epcam pecy7 Search Results


94
Developmental Studies Hybridoma Bank biolegend fc a epcam g8 8
Biolegend Fc A Epcam G8 8, supplied by Developmental Studies Hybridoma Bank, used in various techniques. Bioz Stars score: 94/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Miltenyi Biotec anti cd326 epcam apc miltenyi biotec pe cy7 mouse
Anti Cd326 Epcam Apc Miltenyi Biotec Pe Cy7 Mouse, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher epcam-pe-cy7
Epcam Pe Cy7, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher epcam-pecy7 antibody
Epcam Pecy7 Antibody, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher anti-mouse epcam pecy7
KEY RESOURCES TABLE
Anti Mouse Epcam Pecy7, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher cd326/epcam-pe-cy7 ebiosciences antibody
KEY RESOURCES TABLE
Cd326/Epcam Pe Cy7 Ebiosciences Antibody, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Miltenyi Biotec cd326 epcam pecy7
Correlation between lymphocyte populations and tumor cells in malignant pleural effusions from lung cancer. Cells from MPEs of LAC patients were stained with anti-CD3, CD4, CD20, CD45 and EpCAM <t>(CD326)</t> monoclonal antibodies to be analyzed by flow cytometry. Tumor cells were identified as CD45- CD326 (EpCAM)+ cells. Correlations between CD4+ T and CD8+ T, CD4+ T and CD20+ T, and CD8+ T and CD20+ B lymphocytes cells/ml and between tumor cells/ml and CD4+ T, CD8+ T and CD20+ B lymphocytes cells/ml were analyzed by Spearman’s correlation. Black circles correspond to LAC patients diagnosed with cancer >1 month before of MPE formation. Statistically significant correlations (p < 0.05) are shown.
Cd326 Epcam Pecy7, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher anti epcam pe cy7
Correlation between lymphocyte populations and tumor cells in malignant pleural effusions from lung cancer. Cells from MPEs of LAC patients were stained with anti-CD3, CD4, CD20, CD45 and EpCAM <t>(CD326)</t> monoclonal antibodies to be analyzed by flow cytometry. Tumor cells were identified as CD45- CD326 (EpCAM)+ cells. Correlations between CD4+ T and CD8+ T, CD4+ T and CD20+ T, and CD8+ T and CD20+ B lymphocytes cells/ml and between tumor cells/ml and CD4+ T, CD8+ T and CD20+ B lymphocytes cells/ml were analyzed by Spearman’s correlation. Black circles correspond to LAC patients diagnosed with cancer >1 month before of MPE formation. Statistically significant correlations (p < 0.05) are shown.
Anti Epcam Pe Cy7, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher pe/cy7-conjugated cd326 (epcam
Correlation between lymphocyte populations and tumor cells in malignant pleural effusions from lung cancer. Cells from MPEs of LAC patients were stained with anti-CD3, CD4, CD20, CD45 and EpCAM <t>(CD326)</t> monoclonal antibodies to be analyzed by flow cytometry. Tumor cells were identified as CD45- CD326 (EpCAM)+ cells. Correlations between CD4+ T and CD8+ T, CD4+ T and CD20+ T, and CD8+ T and CD20+ B lymphocytes cells/ml and between tumor cells/ml and CD4+ T, CD8+ T and CD20+ B lymphocytes cells/ml were analyzed by Spearman’s correlation. Black circles correspond to LAC patients diagnosed with cancer >1 month before of MPE formation. Statistically significant correlations (p < 0.05) are shown.
Pe/Cy7 Conjugated Cd326 (Epcam, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Thermo Fisher antibodies against cd90-apc, epcam-pe-cy7
