José Fernández Navarro1, Joel Sjöstrand1, Fredrik Salmén1, Joakim Lundeberg1, Patrik L Ståhl1,2. 1. Division of Gene Technology, School of Biotechnology, Royal Institute of Technology (KTH), SE-106 91 Science for Life Laboratory, Solna, Sweden. 2. Department of Cell and Molecular Biology, SE-171 77 Karolinska Institutet, Stockholm, Sweden.
Abstract
MOTIVATION: In recent years we have witnessed an increase in novel RNA-seq based techniques for transcriptomics analysis. Spatial transcriptomics is a novel RNA-seq based technique that allows spatial mapping of transcripts in tissue sections. The spatial resolution adds an extra level of complexity, which requires the development of new tools and algorithms for efficient and accurate data processing. RESULTS: Here we present a pipeline to automatically and efficiently process RNA-seq data obtained from spatial transcriptomics experiments to generate datasets for downstream analysis. AVAILABILITY AND IMPLEMENTATION: The ST Pipeline is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_pipeline. CONTACT: jose.fernandez.navarro@scilifelab.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
MOTIVATION: In recent years we have witnessed an increase in novel RNA-seq based techniques for transcriptomics analysis. Spatial transcriptomics is a novel RNA-seq based technique that allows spatial mapping of transcripts in tissue sections. The spatial resolution adds an extra level of complexity, which requires the development of new tools and algorithms for efficient and accurate data processing. RESULTS: Here we present a pipeline to automatically and efficiently process RNA-seq data obtained from spatial transcriptomics experiments to generate datasets for downstream analysis. AVAILABILITY AND IMPLEMENTATION: The ST Pipeline is open source under a MIT license and it is available at https://github.com/SpatialTranscriptomicsResearch/st_pipeline. CONTACT: jose.fernandez.navarro@scilifelab.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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