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Omics Data Automation dbit-seq data
Dbit Seq Data, supplied by Omics Data Automation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dbit-seq data/product/Omics Data Automation
Average 90 stars, based on 1 article reviews
dbit-seq data - by Bioz Stars, 2026-04
90/100 stars

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Broad Clinical Labs dbit seq data
A. Stereo-seq pipeline. Step 1 , design of the DNB patterned array chip. Step 2 , in situ sequencing to determine the spatial coordinates of uniquely barcoded oligonucleotides placed on each spot of the chip. Step 3 , preparation of capture probes by ligating the UMI-polyT containing oligonucleotides to each spot. Step 4 , subsequent in situ RNA capture from tissue placed on the chip. Step 5 , cDNA amplification, library construction and sequencing. Step 6 , data analysis to generate the spatially resolved transcriptome of the profiled tissue. B. Stereo-seq achieves a smaller spot size (upper left), higher resolution (upper right), higher number of spots per 100 μm 2 (bottom left) and larger capture area (bottom right) than other reported methods. Samples used for the comparison included mouse olfactory bulb (Stereo-seq, Visium, Slide-seqV2 and HDST), E10 mouse embryo <t>(DBiT-seq)</t> and mouse liver (Seq-Scope) ( ; ; ; ; ). Note that since Seq-Scope uses a random array, which contains no patterned spots, the size of each pixel was estimated according to the published dataset. C. Boxplots showing the number of transcripts captured by Stereo-seq at the indicated resolution in comparison with reported HDST, Slide-seqV2, Visium, DBiT-seq and Seq-Scope datasets. Samples in those datasets used for comparison are as in panel B . D. Unsupervised spatially-constrained clustering of the mouse olfactory bulb section analyzed by Stereo-seq data at bin 14 resolution, bins were colored by their annotation. ONL, olfactory nerve layer. OPL, outer plexiform layer. GL, glomerular layer. GCL-D, granular cell zone deep. GCL-E, granular cell layer externa. GCL-I, granular cell layer internal. IPL, internal plexiform layer. ML, mitral layer. SEZ, subependymal zone. Scale bar, 500 μm. E. Left: spatial visualization of Cdhr1 in a mouse olfactory bulb section analyzed by Stereo-seq. Right: Cdhr1 ISH data taken from Allen Brain Atlas. Scale bars, 500 μm. F. Unsupervised spatially-constrained clustering of the mouse brain section analyzed by Stereo-seq at bin 50 resolution, bins were colored by their annotation. Scale bar, 500 μm. G. Left: projection of captured DNB signals of the same region squared in the panel F . Scale bar, 50 μm. Right: superimposed nucleic acid staining and captured DNB signals from the same region squared in the middle panel. Scale bar, 10 μm.
Dbit Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dbit seq data/product/Broad Clinical Labs
Average 96 stars, based on 1 article reviews
dbit seq data - by Bioz Stars, 2026-04
96/100 stars
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90
Omics Data Automation dbit-seq data
A. Stereo-seq pipeline. Step 1 , design of the DNB patterned array chip. Step 2 , in situ sequencing to determine the spatial coordinates of uniquely barcoded oligonucleotides placed on each spot of the chip. Step 3 , preparation of capture probes by ligating the UMI-polyT containing oligonucleotides to each spot. Step 4 , subsequent in situ RNA capture from tissue placed on the chip. Step 5 , cDNA amplification, library construction and sequencing. Step 6 , data analysis to generate the spatially resolved transcriptome of the profiled tissue. B. Stereo-seq achieves a smaller spot size (upper left), higher resolution (upper right), higher number of spots per 100 μm 2 (bottom left) and larger capture area (bottom right) than other reported methods. Samples used for the comparison included mouse olfactory bulb (Stereo-seq, Visium, Slide-seqV2 and HDST), E10 mouse embryo <t>(DBiT-seq)</t> and mouse liver (Seq-Scope) ( ; ; ; ; ). Note that since Seq-Scope uses a random array, which contains no patterned spots, the size of each pixel was estimated according to the published dataset. C. Boxplots showing the number of transcripts captured by Stereo-seq at the indicated resolution in comparison with reported HDST, Slide-seqV2, Visium, DBiT-seq and Seq-Scope datasets. Samples in those datasets used for comparison are as in panel B . D. Unsupervised spatially-constrained clustering of the mouse olfactory bulb section analyzed by Stereo-seq data at bin 14 resolution, bins were colored by their annotation. ONL, olfactory nerve layer. OPL, outer plexiform layer. GL, glomerular layer. GCL-D, granular cell zone deep. GCL-E, granular cell layer externa. GCL-I, granular cell layer internal. IPL, internal plexiform layer. ML, mitral layer. SEZ, subependymal zone. Scale bar, 500 μm. E. Left: spatial visualization of Cdhr1 in a mouse olfactory bulb section analyzed by Stereo-seq. Right: Cdhr1 ISH data taken from Allen Brain Atlas. Scale bars, 500 μm. F. Unsupervised spatially-constrained clustering of the mouse brain section analyzed by Stereo-seq at bin 50 resolution, bins were colored by their annotation. Scale bar, 500 μm. G. Left: projection of captured DNB signals of the same region squared in the panel F . Scale bar, 50 μm. Right: superimposed nucleic acid staining and captured DNB signals from the same region squared in the middle panel. Scale bar, 10 μm.
Dbit Seq Data, supplied by Omics Data Automation, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/result/dbit-seq data/product/Omics Data Automation
Average 90 stars, based on 1 article reviews
dbit-seq data - by Bioz Stars, 2026-04
90/100 stars
  Buy from Supplier