(A) Overall sphere formation (left panel) and secondary and third sphere formation from dissected single spherical cells (right panel) in vector- or cyclin D1-expressing Huh7 and 97H cells. (B) Phase contrast image of vector- (upper panel) and cyclin D1-expressing (lower panel) liver cancer spherical colonies. (C) mRNA levels of E2F1 in vector and cyclin D1-expressing spheres. qRT-PCR data are represented as the mean ± SD, n = 2. (D) Flow cytometry analysis of the CD90+ and <t>EpCAM+</t> population in vector- or cyclin D1-expressing spherical cells shown by both dot blot and histogram. (E) mRNA levels of the stemness genes NANOG, OCT4, SOX2, NODAL, and ACTIVIN. qRT-PCR data are represented as the mean ± SD, n = 3 (from different spheres); each experiment was conducted in duplicate. The vector- and cyclin D1-expressing spheres were statistically compared with a paired Student's t test (*, p < 0.05; **, p < 0.01; ***, p < 0.001). (F) qRT-PCR of glycolytic genes, GLUT1, PFK1, HK2, and LDHA. (G) Sphere formation capability of vector- or cyclin D1-expressing spheres after cisplatin (0.5-0.8 μg) and doxorubicin (0.1-0.2 μg) treatments.
Antibodies Against Cd90 Apc, Epcam Pe Cy7, supplied by Thermo Fisher, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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Miltenyi Biotec epcam (pe-cy7
Overview of hashing methodology, sample cell-of-origin assignments and pool batch correction, related to <xref ref-type=Figure 1 and (A) Hemotoxylin and Eosin (H&E) staining of intestinal sections demonstrating morphology of samples spanning the times and locations included in transcriptomic atlas (representative images of ≥3 samples at specified location and similar (+-1pcw) timepoints, each at 20x magnification scale bar=180 μm). (B) Example distribution of B2M mRNA expression in single EPCAM+ cells from an early gestation (8 PCW) sample and late gestation (19 PCW) sample from the same pool (identical sequencing depth and sample preparation conditions) showing reduced B2M mRNA levels in early gestation. (C) Density plot showing the distribution of per cell gene detection rate across different cell compartments. Cells are further broken down into G2M&S Phase cells (dashed line) and G1-phase cells (solid line) based on cluster analysis, as cycling cells in the G2M/S-phase tend to have substantially larger total mRNA content. (D) t-distributed stochastic neighborhood embedding (tSNE) of cells from a representative EPCAM- pool based on their recovered hashing antibody profiles, colored by classification into singlets, doublets or unstained/negative cells following dehashing . (E) tSNE embeddings of EPCAM+ cells from a representative pool, showing embeddings based on TotalSeq antibody tags only (i), in-house labelled antibody tags (ii) and both tags (iii). Cells are colored by sample identities assigned from dual-tag labels. Arrows indicate relevant regions highlighting multiplets (top left, (i) panel); inability to discriminate cells from low gestation samples (Sample 1 and Sample 2) when using TotalSeq tags only (center arrow, (i) panel), while the in-house tag separates cells from Sample 1 (left arrow, (ii) panel) from Sample 2 (right arrow, (ii) panel) while some untagged/negative cells still remain (center arrow, (ii) panel). (F) tSNE overlay comparing TotalSeq (i) and in-house (ii) tag signal in late gestation samples, and early gestation samples (iii-iv) in double-tagged EPCAM+ pool cells. In-house tag signal is stronger than TotalSeq tag for early gestation cells, while being comparable for late gestation cells. (G) tSNE embedding of TotalSeq tag signal in late (i) and early (ii) gestation samples in EPCAM- pools shows similar tag recoveries, in contrast to EPCAM+ pool cells in (F). (H) Expression of compartment markers for stromal cells - THY1/CD90 (i) and epithelial cells - EPCAM (ii) shown as a tSNE overlay over embedding shown in E (iii). Arrows highlight regions of interest, where most unstained/unassigned cells in EPCAM+ pools are either EPCAM- due to poor cell quality or are non-epithelial contaminants expressing stromal or immune markers (center arrow, panels i-ii). Non-epithelial contaminant cell sample-of-origin can be resolved in many cases in double-tagged pools, for instance stromal cells in central region of the embedding in other samples ( Figure S1 E iii). (I) Example of pool effect batch correction described in . A UMAP embedding shows epithelial cells and their hashed pool prior to pool effect correction (i) and post-correction (ii). " width="250" height="auto" />
