detection of RNA molecules in the whole transcriptome including rare transcripts, whereas targeted ExSeq enables a smaller defined gene set to be detected and can be utilized to project cells onto tissue context and also visualize gene regulation. Wang and colleagues [42] developed spatially-resolved...
To characterize the pathogenesis from ESPL to ESCC, we conducted spatial whole-transcriptome profiling, as depicted in Fig.1a. The entire process involves probe hybridization with photocleavable oligo-conjugated antibodies, selection of regions of interest (ROIs), photocleavage, oligos collection, and ge...
We deeply profiled their characteristics, and we found that these subclusters successfully deconvoluted most of the features suggested in bulk transcriptome analysis of pancreatic cancer. Among those subclusters, we identified a novel cancer cell subcluster, Ep_VGLL1, showing in...
Processing CRC spatial transcriptome sequencing data and inferring cellular spatial interactions Spatial transcriptome data analysis was conducted using the R package Seurat. This involved normalizing unique molecular identifier (UMI) counts, scaling the data, and identifying the most variable features using ...
Spatially resolved gene expression, or spatial transcriptomics, is a quantitative readout of either whole transcriptome or targeted gene expression mapped to specific locations in a tissue section, and a proven powerful method to understand cellular composition and activity in the native tissue context....
With the rapid advancements in spatial transcriptome sequencing, multiple tissue slices are now available, enabling the integration and interpretation of spatial cellular landscapes. Herein, we introduce SpaDo, a tool for multi-slice spatial domain analysis, including modules for multi-slice spatial domai...
For this, we generated the spatial transcriptome map of U2OS cells using our home built MERFISH platform (Methods). We used InSTAnT to identify d-colocalized gene pairs from our dataset and compared the top K gene pairs (for varying K) between the Moffitt et al. and our data. As shown ...
[--demultiplexing-multiple-hits-keep-one][--demultiplexing-trim-sequences DEMULTIPLEXING_TRIM_SEQUENCES[DEMULTIPLEXING_TRIM_SEQUENCES...]][--homopolymer-mismatches[INT]][--star-genome-loading[STRING]][--star-sort-mem-limit STAR_SORT_MEM_LIMIT][--disable-barcode][--disable-umi][--transcriptome]...
Spatial transcriptome profiling by MERFISH reveals subcellular RNA compartmentalization and cell cycle-dependent gene expression. Proc Natl Acad Sci U S A. 2019;116(39):19490–9. Article CAS PubMed PubMed Central Google Scholar Eng CL, Lawson M, Zhu Q, Dries R, Koulena N, Takei Y, Yun ...
(DCIS) areas with extensive spatial heterogeneity and distinct subclones that cannot be detected by conventional transcriptome analysis [40,204]. In pancreatic ductal adenocarcinoma (PDAC), deconvolution of spatial transcriptome data identified highly heterogeneous and transitional PDAC subpopulations exhibiting...