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stereo seq transcriptomics t kit v1 3  (Complete Genomics Inc)


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    Structured Review

    Complete Genomics Inc stereo seq transcriptomics t kit v1 3
    Stereo Seq Transcriptomics T Kit V1 3, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 472 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/stereo-seq+transcriptomics+t+kit/Stereo-seq+Transcriptomics+Set+for+FFPE/pmc13134484-1369-0-6
    Average 99 stars, based on 472 article reviews
    stereo seq transcriptomics t kit v1 3 - by Bioz Stars, 2026-10
    99/100 stars

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    Related Articles

    Transcriptomics:

    Article Title: A spatial code governs olfactory receptor choice and aligns sensory maps in the nose and brain
    Article Snippet: MERSCOPE Cell Boundary Staining Kit , Vizgen , Cat# 10400118. .. Stereo-seq Transcriptomics T kit v1.3 , STOmics , Cat# 211KT13114-CG. .. Stereo-seq 16 Barcode Library Preparation Kit , STOmics , Cat # 111KL160-CG.

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection
    Article Snippet: All libraries were sequenced using NovaSeq 6000 (Illumina). .. One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI). ..

    Article Title: Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Stereo-seq Permeabilization kit BGI STomics Catalog #111KP118 Stereo-seq Chip P (1cm*1cm) BGI STomics Catalog #111CP118 Stereo-seq Transcriptomics T kit BGI STomics Catalog #111KT114 Stereo-seq Chip T (1cm*1cm) BGI STomics Catalog #110CT114 Stereo-seq Library Prep kit BGI STomics Catalog #111KL114 2100 Bioanalyzer – High sensitivity DNA analysis Agilent Technologies Catalog #G2939BA QubitTM dsDNA Quantification Assay Kits Thermo Fisher Scientific Catalog #Q32851 QubitTM ssDNA Assay Kit Thermo Fisher Scientific Catalog #Q10212 innuPREP mini RNA kit Analytik Jena Catalog # AJ 845-KS-2040250 Deposited data Nova-ST Data (Mouse Brain) This study GEO: GSE256318 Stereo-seq (Mouse Brain) This study GEO: GSE256319 Stereo-seq (Mouse Brain) Chen et al. (2022)8 CNGB: CNS0390078 Stereo-seq (Mouse Brain) You et al. (2023)20 https://www.genographix.com Slideseq-v2 (Mouse Hippocampus) Stickels et al. (2021)6 https://singlecell.broadinstitute.org/ single_cell/study/SCP815 10X Genomics and SMART-seq2 (Mouse Brain) Yao et al. (Cell)19 https://portal.brain-map.org/ atlases-and-data/rnaseq/mousewhole-cortex-and-hippocampus-10x Experimental models: Organisms/strains Six to eight weeks old mice (C57BL/6J) JAX MGI:3028467 Oligonucleotides HDMI-DraI32 IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGAGA TTCTTTCCCTACACGACGCTCTTCC GATCTNNVNNVNNVNNVNNVNNNN NTCTTGTGACTACAGCACCCTCGA CTCTCGCTTTTTTTTTTTTTTTTTTTT TTTTTTTTTTAAAGACTTTCACCAGT CCATGATGTGTAGATCTCGGTGG TCGCCGTATCATT Read1-DraI32 IDT Technologies (PAGE purification) ATCATGGACTGGTGAAAGTCTTTA AAAAAAAAAAAAAAAAAAAAAAAA AAAAAGCGAGAGTCGAGGGTG CTGTAGTCACAAGA RPE_Randomer IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCCGA TCTNNNGGNNNB RPEPCR_Fwd IDT Technologies (Standard desalted) TCTTTCCCTACACGACGC*T*C RPEPCR_Rev IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCC*G*A P5_WTA_TCAAGCGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACTCAAGCGAACACTC TTTCCCTACACGACGCTC TTCCGATCT P5_WTA_ GTAGCTGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACGTAGCTGAACACTCTTT CCCTACACGACGCTCTTCCGATCT P5_WTA_ CCAACCAA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACCCAACCAAACACTCTT TCCCTACACGACGCTCTTCCGATCT P5_WTA_ AACGTTGG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGA GATCTACACAACGTTGGACAC TCTTTCCCTACACGACGC TCTTCCGATCT (Continued on next page) e2 Cell Reports Methods 4, 100831, August 19, 2024 .. REAGENT or RESOURCE SOURCE IDENTIFIER P5_WTA_ ACCAATCG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACACCAATCGACACT CTTTCCCTACACGACGCT CTTCCGATCT P7_WTA_ CCGCGGTT IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATCCGCGGTTGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ TTATAACC IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATTTATAACCGTGACTGGAGT TCAGACGTGTGCTCTTCC*G*A P7_WTA_ GGACTTGG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATGGACTTGGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ AAGTCCAA IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATAAGTCCAAGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ ATCCACTG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATATCCACTGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A Software and algorithms Nova-ST Analysis Pipeline/Notebooks This study https://github.com/aertslab/Nova-ST https://doi.org/10.5281/ zenodo.12608945 Carbide Create https://carbide3d.com/ N/A Carbide Motion https://carbide3d.com/ N/A bcl2fastq2 (v2.20.0) Illumina https://emea.support.illumina.com/ downloads/bcl2fastq-conversionsoftware-v2-20.html RRID:SCR_015058 Sequence Analysis Viewer (v3.0) Illumina https://emea.support.illumina.com/ sequencing/sequencing_software/ sequencing_analysis_viewer_sav.html Python (v3.8.10) Python Software Foundation https://www.python.org/ RRID:SCR_008394 OpenCV (v4.2.0) OpenCV Team https://opencv.org/RRID:SCR_015526 STARsolo (2.7.10b) Dobin et al. (2013)24 https://github.com/alexdobin/STAR RRID:SCR_021542 SAW (v6.1) BGI https://github.com/STOmics/SAW RRID:SCR_025001 Stereopy (v0.6.0) BGI https://github.com/STOmics/Stereopy Scanpy (v1.9.1) Wolf et al. (2018)25 https://github.com/scverse/scanpy RRID:SCR_018139 Fiji (v1.54f) Schindelin et al. (2019)26 https://github.com/fiji/fiji RRID:SCR_002285 Cell2location (v0.1.3) Kleshchevnikov et al. (2022)18 https://github.com/BayraktarLab/ cell2location/RRID:SCR_024859 SCope (v.1.8.2) Davie et al. (2018)17 https://github.com/aertslab/SCope Napari (v.0.4.18) N/A https://github.com/napari/napari RRID: SCR_022765