Epcam (Pe Cy7, supplied by Miltenyi Biotec, 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/epcam (pe-cy7/product/Miltenyi Biotec
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Santa Cruz Biotechnology epcam-pe-cy7 antibody
Overview of hashing methodology, sample cell-of-origin assignments and pool batch correction, related to <xref ref-type=Figure 1 and (A) Hemotoxylin and Eosin (H&E) staining of intestinal sections demonstrating morphology of samples spanning the times and locations included in transcriptomic atlas (representative images of ≥3 samples at specified location and similar (+-1pcw) timepoints, each at 20x magnification scale bar=180 μm). (B) Example distribution of B2M mRNA expression in single EPCAM+ cells from an early gestation (8 PCW) sample and late gestation (19 PCW) sample from the same pool (identical sequencing depth and sample preparation conditions) showing reduced B2M mRNA levels in early gestation. (C) Density plot showing the distribution of per cell gene detection rate across different cell compartments. Cells are further broken down into G2M&S Phase cells (dashed line) and G1-phase cells (solid line) based on cluster analysis, as cycling cells in the G2M/S-phase tend to have substantially larger total mRNA content. (D) t-distributed stochastic neighborhood embedding (tSNE) of cells from a representative EPCAM- pool based on their recovered hashing antibody profiles, colored by classification into singlets, doublets or unstained/negative cells following dehashing . (E) tSNE embeddings of EPCAM+ cells from a representative pool, showing embeddings based on TotalSeq antibody tags only (i), in-house labelled antibody tags (ii) and both tags (iii). Cells are colored by sample identities assigned from dual-tag labels. Arrows indicate relevant regions highlighting multiplets (top left, (i) panel); inability to discriminate cells from low gestation samples (Sample 1 and Sample 2) when using TotalSeq tags only (center arrow, (i) panel), while the in-house tag separates cells from Sample 1 (left arrow, (ii) panel) from Sample 2 (right arrow, (ii) panel) while some untagged/negative cells still remain (center arrow, (ii) panel). (F) tSNE overlay comparing TotalSeq (i) and in-house (ii) tag signal in late gestation samples, and early gestation samples (iii-iv) in double-tagged EPCAM+ pool cells. In-house tag signal is stronger than TotalSeq tag for early gestation cells, while being comparable for late gestation cells. (G) tSNE embedding of TotalSeq tag signal in late (i) and early (ii) gestation samples in EPCAM- pools shows similar tag recoveries, in contrast to EPCAM+ pool cells in (F). (H) Expression of compartment markers for stromal cells - THY1/CD90 (i) and epithelial cells - EPCAM (ii) shown as a tSNE overlay over embedding shown in E (iii). Arrows highlight regions of interest, where most unstained/unassigned cells in EPCAM+ pools are either EPCAM- due to poor cell quality or are non-epithelial contaminants expressing stromal or immune markers (center arrow, panels i-ii). Non-epithelial contaminant cell sample-of-origin can be resolved in many cases in double-tagged pools, for instance stromal cells in central region of the embedding in other samples ( Figure S1 E iii). (I) Example of pool effect batch correction described in . A UMAP embedding shows epithelial cells and their hashed pool prior to pool effect correction (i) and post-correction (ii). " width="250" height="auto" />
Epcam Pe Cy7 Antibody, supplied by Santa Cruz Biotechnology, 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/epcam-pe-cy7 antibody/product/Santa Cruz Biotechnology
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Image Search Results


