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c1 script builder software  (fluidigm)


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    fluidigm c1 script builder software
    C1 Script Builder Software, supplied by fluidigm, used in various techniques. Bioz Stars score: 96/100, based on 2081 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/c1+script+builder/C1/us12377396-1963-22-29
    Average 96 stars, based on 2081 article reviews
    c1 script builder software - by Bioz Stars, 2026-09
    96/100 stars

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    Related Articles

    Modification:

    Article Title: Deformation-induced transitional myofibroblasts contribute to compensatory lung growth
    Article Snippet: Cells were loaded onto the chip at concentrations ranging from 120 to 370 cells/μl and captured cells were imaged using an Olympus IX71 microscope to assess cell number and quality. .. Fluidigm’s standard STA script was modified using C1 Script Builder (Fluidigm) so that the total capture volume was increased fourfold. .. Preamplified cDNA samples from single cells were analyzed by qPCR using 96.96 Dynamic Array IFCs and the Biomark HD System from Fluidigm.

    Staining:

    Article Title: Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies.
    Article Snippet: The C1 Single-Cell Auto Prep system (Fluidigm, San Francisco, CA, USA) was used to isolate and process transduced T cells on a Fluidigm 10- to 17-mm Single-Cell Open App Integrated Fluidic Circuit (IFC). .. A custom-made thermal protocol was designed with the C1 Script Builder (Fluidigm) to perform cell capturing, staining, and processing. ..

    Article Title: Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies
    Article Snippet: The C1 Single-Cell Auto Prep system (Fluidigm, San Francisco, CA, USA) was used to isolate and process transduced T cells on a Fluidigm 10- to 17-μm Single-Cell Open App Integrated Fluidic Circuit (IFC). .. A custom-made thermal protocol was designed with the C1 Script Builder (Fluidigm) to perform cell capturing, staining, and processing. ..



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    Figure 3. Single-Cell Vector Copy Number Assay on Two Cell Samples (A) Diagram of the scVCN workflow. The steps in the light blue box are performed within the <t>closed</t> <t>Fluidigm</t> <t>C1</t> system. ddPCR analysis is performed on each single-cell preamplified material on the QX200 Bio-Rad system. (B and C) Single-cell VCN values from each duplex assay combination are shown for the low (B) or the high (C) pVCN samples, whereas the values from bulk gDNA analysis (gray) include all six combinations and are shown as reference. Combinations originating from RG1 are in light blue, whereas the combinations with RG2 are in dark blue. Each boxplot is represented with mean and standard deviation. (D and E) The mean of the six scVCN combinations is shown for each single cell in the low (D) and high (E) pVCN samples and represented with standard error and 95% confidence interval. Single cells are ordered by increasing mean values. (F and G) Proportion of single cells with predicted vector copy units determined by Bayesian analysis in the low (F) and high (G) pVCN samples. The percentage of single cells with five or more vector copies is grouped. pVCN from bulk population analysis is indicated at the bottom with the standard deviation, alongside the mean of the single-cell VCN predictions. See also Figure S3.
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    Figure 3. Single-Cell Vector Copy Number Assay on Two Cell Samples (A) Diagram of the scVCN workflow. The steps in the light blue box are performed within the <t>closed</t> <t>Fluidigm</t> <t>C1</t> system. ddPCR analysis is performed on each single-cell preamplified material on the QX200 Bio-Rad system. (B and C) Single-cell VCN values from each duplex assay combination are shown for the low (B) or the high (C) pVCN samples, whereas the values from bulk gDNA analysis (gray) include all six combinations and are shown as reference. Combinations originating from RG1 are in light blue, whereas the combinations with RG2 are in dark blue. Each boxplot is represented with mean and standard deviation. (D and E) The mean of the six scVCN combinations is shown for each single cell in the low (D) and high (E) pVCN samples and represented with standard error and 95% confidence interval. Single cells are ordered by increasing mean values. (F and G) Proportion of single cells with predicted vector copy units determined by Bayesian analysis in the low (F) and high (G) pVCN samples. The percentage of single cells with five or more vector copies is grouped. pVCN from bulk population analysis is indicated at the bottom with the standard deviation, alongside the mean of the single-cell VCN predictions. See also Figure S3.
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    Figure 3. Single-Cell Vector Copy Number Assay on Two Cell Samples (A) Diagram of the scVCN workflow. The steps in the light blue box are performed within the closed Fluidigm C1 system. ddPCR analysis is performed on each single-cell preamplified material on the QX200 Bio-Rad system. (B and C) Single-cell VCN values from each duplex assay combination are shown for the low (B) or the high (C) pVCN samples, whereas the values from bulk gDNA analysis (gray) include all six combinations and are shown as reference. Combinations originating from RG1 are in light blue, whereas the combinations with RG2 are in dark blue. Each boxplot is represented with mean and standard deviation. (D and E) The mean of the six scVCN combinations is shown for each single cell in the low (D) and high (E) pVCN samples and represented with standard error and 95% confidence interval. Single cells are ordered by increasing mean values. (F and G) Proportion of single cells with predicted vector copy units determined by Bayesian analysis in the low (F) and high (G) pVCN samples. The percentage of single cells with five or more vector copies is grouped. pVCN from bulk population analysis is indicated at the bottom with the standard deviation, alongside the mean of the single-cell VCN predictions. See also Figure S3.

    Journal: Molecular therapy. Methods & clinical development

    Article Title: Vector Copy Distribution at a Single-Cell Level Enhances Analytical Characterization of Gene-Modified Cell Therapies.

    doi: 10.1016/j.omtm.2020.04.016

    Figure Lengend Snippet: Figure 3. Single-Cell Vector Copy Number Assay on Two Cell Samples (A) Diagram of the scVCN workflow. The steps in the light blue box are performed within the closed Fluidigm C1 system. ddPCR analysis is performed on each single-cell preamplified material on the QX200 Bio-Rad system. (B and C) Single-cell VCN values from each duplex assay combination are shown for the low (B) or the high (C) pVCN samples, whereas the values from bulk gDNA analysis (gray) include all six combinations and are shown as reference. Combinations originating from RG1 are in light blue, whereas the combinations with RG2 are in dark blue. Each boxplot is represented with mean and standard deviation. (D and E) The mean of the six scVCN combinations is shown for each single cell in the low (D) and high (E) pVCN samples and represented with standard error and 95% confidence interval. Single cells are ordered by increasing mean values. (F and G) Proportion of single cells with predicted vector copy units determined by Bayesian analysis in the low (F) and high (G) pVCN samples. The percentage of single cells with five or more vector copies is grouped. pVCN from bulk population analysis is indicated at the bottom with the standard deviation, alongside the mean of the single-cell VCN predictions. See also Figure S3.

    Article Snippet: A custom-made thermal protocol was designed with the C1 Script Builder (Fluidigm) to perform cell capturing, staining, and processing.

    Techniques: Plasmid Preparation, Standard Deviation