    Article Title: Clonal dynamics and Stereo-seq resolve origin and phenotypic plasticity of adenosquamous carcinoma
    Article Snippet: RNA released from the permeabilized tissue and captured by the DNB was reversely transcribed overnight at 42 °C with RT Mix (Stereo-seq Transcriptomics T kit, STOmics). .. After reverse transcription, tissue sections were washed with PR rinse buffer (Stereo-seq Transcriptomics T kit, STOmics) and digested with Tissue Removal buffer (Stereo-seq Transcriptomics T kit, STOmics) at 37 °C for 30 min. cDNA-containing chips were then washed with PR rinse buffer. ..

    other:

    Article Title: Protocol for preparing mammalian skin samples encompassing hair follicles for spatial transcriptomics
    Article Snippet: Stereo-seq Transcriptomics T Kit , STOmics/BGI , 111KT114.

    Article Title: Identification of signaling pathways that specify a subset of migrating enteric neural crest cells at the wavefront in mouse embryos.
    Article Snippet: Article Identification of signaling pathways that specify a subset of migrating enteric neural crest cells at the wavefront in mouse embryos

    Polyacrylamide Gel Electrophoresis:

    Article Title: Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Stereo-seq Permeabilization kit BGI STomics Catalog #111KP118 Stereo-seq Chip P (1cm*1cm) BGI STomics Catalog #111CP118 Stereo-seq Transcriptomics T kit BGI STomics Catalog #111KT114 Stereo-seq Chip T (1cm*1cm) BGI STomics Catalog #110CT114 Stereo-seq Library Prep kit BGI STomics Catalog #111KL114 2100 Bioanalyzer – High sensitivity DNA analysis Agilent Technologies Catalog #G2939BA QubitTM dsDNA Quantification Assay Kits Thermo Fisher Scientific Catalog #Q32851 QubitTM ssDNA Assay Kit Thermo Fisher Scientific Catalog #Q10212 innuPREP mini RNA kit Analytik Jena Catalog # AJ 845-KS-2040250 Deposited data Nova-ST Data (Mouse Brain) This study GEO: GSE256318 Stereo-seq (Mouse Brain) This study GEO: GSE256319 Stereo-seq (Mouse Brain) Chen et al. (2022)8 CNGB: CNS0390078 Stereo-seq (Mouse Brain) You et al. (2023)20 https://www.genographix.com Slideseq-v2 (Mouse Hippocampus) Stickels et al. (2021)6 https://singlecell.broadinstitute.org/ single_cell/study/SCP815 10X Genomics and SMART-seq2 (Mouse Brain) Yao et al. (Cell)19 https://portal.brain-map.org/ atlases-and-data/rnaseq/mousewhole-cortex-and-hippocampus-10x Experimental models: Organisms/strains Six to eight weeks old mice (C57BL/6J) JAX MGI:3028467 Oligonucleotides HDMI-DraI32 IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGAGA TTCTTTCCCTACACGACGCTCTTCC GATCTNNVNNVNNVNNVNNVNNNN NTCTTGTGACTACAGCACCCTCGA CTCTCGCTTTTTTTTTTTTTTTTTTTT TTTTTTTTTTAAAGACTTTCACCAGT CCATGATGTGTAGATCTCGGTGG TCGCCGTATCATT Read1-DraI32 IDT Technologies (PAGE purification) ATCATGGACTGGTGAAAGTCTTTA AAAAAAAAAAAAAAAAAAAAAAAA AAAAAGCGAGAGTCGAGGGTG CTGTAGTCACAAGA