KEY RESOURCES TABLE

Journal: Cancer cell

Article Title: Logic-gated ROR1 chimeric antigen receptor expression rescues T cell-mediated toxicity to normal tissues and enables selective tumor targeting

doi: 10.1016/j.ccell.2019.02.003

Figure Lengend Snippet: KEY RESOURCES TABLE

Article Snippet: Anti-mouse EpCAM PECy7 , Thermo Fisher Scientific , Cat# 25–5791-80, RRID:AB_1724047).

Techniques: Control, Histopathology, Recombinant, Cell Isolation, cDNA Synthesis, Plasmid Preparation, Software, SYBR Green Assay

Correlation between lymphocyte populations and tumor cells in malignant pleural effusions from lung cancer. Cells from MPEs of LAC patients were stained with anti-CD3, CD4, CD20, CD45 and EpCAM (CD326) monoclonal antibodies to be analyzed by flow cytometry. Tumor cells were identified as CD45- CD326 (EpCAM)+ cells. Correlations between CD4+ T and CD8+ T, CD4+ T and CD20+ T, and CD8+ T and CD20+ B lymphocytes cells/ml and between tumor cells/ml and CD4+ T, CD8+ T and CD20+ B lymphocytes cells/ml were analyzed by Spearman’s correlation. Black circles correspond to LAC patients diagnosed with cancer >1 month before of MPE formation. Statistically significant correlations (p < 0.05) are shown.

Journal: Scientific Reports

Article Title: Migrated T lymphocytes into malignant pleural effusions: an indicator of good prognosis in lung adenocarcinoma patients

doi: 10.1038/s41598-018-35840-3

Figure Lengend Snippet: Correlation between lymphocyte populations and tumor cells in malignant pleural effusions from lung cancer. Cells from MPEs of LAC patients were stained with anti-CD3, CD4, CD20, CD45 and EpCAM (CD326) monoclonal antibodies to be analyzed by flow cytometry. Tumor cells were identified as CD45- CD326 (EpCAM)+ cells. Correlations between CD4+ T and CD8+ T, CD4+ T and CD20+ T, and CD8+ T and CD20+ B lymphocytes cells/ml and between tumor cells/ml and CD4+ T, CD8+ T and CD20+ B lymphocytes cells/ml were analyzed by Spearman’s correlation. Black circles correspond to LAC patients diagnosed with cancer >1 month before of MPE formation. Statistically significant correlations (p < 0.05) are shown.

Article Snippet: Panel C included anti-CD45-Vioblue and CD326 (EpCAM)-PECy7 (Miltenyi Biotec).

Techniques: Staining, Bioprocessing, Flow Cytometry

(A) Overall sphere formation (left panel) and secondary and third sphere formation from dissected single spherical cells (right panel) in vector- or cyclin D1-expressing Huh7 and 97H cells. (B) Phase contrast image of vector- (upper panel) and cyclin D1-expressing (lower panel) liver cancer spherical colonies. (C) mRNA levels of E2F1 in vector and cyclin D1-expressing spheres. qRT-PCR data are represented as the mean ± SD, n = 2. (D) Flow cytometry analysis of the CD90+ and EpCAM+ population in vector- or cyclin D1-expressing spherical cells shown by both dot blot and histogram. (E) mRNA levels of the stemness genes NANOG, OCT4, SOX2, NODAL, and ACTIVIN. qRT-PCR data are represented as the mean ± SD, n = 3 (from different spheres); each experiment was conducted in duplicate. The vector- and cyclin D1-expressing spheres were statistically compared with a paired Student's t test (*, p < 0.05; **, p < 0.01; ***, p < 0.001). (F) qRT-PCR of glycolytic genes, GLUT1, PFK1, HK2, and LDHA. (G) Sphere formation capability of vector- or cyclin D1-expressing spheres after cisplatin (0.5-0.8 μg) and doxorubicin (0.1-0.2 μg) treatments.

