SPIRAL: integrating and aligning spatially resolved transcriptomics data across different experiments, conditions, and technologies [0.03%]
SPIRAL：整合和对齐不同实验、条件和技术的空间分辨转录组数据
Tiantian Guo,Zhiyuan Yuan,Yan Pan et al.
Tiantian Guo et al.
Properly integrating spatially resolved transcriptomics (SRT) generated from different batches into a unified gene-spatial coordinate system could enable the construction of a comprehensive spatial transcriptome atlas. Here, we propose SPIR...
Measuring cell-to-cell expression variability in single-cell RNA-sequencing data: a comparative analysis and applications to B cell aging [0.03%]
单细胞RNA测序数据中细胞间表达差异的测量：比较分析及其在B淋巴细胞衰老研究中的应用
Huiwen Zheng,Jan Vijg,Atefeh Taherian Fard et al.
Huiwen Zheng et al.
Background: Single-cell RNA-sequencing (scRNA-seq) technologies enable the capture of gene expression heterogeneity and consequently facilitate the study of cell-to-cell variability at the cell type level. Although differ...
DIVE: a reference-free statistical approach to diversity-generating and mobile genetic element discovery [0.03%]
一种无参考基因组的统计方法DIVE用于多样性和可移动遗传元件的发现
Jordi Abante,Peter L Wang,Julia Salzman
Jordi Abante
Diversity-generating and mobile genetic elements are key to microbial and viral evolution and can result in evolutionary leaps. State-of-the-art algorithms to detect these elements have limitations. Here, we introduce DIVE, a new reference-...
GoM DE: interpreting structure in sequence count data with differential expression analysis allowing for grades of membership [0.03%]
GO मैत्रिक रेखांकन के साथ अनुक्रम गिनतारा डेटा की व्याख्या: सदस्यता के तरह Differential Expression Analysis
Peter Carbonetto,Kaixuan Luo,Abhishek Sarkar et al.
Peter Carbonetto et al.
Parts-based representations, such as non-negative matrix factorization and topic modeling, have been used to identify structure from single-cell sequencing data sets, in particular structure that is not as well captured by clustering or oth...
Dual spatially resolved transcriptomics for human host-pathogen colocalization studies in FFPE tissue sections [0.03%]
用于福尔马林固定石蜡包埋组织切片人宿主-病原体共定位研究的双空间解析转录组学
Hailey Sounart,Enikő Lázár,Yuvarani Masarapu et al.
Hailey Sounart et al.
Technologies to study localized host-pathogen interactions are urgently needed. Here, we present a spatial transcriptomics approach to simultaneously capture host and pathogen transcriptome-wide spatial gene expression information from huma...
GeneSegNet: a deep learning framework for cell segmentation by integrating gene expression and imaging [0.03%]
通过整合基因表达和图像的细胞分割深度学习框架GeneSegNet
Yuxing Wang,Wenguan Wang,Dongfang Liu et al.
Yuxing Wang et al.
When analyzing data from in situ RNA detection technologies, cell segmentation is an essential step in identifying cell boundaries, assigning RNA reads to cells, and studying the gene expression and morphological features of cells. We devel...
Single-cell metabolic profiling reveals subgroups of primary human hepatocytes with heterogeneous responses to drug challenge [0.03%]
单细胞代谢谱分析揭示初级人肝细胞亚群对药物刺激的异质性反应
Eva Sanchez-Quant,Maria Lucia Richter,Maria Colomé-Tatché et al.
Eva Sanchez-Quant et al.
Background: Xenobiotics are primarily metabolized by hepatocytes in the liver, and primary human hepatocytes are the gold standard model for the assessment of drug efficacy, safety, and toxicity in the early phases of dru...
The evolution and mutational robustness of chromatin accessibility in Drosophila [0.03%]
果蝇染色质可及性的进化及突变稳健性
Samuel Khodursky,Eric B Zheng,Nicolas Svetec et al.
Samuel Khodursky et al.
Background: The evolution of genomic regulatory regions plays a critical role in shaping the diversity of life. While this process is primarily sequence-dependent, the enormous complexity of biological systems complicates...
Data-driven identification of total RNA expression genes for estimation of RNA abundance in heterogeneous cell types highlighted in brain tissue [0.03%]
基于数据驱动的总RNA表达基因鉴定以估计脑组织中异质细胞类型的RNA丰度
Louise A Huuki-Myers,Kelsey D Montgomery,Sang Ho Kwon et al.
Louise A Huuki-Myers et al.
We define and identify a new class of control genes for next-generation sequencing called total RNA expression genes (TREGs), which correlate with total RNA abundance in cell types of different sizes and transcriptional activity. We provide...
MalariaSED: a deep learning framework to decipher the regulatory contributions of noncoding variants in malaria parasites [0.03%]
疟疾基因调控区功能解读的深度学习框架疟疾SED：解码疟原虫非编码变异的调控贡献
Chengqi Wang,Yibo Dong,Chang Li et al.
Chengqi Wang et al.
Malaria remains one of the deadliest infectious diseases. Transcriptional regulation effects of noncoding variants in this unusual genome of malaria parasites remain elusive. We developed a sequence-based, ab initio deep learning framework,...