RPE_Randomer IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCCGA TCTNNNGGNNNB RPEPCR_Fwd IDT Technologies (Standard desalted) TCTTTCCCTACACGACGC*T*C RPEPCR_Rev IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCC*G*A P5_WTA_TCAAGCGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACTCAAGCGAACACTC TTTCCCTACACGACGCTC TTCCGATCT P5_WTA_ GTAGCTGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACGTAGCTGAACACTCTTT CCCTACACGACGCTCTTCCGATCT P5_WTA_ CCAACCAA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACCCAACCAAACACTCTT TCCCTACACGACGCTCTTCCGATCT P5_WTA_ AACGTTGG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGA GATCTACACAACGTTGGACAC TCTTTCCCTACACGACGC TCTTCCGATCT (Continued on next page) e2 Cell Reports Methods 4, 100831, August 19, 2024 .. REAGENT or RESOURCE SOURCE IDENTIFIER P5_WTA_ ACCAATCG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACACCAATCGACACT CTTTCCCTACACGACGCT CTTCCGATCT P7_WTA_ CCGCGGTT IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATCCGCGGTTGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ TTATAACC IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATTTATAACCGTGACTGGAGT TCAGACGTGTGCTCTTCC*G*A P7_WTA_ GGACTTGG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATGGACTTGGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ AAGTCCAA IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATAAGTCCAAGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ ATCCACTG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATATCCACTGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A Software and algorithms Nova-ST Analysis Pipeline/Notebooks This study https://github.com/aertslab/Nova-ST https://doi.org/10.5281/ zenodo.12608945 Carbide Create https://carbide3d.com/ N/A Carbide Motion https://carbide3d.com/ N/A bcl2fastq2 (v2.20.0) Illumina https://emea.support.illumina.com/ downloads/bcl2fastq-conversionsoftware-v2-20.html RRID:SCR_015058 Sequence Analysis Viewer (v3.0) Illumina https://emea.support.illumina.com/ sequencing/sequencing_software/ sequencing_analysis_viewer_sav.html Python (v3.8.10) Python Software Foundation https://www.python.org/ RRID:SCR_008394 OpenCV (v4.2.0) OpenCV Team https://opencv.org/RRID:SCR_015526 STARsolo (2.7.10b) Dobin et al. (2013)24 https://github.com/alexdobin/STAR RRID:SCR_021542 SAW (v6.1) BGI https://github.com/STOmics/SAW RRID:SCR_025001 Stereopy (v0.6.0) BGI https://github.com/STOmics/Stereopy Scanpy (v1.9.1) Wolf et al. (2018)25 https://github.com/scverse/scanpy RRID:SCR_018139 Fiji (v1.54f) Schindelin et al. (2019)26 https://github.com/fiji/fiji RRID:SCR_002285 Cell2location (v0.1.3) Kleshchevnikov et al. (2022)18 https://github.com/BayraktarLab/ cell2location/RRID:SCR_024859 SCope (v.1.8.2) Davie et al. (2018)17 https://github.com/aertslab/SCope Napari (v.0.4.18) N/A https://github.com/napari/napari RRID: SCR_022765

