284 results for ""1,7"+million+WIPO+trademark+immersive"

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• CD49f single-cell methylomes

  Single-cell DNA methylation has emerged as a powerful tool to study molecular heterogeneity within cellular populations. We report the development of a bisulfite based whole genome protocol suitable for use on single index sorted primary mammalian cells. Application of this protocol to human hematopoietic stem cells provided quantitative DNA methylation measurements of up to 5.7 million CpGs in a single cell. Analysis of cis CpG methylation states in single cells revealed a loss of concordance beyond 2kb, which supported the development of a new analytical framework (PDclust) for single-cell DNA methylation datasets that considers heterogeneity of methylation states at single CpG resolution. PDclust identified epigenetically distinct subpopulations within highly purified and functionally defined human stem cell populations. In silico merging of the methylation states from the single cells allowed us to ascribe function to these epigenetically distinct subpopulations on the basis of their epigenetic states.

  Study EGAS00001002789

• Single cell RNAseq of PBMC from bladder cancer patients

  Frozen PBMC samples containing at least 1 million cells were thawed for 1 minute at 37C and washed twice with RPMI complete media (10% FBS with glutamate and Pen/Strep). All of the samples had >80% viable cells. Sample processing for single-cell RNA-seq was done using Chromium Single Cell 3’ Library and Gel bead kit v2 (PN-120237) following manufacturer’s user guide (CG00052, 10x Genomics, Pleasanton, CA). The total cell density was used to impute the volume of single cell suspension needed in the reverse transcription (RT) master mix, aiming to achieve ~ 6,000 cells per sample. cDNAs and libraries were prepared following manufacturer’s user guide (10x Genomics). cDNA amplification and indexed libraries were prepared using 12 and 14 cycles of PCR, respectively. Libraries were profiled, quantified, and sequenced as 5’ single-cell gene expression libraries.

  Study EGAS00001004008

• Single cell RNAseq of PBMC from RCC patients

  Frozen PBMC samples containing at least 1 million cells were thawed for 1 minute at 37C and washed twice with RPMI complete media (10% FBS with glutamate and Pen/Strep). All of the samples had >80% viable cells. Sample processing for single-cell RNA-seq was done using Chromium Single Cell 3’ Library and Gel bead kit v2 (PN-120237) following manufacturer’s user guide (CG00052, 10x Genomics, Pleasanton, CA). The total cell density was used to impute the volume of single cell suspension needed in the reverse transcription (RT) master mix, aiming to achieve ~ 6,000 cells per sample. cDNAs and libraries were prepared following manufacturer’s user guide (10x Genomics). cDNA amplification and indexed libraries were prepared using 12 and 14 cycles of PCR, respectively. Libraries were profiled, quantified, and sequenced as 5’ single-cell gene expression libraries.

  Study EGAS00001004451

• single nuclei RNASeq of 5 regions of the human prenatal brain

  Data generated through single nuclei RNA sequencing on 5 regions of the brain (frontal cortex, ganglionic eminence, hippocampus, thalamus and cerebellum) from 3 fetuses (two of 14 and one of 15 post-conception weeks, all female). Tissue was acquired from the MRC-Wellcome Trust Human Developmental Biology Resource (HDBR) with ethical approval. snRNA-seq libraries were prepared from ∼10,000 nuclei from each sample using Chromium Single Cell 3ʹ (v3) reagents (10X Genomics). Quality control of libraries was performed using the Agilent 5200 Fragment Analyzer before sequencing on an Illumina NovaSeq 6000 to a depth of at least 865 million (median = 1.01 billion) read pairs per library. Raw sequencing data were converted into FASTQ files. For a full description of data generation, please see Cameron et al, Biological Psychiatry 2022, https://doi.org/10.1016/j.biopsych.2022.06.033.