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A. Stereo-seq pipeline. Step 1 , design of the DNB patterned array chip. Step 2 , in situ sequencing to determine the spatial coordinates of uniquely barcoded oligonucleotides placed on each spot of the chip. Step 3 , preparation of capture probes by ligating the UMI-polyT containing oligonucleotides to each spot. Step 4 , subsequent in situ RNA capture from tissue placed on the chip. Step 5 , cDNA amplification, library construction and sequencing. Step 6 , data analysis to generate the spatially resolved transcriptome of the profiled tissue. B. Stereo-seq achieves a smaller spot size (upper left), higher resolution (upper right), higher number of spots per 100 μm 2 (bottom left) and larger capture area (bottom right) than other reported methods. Samples used for the comparison included mouse olfactory bulb (Stereo-seq, Visium, Slide-seqV2 and HDST), E10 mouse embryo (DBiT-seq) and mouse liver (Seq-Scope) ( ; ; ; ; ). Note that since Seq-Scope uses a random array, which contains no patterned spots, the size of each pixel was estimated according to the published dataset. C. Boxplots showing the number of transcripts captured by Stereo-seq at the indicated resolution in comparison with reported HDST, Slide-seqV2, Visium, DBiT-seq and Seq-Scope datasets. Samples in those datasets used for comparison are as in panel B . D. Unsupervised spatially-constrained clustering of the mouse olfactory bulb section analyzed by Stereo-seq data at bin 14 resolution, bins were colored by their annotation. ONL, olfactory nerve layer. OPL, outer plexiform layer. GL, glomerular layer. GCL-D, granular cell zone deep. GCL-E, granular cell layer externa. GCL-I, granular cell layer internal. IPL, internal plexiform layer. ML, mitral layer. SEZ, subependymal zone. Scale bar, 500 μm. E. Left: spatial visualization of Cdhr1 in a mouse olfactory bulb section analyzed by Stereo-seq. Right: Cdhr1 ISH data taken from Allen Brain Atlas. Scale bars, 500 μm. F. Unsupervised spatially-constrained clustering of the mouse brain section analyzed by Stereo-seq at bin 50 resolution, bins were colored by their annotation. Scale bar, 500 μm. G. Left: projection of captured DNB signals of the same region squared in the panel F . Scale bar, 50 μm. Right: superimposed nucleic acid staining and captured DNB signals from the same region squared in the middle panel. Scale bar, 10 μm.