    Purification:

    Article Title: Nova-ST: Nano-patterned ultra-dense platform for spatial transcriptomics.
    Article Snippet: .. REAGENT or RESOURCE SOURCE IDENTIFIER Stereo-seq Permeabilization kit BGI STomics Catalog #111KP118 Stereo-seq Chip P (1cm*1cm) BGI STomics Catalog #111CP118 Stereo-seq Transcriptomics T kit BGI STomics Catalog #111KT114 Stereo-seq Chip T (1cm*1cm) BGI STomics Catalog #110CT114 Stereo-seq Library Prep kit BGI STomics Catalog #111KL114 2100 Bioanalyzer – High sensitivity DNA analysis Agilent Technologies Catalog #G2939BA QubitTM dsDNA Quantification Assay Kits Thermo Fisher Scientific Catalog #Q32851 QubitTM ssDNA Assay Kit Thermo Fisher Scientific Catalog #Q10212 innuPREP mini RNA kit Analytik Jena Catalog # AJ 845-KS-2040250 Deposited data Nova-ST Data (Mouse Brain) This study GEO: GSE256318 Stereo-seq (Mouse Brain) This study GEO: GSE256319 Stereo-seq (Mouse Brain) Chen et al. (2022)8 CNGB: CNS0390078 Stereo-seq (Mouse Brain) You et al. (2023)20 https://www.genographix.com Slideseq-v2 (Mouse Hippocampus) Stickels et al. (2021)6 https://singlecell.broadinstitute.org/ single_cell/study/SCP815 10X Genomics and SMART-seq2 (Mouse Brain) Yao et al. (Cell)19 https://portal.brain-map.org/ atlases-and-data/rnaseq/mousewhole-cortex-and-hippocampus-10x Experimental models: Organisms/strains Six to eight weeks old mice (C57BL/6J) JAX MGI:3028467 Oligonucleotides HDMI-DraI32 IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGAGA TTCTTTCCCTACACGACGCTCTTCC GATCTNNVNNVNNVNNVNNVNNNN NTCTTGTGACTACAGCACCCTCGA CTCTCGCTTTTTTTTTTTTTTTTTTTT TTTTTTTTTTAAAGACTTTCACCAGT CCATGATGTGTAGATCTCGGTGG TCGCCGTATCATT Read1-DraI32 IDT Technologies (PAGE purification) ATCATGGACTGGTGAAAGTCTTTA AAAAAAAAAAAAAAAAAAAAAAAA AAAAAGCGAGAGTCGAGGGTG CTGTAGTCACAAGA RPE_Randomer IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCCGA TCTNNNGGNNNB RPEPCR_Fwd IDT Technologies (Standard desalted) TCTTTCCCTACACGACGC*T*C RPEPCR_Rev IDT Technologies (Standard desalted) TCAGACGTGTGCTCTTCC*G*A P5_WTA_TCAAGCGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACTCAAGCGAACACTC TTTCCCTACACGACGCTC TTCCGATCT P5_WTA_ GTAGCTGA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACGTAGCTGAACACTCTTT CCCTACACGACGCTCTTCCGATCT P5_WTA_ CCAACCAA IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAGA TCTACACCCAACCAAACACTCTT TCCCTACACGACGCTCTTCCGATCT P5_WTA_ AACGTTGG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGA GATCTACACAACGTTGGACAC TCTTTCCCTACACGACGC TCTTCCGATCT (Continued on next page) e2 Cell Reports Methods 4, 100831, August 19, 2024 .. REAGENT or RESOURCE SOURCE IDENTIFIER P5_WTA_ ACCAATCG IDT Technologies (Standard