2026-10-13T18:18:38Z https://api.figshare.com/v2/oai

oai:figshare.com:article/33365094 2026-09-22T09:06:18Z category_24208 category_24184 portal_886 item_type_3 month_year_09_2026

Supplementary data for thesis "Methodologies in Resolving Spatial Transcriptomic Signals and Applications" Kun Ma (13127868) Bioinformatics and computational biology not elsewhere classified Bioinformatic methods development Mitochondrial SNPs Spatial Transcriptomics Data Correction <p dir="ltr">Chapter 3 titled "Spatially Resolved Analysis of Human Ovarian Tissue Responses to Cryopreservation" (in revision)</p><ul><li>This study constructs a spatially resolved molecular map of human ovarian tissue using high-resolution Stereo-seq to characterize how the two principal cryopreservation strategies, slow-freezing and vitrification, affect different functional regions of the organ. </li><li>The code provided here illustrate the analysis pipeline.</li></ul><p dir="ltr"><br></p><p dir="ltr">Chapter 4 titled "Mitochondrial Single Nucleotide Polymorphisms Resolve Clonal Architecture and Progressive Lineage Expansion in Colorectal Cancer" (in preparation)</p><ul><li>This study asks whether mitochondrial single-nucleotide polymorphisms captured by single-cell ATAC sequencing can serve as endogenous lineage barcodes for reconstructing clonal expansion in colorectal cancer. We developed a reproducible computational workflow integrating mitochondrial variant calling, clone identification, cell-type annotation, chromatin-accessibility analysis, and copy-number inference. </li></ul><p dir="ltr">Chapter 5 titled "CLEAR-ST: Physics-informed Probabilistic Decontamination of Spatial Transcriptomics by Modeling mRNA Lateral Diffusion" (submitted)</p><ul><li>This study addresses lateral mRNA diffusion in sequencing-based spatial transcriptomics, where transcripts may spread during tissue permeabilization and contaminate neighbouring capture locations. We developed CLEAR-ST, a physics-informed probabilistic framework that couples a denoising autoencoder with a graph-Laplacian forward diffusion model, explicitly representing the experimental sequence in which transcripts spread from their true locations before capture. </li></ul><p dir="ltr"><br></p> 2026-09-22T09:06:18Z Dataset Dataset 10.25442/hku.33365094.v1 https://figshare.com/articles/dataset/Supplementary_data_for_thesis_Methodologies_in_Resolving_Spatial_Transcriptomic_Signals_and_Applications_/33365094 CC BY-NC 4.0