Journal: bioRxiv

Article Title: Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

doi: 10.1101/2021.01.17.427004

Figure Lengend Snippet: A. Stereo-seq pipeline. Step 1 , design of the DNB patterned array chip. Step 2 , in situ sequencing to determine the spatial coordinates of uniquely barcoded oligonucleotides placed on each spot of the chip. Step 3 , preparation of capture probes by ligating the UMI-polyT containing oligonucleotides to each spot. Step 4 , subsequent in situ RNA capture from tissue placed on the chip. Step 5 , cDNA amplification, library construction and sequencing. Step 6 , data analysis to generate the spatially resolved transcriptome of the profiled tissue. B. Stereo-seq achieves a smaller spot size (upper left), higher resolution (upper right), higher number of spots per 100 μm 2 (bottom left) and larger capture area (bottom right) than other reported methods. Samples used for the comparison included mouse olfactory bulb (Stereo-seq, Visium, Slide-seqV2 and HDST), E10 mouse embryo (DBiT-seq) and mouse liver (Seq-Scope) ( ; ; ; ; ). Note that since Seq-Scope uses a random array, which contains no patterned spots, the size of each pixel was estimated according to the published dataset. C. Boxplots showing the number of transcripts captured by Stereo-seq at the indicated resolution in comparison with reported HDST, Slide-seqV2, Visium, DBiT-seq and Seq-Scope datasets. Samples in those datasets used for comparison are as in panel B . D. Unsupervised spatially-constrained clustering of the mouse olfactory bulb section analyzed by Stereo-seq data at bin 14 resolution, bins were colored by their annotation. ONL, olfactory nerve layer. OPL, outer plexiform layer. GL, glomerular layer. GCL-D, granular cell zone deep. GCL-E, granular cell layer externa. GCL-I, granular cell layer internal. IPL, internal plexiform layer. ML, mitral layer. SEZ, subependymal zone. Scale bar, 500 μm. E. Left: spatial visualization of Cdhr1 in a mouse olfactory bulb section analyzed by Stereo-seq. Right: Cdhr1 ISH data taken from Allen Brain Atlas. Scale bars, 500 μm. F. Unsupervised spatially-constrained clustering of the mouse brain section analyzed by Stereo-seq at bin 50 resolution, bins were colored by their annotation. Scale bar, 500 μm. G. Left: projection of captured DNB signals of the same region squared in the panel F . Scale bar, 50 μm. Right: superimposed nucleic acid staining and captured DNB signals from the same region squared in the middle panel. Scale bar, 10 μm.

Article Snippet: HDST data ( ) were taken from GSE130682, SLIDE-seqV2 data ( ) from the Single Cell Portal of the Broad Institute, DBiT-seq data ( ) from GSE137986, and Visium data ( ) from GSE153859, Seq-Scope data were taken from GSE169706 ( ).

Techniques: In Situ, Sequencing, Amplification, Comparison, Olfactory, Staining

A. Spatial heatmap indicating the number of UMI captured by Stereo-seq from an E10.5 embryo section (same as in ) at bin 50 (left) compared to an E10 DBiT-seq dataset at the same resolution (right). Scale bar, 500 μm. B. Spatial visualization of the expression of the indicated genes in Stereo-seq (upper panels) and DBiT-seq (lower panels) mouse embryo datasets. Scale bars, 500 μm.

Journal: bioRxiv

Article Title: Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball patterned arrays

doi: 10.1101/2021.01.17.427004

Figure Lengend Snippet: A. Spatial heatmap indicating the number of UMI captured by Stereo-seq from an E10.5 embryo section (same as in ) at bin 50 (left) compared to an E10 DBiT-seq dataset at the same resolution (right). Scale bar, 500 μm. B. Spatial visualization of the expression of the indicated genes in Stereo-seq (upper panels) and DBiT-seq (lower panels) mouse embryo datasets. Scale bars, 500 μm.

Article Snippet: HDST data ( ) were taken from GSE130682, SLIDE-seqV2 data ( ) from the Single Cell Portal of the Broad Institute, DBiT-seq data ( ) from GSE137986, and Visium data ( ) from GSE153859, Seq-Scope data were taken from GSE169706 ( ).

Techniques: Expressing