desalted) AATGATACGGCGACCACCGAG ATCTACACACCAATCGACACT CTTTCCCTACACGACGCT CTTCCGATCT P7_WTA_ CCGCGGTT IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATCCGCGGTTGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ TTATAACC IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATTTATAACCGTGACTGGAGT TCAGACGTGTGCTCTTCC*G*A P7_WTA_ GGACTTGG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATGGACTTGGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ AAGTCCAA IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATAAGTCCAAGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A P7_WTA_ ATCCACTG IDT Technologies (Standard desalted) CAAGCAGAAGACGGCATACGA GATATCCACTGGTGACTGGAG TTCAGACGTGTGCTCTTCC*G*A Software and algorithms Nova-ST Analysis Pipeline/Notebooks This study https://github.com/aertslab/Nova-ST https://doi.org/10.5281/ zenodo.12608945 Carbide Create https://carbide3d.com/ N/A Carbide Motion https://carbide3d.com/ N/A bcl2fastq2 (v2.20.0) Illumina https://emea.support.illumina.com/ downloads/bcl2fastq-conversionsoftware-v2-20.html RRID:SCR_015058 Sequence Analysis Viewer (v3.0) Illumina https://emea.support.illumina.com/ sequencing/sequencing_software/ sequencing_analysis_viewer_sav.html Python (v3.8.10) Python Software Foundation https://www.python.org/ RRID:SCR_008394 OpenCV (v4.2.0) OpenCV Team https://opencv.org/RRID:SCR_015526 STARsolo (2.7.10b) Dobin et al. (2013)24 https://github.com/alexdobin/STAR RRID:SCR_021542 SAW (v6.1) BGI https://github.com/STOmics/SAW RRID:SCR_025001 Stereopy (v0.6.0) BGI https://github.com/STOmics/Stereopy Scanpy (v1.9.1) Wolf et al. (2018)25 https://github.com/scverse/scanpy RRID:SCR_018139 Fiji (v1.54f) Schindelin et al. (2019)26 https://github.com/fiji/fiji RRID:SCR_002285 Cell2location (v0.1.3) Kleshchevnikov et al. (2022)18 https://github.com/BayraktarLab/ cell2location/RRID:SCR_024859 SCope (v.1.8.2) Davie et al. (2018)17 https://github.com/aertslab/SCope Napari (v.0.4.18) N/A https://github.com/napari/napari RRID: SCR_022765

    Reverse Transcription:

    Article Title: Clonal dynamics and Stereo-seq resolve origin and phenotypic plasticity of adenosquamous carcinoma
    Article Snippet: RNA released from the permeabilized tissue and captured by the DNB was reversely transcribed overnight at 42 °C with RT Mix (Stereo-seq Transcriptomics T kit, STOmics). .. After reverse transcription, tissue sections were washed with PR rinse buffer (Stereo-seq Transcriptomics T kit, STOmics) and digested with Tissue Removal buffer (Stereo-seq Transcriptomics T kit, STOmics) at 37 °C for 30 min. cDNA-containing chips were then washed with PR rinse buffer. ..