Journal: Oncotarget

Article Title: Smad inhibitor induces CSC differentiation for effective chemosensitization in cyclin D1- and TGF-β/Smad-regulated liver cancer stem cell-like cells

doi: 10.18632/oncotarget.16402

Figure Lengend Snippet: (A) Overall sphere formation (left panel) and secondary and third sphere formation from dissected single spherical cells (right panel) in vector- or cyclin D1-expressing Huh7 and 97H cells. (B) Phase contrast image of vector- (upper panel) and cyclin D1-expressing (lower panel) liver cancer spherical colonies. (C) mRNA levels of E2F1 in vector and cyclin D1-expressing spheres. qRT-PCR data are represented as the mean ± SD, n = 2. (D) Flow cytometry analysis of the CD90+ and EpCAM+ population in vector- or cyclin D1-expressing spherical cells shown by both dot blot and histogram. (E) mRNA levels of the stemness genes NANOG, OCT4, SOX2, NODAL, and ACTIVIN. qRT-PCR data are represented as the mean ± SD, n = 3 (from different spheres); each experiment was conducted in duplicate. The vector- and cyclin D1-expressing spheres were statistically compared with a paired Student's t test (*, p < 0.05; **, p < 0.01; ***, p < 0.001). (F) qRT-PCR of glycolytic genes, GLUT1, PFK1, HK2, and LDHA. (G) Sphere formation capability of vector- or cyclin D1-expressing spheres after cisplatin (0.5-0.8 μg) and doxorubicin (0.1-0.2 μg) treatments.

Article Snippet: To identify the liver CSC population, the cells were labeled with antibodies against CD90-APC, EpCAM-PE-Cy7 (eBioscience), and CD133 (Miltenyi) and then subjected to a flow cytometry analysis using FACSCalibur (Becton Dickinson).

Techniques: Plasmid Preparation, Expressing, Quantitative RT-PCR, Flow Cytometry, Dot Blot

(A) Flow cytometry analysis of the CD90+, EpCAM+, and CD133+ population in cyclin D1-expressing spheres after treatment with the Smad inhibitor SB431542. (B) NANOG, OCT4, and SOX2 expression in cyclin D1-expressing spheres treated with SB431542 versus DMSO. (C) Expression of the epithelial genes CDH1 and CK19 and (D) the mesenchymal genes SNAIL1, SNAIL2, CDH2 and ABCB1 after SB431542 treatment. (E) Relative sphere viability of cyclin D1-expressing spheres treated with various doses of SB431542 (10, 30, or 40 μM) versus DMSO. (F) Percentage of differentiated spherical colonies after SB431542 (20-30 μM) treatment. (G) Phase contrast image of spherical colonies treated with SB431542 versus untreated control. (H) Sphere viability of cyclin D1-97H spherical cells treated with cisplatin alone, SB431542 in combination with cisplatin (SB +cis), or SB431542 pre-treatment followed by cisplatin (SB >cis). SB431542 all in low dose (10 μM). (I) Same assay as described in (H) in cyclin D1-Huh7 spherical cells.

Journal: Oncotarget

Article Title: Smad inhibitor induces CSC differentiation for effective chemosensitization in cyclin D1- and TGF-β/Smad-regulated liver cancer stem cell-like cells

doi: 10.18632/oncotarget.16402

Figure Lengend Snippet: (A) Flow cytometry analysis of the CD90+, EpCAM+, and CD133+ population in cyclin D1-expressing spheres after treatment with the Smad inhibitor SB431542. (B) NANOG, OCT4, and SOX2 expression in cyclin D1-expressing spheres treated with SB431542 versus DMSO. (C) Expression of the epithelial genes CDH1 and CK19 and (D) the mesenchymal genes SNAIL1, SNAIL2, CDH2 and ABCB1 after SB431542 treatment. (E) Relative sphere viability of cyclin D1-expressing spheres treated with various doses of SB431542 (10, 30, or 40 μM) versus DMSO. (F) Percentage of differentiated spherical colonies after SB431542 (20-30 μM) treatment. (G) Phase contrast image of spherical colonies treated with SB431542 versus untreated control. (H) Sphere viability of cyclin D1-97H spherical cells treated with cisplatin alone, SB431542 in combination with cisplatin (SB +cis), or SB431542 pre-treatment followed by cisplatin (SB >cis). SB431542 all in low dose (10 μM). (I) Same assay as described in (H) in cyclin D1-Huh7 spherical cells.