  Study EGAS00001006537

• HCC cfMeDIP-seq

  This dataset comprises 406 raw fastq files derived from 203 plasma cfDNA samples from 90 patients diagnosed with hepatocellular carcinoma (HCC). The samples include 90 baseline HCC (b-HCC) samples, collected during liver transplant or resection surgeries, and 113 postoperative follow-up (f-HCC) samples. For each sample, 10ng of cfDNA was used for library preparation utilizing cfMeDIP-seq technology based on the 5mC antibody-immunoprecipitation strategy. Libraries were validated via Bioanalyzer trace analysis and sequenced on Illumina NovaSeq 6000 or HiSeq 2500 platform with paired-end 150-bp (NovaSeq) or 125-bp (HiSeq) model for ~100 million reads per sample.

  Dataset EGAD50000000651

• Ribosomal profiling on Epstein-Barr virus transformed B-lymphoblastoid cell lines

  Epstein-Barr virus-transformed B-lymphoblastoid cell lines from six individuals (HG00114, HG00282, NA12005, NA12044, NA12717 and NA12751) of the GEUVADIS Project were selected for ribosomal profiling. For each EBV-LCL, 20 million cells were treated with 2 μg/ml harringtonine and 100 μg/ml cycloheximide. After lysing cells in lysis buffer supplemented with 100 μg/ml cycloheximide, ribosome complexes were purified by density purification. Small RNA molecules were isolated using the NucleoSpin miRNA Kit (Bioke, Leiden, Netherlands), followed by RNA PAGE gel separation. Universal linkers were added after dephosphorylation. After reverse transcription, the cDNA was circularized and, after ribosomal RNA depletion, barcoded and sequenced on Illumina NextSeq 500.

  Dac EGAC50000000209

• Single-cell atlas of > 1.5 million PBMC with multi-layer omics data in Japanese

  Osaka Atlas of Immune Cells (OASIS) is multi-omics immune cell atlas from 235 Japanese including COVID-19 patients and healthy subjects. The 5’ single-cell transcriptomics data profiled over 1,500,000 peripheral blood mononuclear cells (PBMCs). OASIS links these single-cell transcriptomics data with host genetics, plasma proteomics, and metagenomics data.

  Study EGAS00001008016

• Systematic comparative analysis of single-nucleotide variant detection methods from single-cell RNA sequencing data

  In this study, we performed systematic comparative analysis of seven widely-used SNV-calling methods, including SAMtools, the GATK Best Practices pipeline, CTAT, FreeBayes, MuTect2, Strelka2 and VarScan2, on both simulated and real single-cell RNA-seq datasets. We generated SMART-seq2 data for 70 CD45- single cells, which were derived from two colorectal cancer patients (P0411 and P0413). The average sequencing depths of these cells were 1.4 million reads per cell. We also generated tumor and adjacent normal bulk WES data, as well as tumor bulk RNA-seq data for these patients.

  Dataset EGAD00001005373

• Genotype data for The admixture histories of Cabo Verde - genotype data

  Datasets used in the article "The genetic and linguistic admixture histories of the islands of Cabo Verde" by Laurent R et al. eLife 2023 (DOI: https://doi.org/10.7554/eLife.79827 - URL: https://elifesciences.org/articles/79827) As per Materials and Methods herein, the genotype data corresponds to 2,118,722 autosomal SNPs genotyped from the IlluminaOmni 2.5 Million BeadChip for 233 Cabo Verdean volunteer participants, family unrelated at the 2nd degree based on population genetics analyses (see Material and Methods). SNP rsID, Chromosome position and genetic position in (bp) are in Build GRCh38. Cabo Verdean individuals are designated with an alphanumeric unique code

  Dataset EGAD00001008979

• CCA ChIP-seq data (63 CCA, 8 normal, 19 cell-line)

  Fastq files for H3K27ac ChIP-seq (with matched input-DNA control) for 63 CCAs, 8 normal bile duct tissues, 16 CCA cell-lines (including replicates), and 3 normal cholangiocyte cell-lines (including replicates). Library prep was performed with the NEBNext ChIP-seq library preparation kit. Each library (including matching input DNA) was sequenced to an average depth of 20 to 30 million raw reads on Illumina HiSeq4000 sequencer, with paired-end sequencing (except for 3 normal bile tissues done with single-end sequencing).

  Dataset EGAD00001012103