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    Complete Genomics Inc 111cp118 stereo seq transcriptomics t kit bgi stomics
    a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and <t>STOmics</t> Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.
    111cp118 Stereo Seq Transcriptomics T Kit Bgi Stomics, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/stereo-seq+transcriptomics+t+kit/Stereo-seq+Transcriptomics+Set+for+FFPE/pm39111312-188-19-24
    Average 99 stars, based on 1 article reviews
    111cp118 stereo seq transcriptomics t kit bgi stomics - by Bioz Stars, 2026-10
    99/100 stars
      Buy from Supplier

    99
    Complete Genomics Inc stereo seq transcriptomics t kit stomics
    a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and <t>STOmics</t> Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.
    Stereo Seq Transcriptomics T Kit Stomics, supplied by Complete Genomics Inc, used in various techniques. Bioz Stars score: 99/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/stereo-seq+transcriptomics+t+kit/Stereo-seq+Transcriptomics+Set+for+FFPE/pm38636517-771-166-170
    Average 99 stars, based on 1 article reviews
    stereo seq transcriptomics t kit stomics - by Bioz Stars, 2026-10
    99/100 stars
      Buy from Supplier

    Image Search Results


    a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and STOmics Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and STOmics Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Slice Preparation, Staining, Derivative Assay, Expressing, Marker

    a , Illustration of the five different brain bregma used for STOmics Stereo-seq in accordance with the Visium data set. Representative H&E stains are shown for each Bregma. Since Stereo-seq does not support H&E stains directly from the sequenced tissue slices, an adjacent (directly before or after) tissue slice was prepared and stained before running the spatial transcriptomics experiments. b , From left to right and per brain bregma (top to bottom): integrated UMAP representation of all cleaned Stereo-seq spot clusters using the bin200 resolution, pie charts and per replicate spatial projections of the final annotated spot clusters. Cluster names and colors were assigned in accordance with the Visium data set (cf. Methods). c , Distribution of four main quality control features across the cleaned spots and per Stereo-seq brain replicate at bin200 resolution.

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Illustration of the five different brain bregma used for STOmics Stereo-seq in accordance with the Visium data set. Representative H&E stains are shown for each Bregma. Since Stereo-seq does not support H&E stains directly from the sequenced tissue slices, an adjacent (directly before or after) tissue slice was prepared and stained before running the spatial transcriptomics experiments. b , From left to right and per brain bregma (top to bottom): integrated UMAP representation of all cleaned Stereo-seq spot clusters using the bin200 resolution, pie charts and per replicate spatial projections of the final annotated spot clusters. Cluster names and colors were assigned in accordance with the Visium data set (cf. Methods). c , Distribution of four main quality control features across the cleaned spots and per Stereo-seq brain replicate at bin200 resolution.