Article Snippet: To identify the liver CSC population, the cells were labeled with antibodies against CD90-APC, EpCAM-PE-Cy7 (eBioscience), and CD133 (Miltenyi) and then subjected to a flow cytometry analysis using FACSCalibur (Becton Dickinson).

Techniques: Flow Cytometry, Expressing, Control

Overview of hashing methodology, sample cell-of-origin assignments and pool batch correction, related to <xref ref-type=Figure 1 and (A) Hemotoxylin and Eosin (H&E) staining of intestinal sections demonstrating morphology of samples spanning the times and locations included in transcriptomic atlas (representative images of ≥3 samples at specified location and similar (+-1pcw) timepoints, each at 20x magnification scale bar=180 μm). (B) Example distribution of B2M mRNA expression in single EPCAM+ cells from an early gestation (8 PCW) sample and late gestation (19 PCW) sample from the same pool (identical sequencing depth and sample preparation conditions) showing reduced B2M mRNA levels in early gestation. (C) Density plot showing the distribution of per cell gene detection rate across different cell compartments. Cells are further broken down into G2M&S Phase cells (dashed line) and G1-phase cells (solid line) based on cluster analysis, as cycling cells in the G2M/S-phase tend to have substantially larger total mRNA content. (D) t-distributed stochastic neighborhood embedding (tSNE) of cells from a representative EPCAM- pool based on their recovered hashing antibody profiles, colored by classification into singlets, doublets or unstained/negative cells following dehashing . (E) tSNE embeddings of EPCAM+ cells from a representative pool, showing embeddings based on TotalSeq antibody tags only (i), in-house labelled antibody tags (ii) and both tags (iii). Cells are colored by sample identities assigned from dual-tag labels. Arrows indicate relevant regions highlighting multiplets (top left, (i) panel); inability to discriminate cells from low gestation samples (Sample 1 and Sample 2) when using TotalSeq tags only (center arrow, (i) panel), while the in-house tag separates cells from Sample 1 (left arrow, (ii) panel) from Sample 2 (right arrow, (ii) panel) while some untagged/negative cells still remain (center arrow, (ii) panel). (F) tSNE overlay comparing TotalSeq (i) and in-house (ii) tag signal in late gestation samples, and early gestation samples (iii-iv) in double-tagged EPCAM+ pool cells. In-house tag signal is stronger than TotalSeq tag for early gestation cells, while being comparable for late gestation cells. (G) tSNE embedding of TotalSeq tag signal in late (i) and early (ii) gestation samples in EPCAM- pools shows similar tag recoveries, in contrast to EPCAM+ pool cells in (F). (H) Expression of compartment markers for stromal cells - THY1/CD90 (i) and epithelial cells - EPCAM (ii) shown as a tSNE overlay over embedding shown in E (iii). Arrows highlight regions of interest, where most unstained/unassigned cells in EPCAM+ pools are either EPCAM- due to poor cell quality or are non-epithelial contaminants expressing stromal or immune markers (center arrow, panels i-ii). Non-epithelial contaminant cell sample-of-origin can be resolved in many cases in double-tagged pools, for instance stromal cells in central region of the embedding in other samples ( Figure S1 E iii). (I) Example of pool effect batch correction described in . A UMAP embedding shows epithelial cells and their hashed pool prior to pool effect correction (i) and post-correction (ii). " width="100%" height="100%">

