23 papers · ranked by Valyu relevance
Valentine Svensson, Sarah A Teichmann, Oliver Stegle
Technological advances have enabled low-input RNA-sequencing, paving the way for assaying transcriptome variation in spatial contexts, including in tissues. While the generation of spatially resolved transcriptome maps is increasingly feasible, computational methods for analysing the resulting data are not established.…
Lukas M. Weber, Arkajyoti Saha, Abhirup Datta, Kasper D. Hansen + 1 more
'Stephanie C. Hicks'] Feature selection to identify spatially variable genes or other biologically informative genes is a key step during analyses of spatially-resolved transcriptomics data. Here, we propose nnSVG, a scalable approach to identify spatially variable genes based on nearest-neighbor Gaussian processes.…
Phillip B. Nicol, Rong Ma, Rosalind J. Xu, Jeffrey R. Moffitt + 1 more
Spatial transcriptomics enables high-resolution gene expression measurements while preserving the two-dimensional spatial organization of the biological sample. A common objective in spatial transcriptomics data analysis is to identify spatially variable genes within predefined cell types or regions within the tissue.…
Zhijian Li, Zain M.Patel, Dongyuan Song, Sai Nirmayi Yasa + 4 more
Background Spatially resolved transcriptomics offers unprecedented insight by enabling the profiling of gene expression within the intact spatial context of cells, effectively adding a new and essential dimension to data interpretation. To efficiently detect spatial structure of interest, an essential step in analyzing…
Ke Zhang, Wanwan Feng, Peng Wang
Single-cell gene expression data with positional information are critical to dissect mechanisms and architectures of multicellular organisms, but the potential is limited by current data analysis strategies. Here, we present scGCO (single-cell graph cuts optimization), a method based on fast optimization of Markov…
Guoxin Cai, Yichang Chen, Xun Gu, Zhan Zhou
Spatial transcriptomics enables the depiction of in situ gene expression and could further be applied to infer the mechanism of cell functions. In this study, we present Spanve (Spatial Neighborhood Variably Expressed Genes), a statistic based approach to detect space-dependent expressed genes from spatial…
Shan Yu, Wei Vivian Li
Spatially resolved transcriptomics technologies have opened new avenues for understanding gene expression heterogeneity in spatial contexts. However, existing methods for identifying spatially variable genes often focus solely on statistical significance, limiting their ability to capture continuous expression patterns…
Zhijian Li, Zain M.Patel, Dongyuan Song, Guanao Yan + 2 more
Spatially resolved transcriptomics offers unprecedented insight by enabling the profiling of gene expression within the intact spatial context of cells, effectively adding a new and essential dimension to data interpretation. To efficiently detect spatial structure of interest, an essential step in analyzing such data…
Peiying Cai, Mark D Robinson, Simone Tiberi, Anthony Mathelier
Spatially resolved transcriptomics (SRT) technologies allow the spatial characterization of gene expression profiles in a tissue. SRT techniques can be broadly grouped into two categories: sequencing-based methods (e.g. Slide-seq (), Slide-seq-V2 (), 10X Genomics Visium, spatial transcriptomics (), high definition…
Sikta Das Adhikari, Jiaxin Yang, Jianrong Wang, Yuehua Cui
With the emergence of advanced spatial transcriptomic technologies, there has been a surge in research papers dedicated to analyzing spatial transcriptomics data, resulting in significant contributions to our understanding of biology. The initial stage of downstream analysis of spatial transcriptomic data has centered…
Haohao Su, Yuesong Wu, Bin Chen, Yuehua Cui
One of the major challenges in spatial transcriptomics is to detect spatially variable genes (SVGs), whose expression patterns are non-random across tissue locations. Many SVGs correlate with cell type compositions, introducing the concept of cell type-specific SVGs (ctSVGs). Existing ctSVG detection methods treat cell…
Yijun Li, Stefan Stanojevic, Bing He, Zheng Jing + 3 more