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Staining, Control

    a , Scatter plot showing the average log2-scaled fold-change between aging and infection for all brain DEGs matched and colored by spot cluster. b , Normalized spatial expression of C4b in four representative brain samples (Bregma: - 2.06), two from aging (top left: young, top right: old) and infection (bottom left: control, bottom right: infected) cohort. c , Dot plot showing adjusted and log-scaled Hypergeometric test p-values and the number of gene hits for the enriched categories from the Reactome pathway database across the four organs shared between aging and infection cohort. For each row of results a different list of genes was used as input (cf. Methods). d , Relative (scored) complement pathway activity in pseudobulk samples across all aging and infection cohort organs, split and colored by the five experimental groups (young, middle, old, healthy controls, infected). e , STRING network for Serpina3n in Mus musculus after performing one level of network expansion and removing edges from text mining and gene fusion. Edges are colored according to the type of association or interaction: curated databases (light blue), experientially determined (purple), gene neighborhood (green), gene co-occurrence (dark blue), co-expression (black), or protein homology (light purple). Nodes are colored according to their shell of interactions towards Serpina3n. f , Scatter plot showing normalized pseudobulk expression of C4b (x-axis) against Serpina3n (y-axis) across all samples and colored by the five experimental groups (young, middle, old, healthy controls, infected). g , Row and column clustered heatmap showing the scaled pseudobulk expression for all members of the serine protease inhibitor (Serpin*) gene family. h , Demonstration of spatially connected (sub-)cellular activity of the complement pathway (C4b+) and activated Astrocytes (Gfap+) in the aging brain (Bregma -2.06). Normalized expression values from one young representative on the top and one old representative on the bottom originating from the Stereo-seq samples at bin20 resolution are displayed.

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Scatter plot showing the average log2-scaled fold-change between aging and infection for all brain DEGs matched and colored by spot cluster. b , Normalized spatial expression of C4b in four representative brain samples (Bregma: - 2.06), two from aging (top left: young, top right: old) and infection (bottom left: control, bottom right: infected) cohort. c , Dot plot showing adjusted and log-scaled Hypergeometric test p-values and the number of gene hits for the enriched categories from the Reactome pathway database across the four organs shared between aging and infection cohort. For each row of results a different list of genes was used as input (cf. Methods). d , Relative (scored) complement pathway activity in pseudobulk samples across all aging and infection cohort organs, split and colored by the five experimental groups (young, middle, old, healthy controls, infected). e , STRING network for Serpina3n in Mus musculus after performing one level of network expansion and removing edges from text mining and gene fusion. Edges are colored according to the type of association or interaction: curated databases (light blue), experientially determined (purple), gene neighborhood (green), gene co-occurrence (dark blue), co-expression (black), or protein homology (light purple). Nodes are colored according to their shell of interactions towards Serpina3n. f , Scatter plot showing normalized pseudobulk expression of C4b (x-axis) against Serpina3n (y-axis) across all samples and colored by the five experimental groups (young, middle, old, healthy controls, infected). g , Row and column clustered heatmap showing the scaled pseudobulk expression for all members of the serine protease inhibitor (Serpin*) gene family. h , Demonstration of spatially connected (sub-)cellular activity of the complement pathway (C4b+) and activated Astrocytes (Gfap+) in the aging brain (Bregma -2.06). Normalized expression values from one young representative on the top and one old representative on the bottom originating from the Stereo-seq samples at bin20 resolution are displayed.

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Infection, Expressing, Control, Activity Assay, Protease Inhibitor

    a , Combined analysis of C4b and Serpina3n by per-spot multiplication of normalized expression values across four groups of samples (young, old, control, infected). Shown are the combined expression values for Astrocyte assigned spots from the cell binning resolved brain1 Stereo-seq samples (left), and the Astrocyte marker enriched spots from the aging (middle) and malaria disease (right) mouse brain Visium samples. b , As in ( a ) but for the Oligodendrocyte assigned spots (Stereo-seq) and Oligodendrocyte marker enriched spots (Visium). c , Normalized protein expression intensities of C4b and Serpina3n in young (3 month), adult middle aged (15 month), and old (24 month) mouse brain cortex (left) and hippocampus (right), as originally obtained by Tsumagari et al .

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Combined analysis of C4b and Serpina3n by per-spot multiplication of normalized expression values across four groups of samples (young, old, control, infected). Shown are the combined expression values for Astrocyte assigned spots from the cell binning resolved brain1 Stereo-seq samples (left), and the Astrocyte marker enriched spots from the aging (middle) and malaria disease (right) mouse brain Visium samples. b , As in ( a ) but for the Oligodendrocyte assigned spots (Stereo-seq) and Oligodendrocyte marker enriched spots (Visium). c , Normalized protein expression intensities of C4b and Serpina3n in young (3 month), adult middle aged (15 month), and old (24 month) mouse brain cortex (left) and hippocampus (right), as originally obtained by Tsumagari et al .

