12004 results for "cancer rna-seq"

in 39.10 milliseconds.

• MESA colorectal cancer cfDNA EM-seq dataset

  This dataset contains the methylation sequencing data of 60 nonCancer and 70 colorectal cancer cfDNA samples. The methylation library is constructed by using NEBNext Enzymatic-seq Kit.

  Dataset EGAD00001009165

• Pancreatic cancer RNA sequencing

  Study EGAS00001004706

• Single-nuclei RNA sequencing of pheochromocytoma and paraganglioma arising from germline SDHB mutations

  10x genomics single-nuclei RNA sequencing of 9 SDHB-deficient non-metastatic and metastatic pheochromocytoma and paraganglioma. snRNA-seq was performed using the ‘Frankenstein’ protocol (dx.doi.org/10.17504/protocols.io.bqxymxpw). Briefly, nuclei were extracted from frozen tissues and subjected to fluorescence-activated nuclei sorting (FANS) using 4′,6-diamidino-2-phenylindole (DAPI). Sorting was performed using a BD FACSaria 2 instrument, sorting between 3000 and 10,000 nuclei per sample, capturing both diploid and tetraploid populations. FAN-sorted nuclei were immediately processed using either the 10x Chromium Single Cell 5’ (PN-1000006, 4 samples) or 3’ (PN-1000075, 4 samples) Library & Gel Bead Kit (10x Genomics, USA). Once processed, snRNA-seq libraries were sequenced on the Illumina Nova-Seq 6000 (Illumina, USA) using 150bp paired-end sequencing. This dataset contains raw sequencing reads in FASTQ format.

  Dataset EGAD50000000505

• TenK10K Phase 1:  Single Cell

  Understanding the genetic basis of gene expression can shed light on the regulatory mechanisms underlying complex traits and diseases. Single-cell resolved measures of RNA levels and single-cell expression quantitative trait loci (sc-eQTLs) have revealed genetic regulation that drives sub-tissue cell states and types across diverse human tissues. Here, we describe the first phase of TenK10K, the largest- to-date dataset of matched whole-genome sequencing (WGS) and single-cell RNA-sequencing (scRNA-seq). We leverage scRNA-seq data from over 5 million cells across 28 immune cell types and matched WGS from 1,925 individuals. This provides power to detect associations between rare and low-frequency genetic variants that have largely been uncharacterised in their impact on cell-specific gene expression. We map the effects of both common and rare variants in a cell type specific manner using SAIGE-QTL.

  Study EGAS50000001653

• PDAC organoid genomic heterogeneity

  Two primary tumor-derived PDAC organoids were subjected to SNP array, RNA-seq, and single-cell WGS

  Dataset EGAD00010002408

• SF10432 Wildtype Primary GBM Female, 50

  Single Cell-RNA Seq of Wildtype Primary GBM for Female, Age 50.

  Dataset EGAD00001006019

• RNAseq data for EGAS00001004572

  Bulk RNA-seq data of tumours in EGAS00001004572.

  Dataset EGAD00001006876

• KUI6280

  RNA seq data normal and hypomethylation

  Dataset EGAD00001009887

• INSPIRE RNA-seq tumors

  INSPIRE whole transcriptome sequencing of tumors

  Dataset EGAD00001006564

• 10X single-cell Multiome (RNA+ATAC) of cord blood-derived HSPC

  10X genomics chromium single-cell ATAC+RNA (Multiome) was use to prepare single-nucleus RNA- and ATAC-seq libraries, sequenced on an Illumina NovaSeq 6000 platform. BAM files are provided. Samples from 4 donors were sequenced after sorting for primitive HSPCs in 2 libraries, each with cells from 1 male and 1 female CB.

  Dataset EGAD50000002327