstein
Michael Eisenstein
Quartet RNA reference materials improve the quality of transcriptomic data through ratio-based profiling [0.03%]
基于比率的定量四联体RNA参考材料可提高转录组数据质量
Ying Yu,Wanwan Hou,Yaqing Liu et al.
Ying Yu et al.
Certified RNA reference materials are indispensable for assessing the reliability of RNA sequencing to detect intrinsically small biological differences in clinical settings, such as molecular subtyping of diseases. As part of the Quartet P...
Integration of spatial and single-cell data across modalities with weakly linked features [0.03%]
跨模式弱链接特征的空间和单细胞数据集成
Shuxiao Chen,Bokai Zhu,Sijia Huang et al.
Shuxiao Chen et al.
Although single-cell and spatial sequencing methods enable simultaneous measurement of more than one biological modality, no technology can capture all modalities within the same cell. For current data integration methods, the feasibility o...
Multi-omics data integration using ratio-based quantitative profiling with Quartet reference materials [0.03%]
基于比率的定量分析与四重参考材料的多组学数据整合方法
Yuanting Zheng,Yaqing Liu,Jingcheng Yang et al.
Yuanting Zheng et al.
Characterization and integration of the genome, epigenome, transcriptome, proteome and metabolome of different datasets is difficult owing to a lack of ground truth. Here we develop and characterize suites of publicly available multi-omics ...