Journal: Cell

Article Title: Spatiotemporal analysis of human intestinal development at single-cell resolution

doi: 10.1016/j.cell.2020.12.016

Figure Lengend Snippet: Overview of hashing methodology, sample cell-of-origin assignments and pool batch correction, related to Figure 1 and (A) Hemotoxylin and Eosin (H&E) staining of intestinal sections demonstrating morphology of samples spanning the times and locations included in transcriptomic atlas (representative images of ≥3 samples at specified location and similar (+-1pcw) timepoints, each at 20x magnification scale bar=180 μm). (B) Example distribution of B2M mRNA expression in single EPCAM+ cells from an early gestation (8 PCW) sample and late gestation (19 PCW) sample from the same pool (identical sequencing depth and sample preparation conditions) showing reduced B2M mRNA levels in early gestation. (C) Density plot showing the distribution of per cell gene detection rate across different cell compartments. Cells are further broken down into G2M&S Phase cells (dashed line) and G1-phase cells (solid line) based on cluster analysis, as cycling cells in the G2M/S-phase tend to have substantially larger total mRNA content. (D) t-distributed stochastic neighborhood embedding (tSNE) of cells from a representative EPCAM- pool based on their recovered hashing antibody profiles, colored by classification into singlets, doublets or unstained/negative cells following dehashing . (E) tSNE embeddings of EPCAM+ cells from a representative pool, showing embeddings based on TotalSeq antibody tags only (i), in-house labelled antibody tags (ii) and both tags (iii). Cells are colored by sample identities assigned from dual-tag labels. Arrows indicate relevant regions highlighting multiplets (top left, (i) panel); inability to discriminate cells from low gestation samples (Sample 1 and Sample 2) when using TotalSeq tags only (center arrow, (i) panel), while the in-house tag separates cells from Sample 1 (left arrow, (ii) panel) from Sample 2 (right arrow, (ii) panel) while some untagged/negative cells still remain (center arrow, (ii) panel). (F) tSNE overlay comparing TotalSeq (i) and in-house (ii) tag signal in late gestation samples, and early gestation samples (iii-iv) in double-tagged EPCAM+ pool cells. In-house tag signal is stronger than TotalSeq tag for early gestation cells, while being comparable for late gestation cells. (G) tSNE embedding of TotalSeq tag signal in late (i) and early (ii) gestation samples in EPCAM- pools shows similar tag recoveries, in contrast to EPCAM+ pool cells in (F). (H) Expression of compartment markers for stromal cells - THY1/CD90 (i) and epithelial cells - EPCAM (ii) shown as a tSNE overlay over embedding shown in E (iii). Arrows highlight regions of interest, where most unstained/unassigned cells in EPCAM+ pools are either EPCAM- due to poor cell quality or are non-epithelial contaminants expressing stromal or immune markers (center arrow, panels i-ii). Non-epithelial contaminant cell sample-of-origin can be resolved in many cases in double-tagged pools, for instance stromal cells in central region of the embedding in other samples ( Figure S1 E iii). (I) Example of pool effect batch correction described in . A UMAP embedding shows epithelial cells and their hashed pool prior to pool effect correction (i) and post-correction (ii).

Article Snippet: For analysis of cell dissociation efficiency, before undertaking scRNA-seq, cells in single-cell suspension as previously described were stained with EpCAM (PE-Cy7, Milteyni 1:50), CD90 (FITC, Biolegend 1:75), CD45 (APC, Milteyni 1:50) antibodies as appropriate for 30 minutes in PBS supplemented with 1% Bovine Serum Albumin.

Techniques: Staining, Expressing, Sequencing, Sample Prep

Journal: Cell

Article Title: Spatiotemporal analysis of human intestinal development at single-cell resolution

doi: 10.1016/j.cell.2020.12.016

Figure Lengend Snippet:

Article Snippet: For analysis of cell dissociation efficiency, before undertaking scRNA-seq, cells in single-cell suspension as previously described were stained with EpCAM (PE-Cy7, Milteyni 1:50), CD90 (FITC, Biolegend 1:75), CD45 (APC, Milteyni 1:50) antibodies as appropriate for 30 minutes in PBS supplemented with 1% Bovine Serum Albumin.

Techniques: Conjugation Assay, Recombinant, Saline, Modification, Plasmid Preparation, Expressing, Generated, Software