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fluidigm c1 chip  (fluidigm)


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    fluidigm fluidigm c1 chip
    Fluidigm C1 Chip, 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/fluidigm+c1+chips/C1/pm40250790-150-12-12
    Average 96 stars, based on 2081 article reviews
    fluidigm c1 chip - by Bioz Stars, 2026-09
    96/100 stars

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    Related Articles

    other:

    Article Title: Tissue adaptation of regulatory and intraepithelial CD4⁺ T cells controls gut inflammation.
    Article Snippet: Using this pipeline, we processed 86 Fluidigm C1 chips and sequenced 4488 single nuclei to an average depth of 8.34million reads (table S1 and fig. S5).

    Article Title: Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.
    Article Snippet: Using this pipeline, we processed 86 Fluidigm C1 chips and sequenced 4488 single nuclei to an average depth of 8.34million reads (table S1 and fig. S5).

    RNA Sequencing:

    Article Title: Dissecting the heterogeneity and tumorigenesis of BRCA1 deficient mammary tumors via single cell RNA sequencing
    Article Snippet: .. Luminal cells or tumor cells were sorted out and captured on Fluidigm C1 chips for RNA-seq libraries preparation. ..

    Article Title: Signalling by senescent melanocytes hyperactivates hair growth.
    Article Snippet: The libraries were sequenced on the Illumina Next-Seq500 system to an average depth of 10–30 million reads per library using paired 43-bp reads. .. For single-cell RNA-seq, cells were captured using the Fluidigm C1 chips as per the manufacturer’s protocol. ..

    Single Cell:

    Article Title: Signalling by senescent melanocytes hyperactivates hair growth.
    Article Snippet: The libraries were sequenced on the Illumina Next-Seq500 system to an average depth of 10–30 million reads per library using paired 43-bp reads. .. For single-cell RNA-seq, cells were captured using the Fluidigm C1 chips as per the manufacturer’s protocol. ..



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    Image Search Results


    a) Single cell and barcode beads are co-encapsulated by microfluidics platform. The primers on the barcode beads are equipped with handles for library preparation and single cell barcode and ended with rDS (red) or polyT5C8N (blue), which target both polyA+ and polyA-RNA transcripts. b) Gene-body coverage across all genes based on merged single cells data showing strong 3’ bias for inDrops and mostly uniform with a small 3’ bias for sc-rDSeq. Each gene is divided into 40 segments and counts failing into each segment are calculated for coverage. Ribbon area shows the SEM around mean. c) The boxplot displays nUMI/cell for sc-rDSeq and inDrops. On average, sc-rDSeq captures 90k nUMI/cell, inDrops captures 7.4k nUMI/cell. d) Distribution of uniquely mapped reads in each type of genomic locations with merged single cells data. e) Percentage of genes detected by sc-rDSeq compared to inDrops. f) Histogram showing normalized distribution of the fraction of transcripts per biotype expressed in single cells, comparing sc-rDSeq to inDrops. g) Cost comparison of sc-rDSeq and other single RNA-seq technologies. Top bars (red) for instrument cost, and bottom bars (blue) for library and sequencing cost per cell. h) UMAP of PC9 cells (n = 680) based on total transcriptome, revealing four clusters of populations. i) Differentially expressed genes were identified using KNN unsupervised clustering of total transcriptome expression. The average expression of selected marker genes for each cluster are presented in dot plot. j) Top five GO terms enriched in each cluster, ranked by fold enrichment. k) The average expression of polyA-RNAs showed heterogeneity, including histone RNAs, lncRNAs, sncRNAs, and microRNAs.

    Journal: bioRxiv

    Article Title: Expanding single-cell toolbox with a cost-effective full-length total RNA droplet-based sequencing technology

    doi: 10.1101/2025.02.23.639726

    Figure Lengend Snippet: a) Single cell and barcode beads are co-encapsulated by microfluidics platform. The primers on the barcode beads are equipped with handles for library preparation and single cell barcode and ended with rDS (red) or polyT5C8N (blue), which target both polyA+ and polyA-RNA transcripts. b) Gene-body coverage across all genes based on merged single cells data showing strong 3’ bias for inDrops and mostly uniform with a small 3’ bias for sc-rDSeq. Each gene is divided into 40 segments and counts failing into each segment are calculated for coverage. Ribbon area shows the SEM around mean. c) The boxplot displays nUMI/cell for sc-rDSeq and inDrops. On average, sc-rDSeq captures 90k nUMI/cell, inDrops captures 7.4k nUMI/cell. d) Distribution of uniquely mapped reads in each type of genomic locations with merged single cells data. e) Percentage of genes detected by sc-rDSeq compared to inDrops. f) Histogram showing normalized distribution of the fraction of transcripts per biotype expressed in single cells, comparing sc-rDSeq to inDrops. g) Cost comparison of sc-rDSeq and other single RNA-seq technologies. Top bars (red) for instrument cost, and bottom bars (blue) for library and sequencing cost per cell. h) UMAP of PC9 cells (n = 680) based on total transcriptome, revealing four clusters of populations. i) Differentially expressed genes were identified using KNN unsupervised clustering of total transcriptome expression. The average expression of selected marker genes for each cluster are presented in dot plot. j) Top five GO terms enriched in each cluster, ranked by fold enrichment. k) The average expression of polyA-RNAs showed heterogeneity, including histone RNAs, lncRNAs, sncRNAs, and microRNAs.

    Article Snippet: The single cell isolation is based on Fluidigm C1 microfluidics chips, which has limited throughput, and the method does not incorporate UMIs for PCR deduplication.

    Techniques: Comparison, RNA Sequencing, Sequencing, Expressing, Marker