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Expressing, Control, Infection, Marker

    a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and STOmics Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Visualization of the five Bregmata selected to study different regions of the aging brain. b , From left to right: Two-dimensional UMAP representation of colored spot clusters computationally integrated by brain slice (top to bottom), pie chart showing the proportion of annotated clusters across all brain samples, one representative annotated Visium sample with the spot cluster identities plotted over the H&E-stained tissue image. c , Number of differentially expressed genes per aging brain bregma (old vs. young) and direction of dysregulation. Total DEG counts were derived across all organ clusters, without removing duplicates. d , Five-dimensional Venn diagram comparing the brain DEG sets from ( c ). e , Heatmap showing scaled expression of the 17 aging DEGs (rows) shared between all five brain slices, using the Brain1 pseudobulk samples and spot clusters for visualization (columns). All genes except Rbm3 are also significant SVGs in at least one of the five brain bregmata. f , Sketch of 10x Visium and STOmics Stereo-seq examples comparing the features of both spatial transcriptomics technology platforms. g , Examples for binned (bin200) and annotated spot clusters of the aging brain (top to bottom; young, middle, old) at Bregma#1 sequenced with Stereo-seq. h , Dot plot showing the top 3 most significant marker genes per cell type annotated spot cluster using the Stereo-seq cellbin resolution of Brain1 samples. i , Normalized spatial expression of Trem2 across all 15 STOmics Stereo-seq brain samples using the near-cellular resolution bin20 (from left to right: young, middle, old; from top to bottom: Brain1-5). For visualization spot sizes were rescaled into the point interval [0.1, 1.5] according to their expression of Trem2.

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Slice Preparation, Staining, Derivative Assay, Expressing, Marker

    a , Illustration of the five different brain bregma used for STOmics Stereo-seq in accordance with the Visium data set. Representative H&E stains are shown for each Bregma. Since Stereo-seq does not support H&E stains directly from the sequenced tissue slices, an adjacent (directly before or after) tissue slice was prepared and stained before running the spatial transcriptomics experiments. b , From left to right and per brain bregma (top to bottom): integrated UMAP representation of all cleaned Stereo-seq spot clusters using the bin200 resolution, pie charts and per replicate spatial projections of the final annotated spot clusters. Cluster names and colors were assigned in accordance with the Visium data set (cf. Methods). c , Distribution of four main quality control features across the cleaned spots and per Stereo-seq brain replicate at bin200 resolution.

    Journal: bioRxiv

    Article Title: Spatiotemporal transcriptomic niches of complement pathway and serine protease inhibitor activation in aging and infection

    doi: 10.1101/2024.11.04.621811

    Figure Lengend Snippet: a , Illustration of the five different brain bregma used for STOmics Stereo-seq in accordance with the Visium data set. Representative H&E stains are shown for each Bregma. Since Stereo-seq does not support H&E stains directly from the sequenced tissue slices, an adjacent (directly before or after) tissue slice was prepared and stained before running the spatial transcriptomics experiments. b , From left to right and per brain bregma (top to bottom): integrated UMAP representation of all cleaned Stereo-seq spot clusters using the bin200 resolution, pie charts and per replicate spatial projections of the final annotated spot clusters. Cluster names and colors were assigned in accordance with the Visium data set (cf. Methods). c , Distribution of four main quality control features across the cleaned spots and per Stereo-seq brain replicate at bin200 resolution.

    Article Snippet: One brain sample of each age was processed at the MGI Tech Co., Ltd. (Riga, Latvia) using the STOmics Stereo-seq Transcriptomics T Kit (MGI).

    Techniques: Staining, Control