Spatial transcriptomics has allowed researchers to analyze transcriptome data in its tissue sample’s spatial context. Various methods have been developed for detecting spatially variable genes (SV genes), whose gene expression over the tissue space shows strong spatial autocorrelation. Such genes are often used to…
Mingcong Wu, Yang Li, Shuangge Ma, Mengyun Wu
Bayesian regularization approach Authors: ['Mingcong Wu' 'Yang Li' 'Shuangge Ma' 'Mengyun Wu'] Identifying genes that display spatial patterns is critical to investigating expression interactions within a spatial context and further dissecting biological understanding of complex mechanistic functionality. Despite the…
Yuesong Wu, Haohao Su, Nina Steele, Yuying Xie + 1 more
Identifying spatially variable genes (SVGs) has been an essential task in spatial transcriptomics. In addition to SVGs detection, there are genes exhibiting expression patterns that are associated with cellular developmental stages or lineage fates across a tissue section. Identifying such genes could provide novel…
Meng Zhou, Shuangge Ma, Mengyun Wu
Spatial transcriptomics has revolutionized tissue analysis by simultaneously mapping gene expression, spatial topography, and histological context across consecutive tissue sections, enabling systematic investigation of spatial heterogeneity. The detection of spatially variable (SV) genes, which are molecular…
Haohao Su, Yuesong Wu, Bin Chen, Yuehua Cui
A significant challenge in analyzing spatial transcriptomics data is the effective and efficient detection of spatially variable genes (SVGs), whose expression exhibits non-random spatial patterns in tissues. Many SVGs show spatial variation in expression that is highly correlated with cell type categories or…
Natalie Charitakis, Mirana Ramialison, Hieu T. Nim
The technology to generate Spatially Resolved Transcriptomics (SRT) data is rapidly being improved and applied to investigate a variety of biological tissues. The ability to interrogate how spatially localised gene expression can lend new insight to different tissue development is critical, but the appropriate tools to…
Xi Jiang, Qiwei Li, Guanghua Xiao
A recent technology breakthrough in spatial molecular profiling has enabled the comprehensive molecular characterizations of single cells while preserving spatial information. It provides new opportunities to delineate how cells from different origins form tissues with distinctive structures and functions. One…
Guanao Yan, Shuo Harper Hua, Jingyi Jessica Li
In the analysis of spatially resolved transcriptomics data, detecting spatially variable genes (SVGs) is crucial. Numerous computational methods exist, but varying SVG definitions and methodologies lead to incomparable results. We review 31 state-of-the-art methods, categorizing SVGs into three types: overall…
Benjamin Zoller, Shawn C. Little, Thomas Gregor
In early development, regulation of transcription results in precisely positioned and highly reproducible expression patterns that specify cellular identities. How transcription, a fundamentally noisy molecular process, is regulated to achieve reliable embryonic patterning remains unclear. In particular, it is unknown…
Hamid Reza Razzaghian, Lars A. Forsberg, Kancherla Reddy Prakash, Szymon Przerada + 14 more
'Szymon Przerada' 'Hanna Paprocka' 'Anna Zywicka' 'Maxwell P. Westerman' 'Nancy L. Pedersen' "Terrance P. O'Hanlon" 'Lisa G. Rider' 'Frederick W. Miller' 'Ewa Srutek' 'Michal Jankowski' 'Wojciech Zegarski' 'Arkadiusz Piotrowski' 'Devin Absher' 'Jan P. Dumanski' 'Tatjana Adamovic'] Although historically considered as…
Zhiwen Pan, Jan Dellith, Lothar Wondraczek
Understanding the multivariate origin of physical properties is particularly complex for polyionic glasses. As a concept, the term genome has been used to describe the entirety of structure-property relations in solid materials, based on functional genes acting as descriptors for a particular property, for example, for…
Hao-Che Peng, Shrijaa Mohan, Muhammad T. Huq, Julie A. Bull + 7 more
Experimental methods to determine transition temperatures for individual base pair melting events in DNA duplexes are lacking despite intense interest in these thermodynamic parameters. Here, we determine the dimensions of the thymine (T) C2=O stretching vibration when it is within the DNA duplex via iso-topic…