14983 results for "cancer studies using rna-seq"

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• GEPs

  Gene Expression Profiles measured using Affymetrix HGU133plus2.0 Array

  Dataset EGAD00010002543

• SWEPIC_methylation_cases

  CASE SAMPLES methylation data using Illumina EPIC technology

  Dataset EGAD00010002639

• 59 CLPD-NK cases WGS & WTS data

  For the cohort of 59 samples, we performed TruSeq DNA PCR-Free whole-genome sequencing library preparation according to manufacturer’s instructions (llumina, ILMN, San Diego, CA) on the automated NGS Star liquid handling platform (Hamilton, Bonaduz, Switzerland) followed by 2x150 bp paired-end sequencing on the HiSeqX or NovaSeq6000 (ILMN). An average coverage of >100x was achieved. For whole transcriptome analysis, the TruSeq Total Stranded RNA kit was used, starting with 250 ng of total RNA, to generate RNA libraries following the manufacturer’s recommendations (ILMN). 2x100bp paired-end reads were sequenced on the NovaSeq 6000 with a median of 50 mio. reads per sample (ILMN).

  Dataset EGAD00001008558

• Colorectal cancer functional annotation - Micro-C

  Ultra high resolution Micro-C data from multiple colorectal cancer cell lines

  Study EGAS50000000206

• Pancreatic Cancer NGS WGS data

  Whole genome sequencing data for Pancreatic Cancer Samples exploring the tandem duplicator phenotype

  Study EGAS50000001078

• Division of Cancer Evolution National Cancer Center Research Institute Data Access Committee

  Data Access Committee for data from Division of Cancer Evolution, National Cancer Center Research Institute

  Dac EGAC50000000737

• Mixture of 2

  Mixture of 2 unrelated individuals sequenced by 10x as a scRNA-seq. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile. The clustering of SNPs is submitted as the processed file. The Sequencing fastqs are submitted as unprocessed files.

  Dataset EGAD00001008726

• Low-pass whole-genome DNA sequencing of cohesin-mutated and wildtype adult AMLs

  Low-pass whole-genome DNA sequencing of cohesin-mutated (STAG2 or RAD21 mutations) and wildtype (CTRL-AML) adult AMLs generated generated from ultrasound-fragmented genomic DNA. Samples were only sequenced shallow (20-40 Mio reads) Used for digital karyotyping and ChIP-seq background/copy-nuber normalization/correction.

  Dataset EGAD00001011207

• AML-PMP miRNA-Seq

  miRNA libraries of the AML-PMP project were sequenced on the Illumina HiSeq 2000 instrument, approximately 16 samples per HiSeq lane, to a median depth of 5.7 million reads per library.

  Dataset EGAD00001009772

• HiC-sequencing in human monocyte differentiation

  This dataset consists of in situ HiC-seq data from human monocytes, monocyte-derived dendritic cells as well as monocyte-derived cells that were subjected to siRNA treatment targeting CTCF or RAD21. In total, the data set includes 42 samples.

  Dataset EGAD00001007955

• scRNA-seq of nonhematopoietic cells in human lymph nodes and lymphoma

  Single-cell count data generated by the Cellranger (10X Genomics).

  Dataset EGAD00001008311

• ATAC-Seq on OCIAML-22 Fractions

  The donor AML patient (unsorted) that was used to generate OCI-AML22 was expanded for 3-4 months, then sorted for the indicated fraction (CD34p: CD34+; CD34m: CD34-)

  Study EGAS00001006511

• Using de novo assembly to identify structural variation of complex immune system gene regions

  Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity. Several factors contribute to this including inheritable structural polymorphism of the underlying genes. To investigate this we generated data for a single healthy European individual (identified as HV31) using multiple long-read (PacBio Sequel II and Oxford Nanopore), short-read (Illumina HiSeq and MGI G400) and linked-read (10X Chromium and stLFR) sequencing platforms, and optical mapping using the Bionano Saphyr platform. DNA was extracted from monocytes or from peripheral blood mononuclear cells. We used these data to assemble a set of regions encoding components of the immune system and to investigate structural variation. The raw data and analysis results are deposited here for generate research use. A complete description of these data and results can be found in the accompanying article at https://doi.org/10.1101/2021.02.03.429586.

  Study EGAS00001005046

• Perceptions, Prevalence, and Patterns of Cannabis Use among Cancer Patients in NCI-Designated Cancer Centers

  This study aimed to better understand the evolving landscape of cannabis use among patients undergoing cancer treatment across diverse geographic regions. It sought to characterize patterns of use, patient perceptions, and contextual influences such as legal status and provider engagement that affect cannabis use. Given the shifting legal environment, this study addresses a critical gap in the literature by providing data on how cancer patients integrate cannabis into their care. The available delivery methods of cannabis have also undergone dramatic changes and now include edibles, oils, tinctures, topicals, and inhaled forms. State-based policy changes are rapidly changing. Yet research on cannabis use by cancer patients across a variety of geographic settings remains limited. The extent of cannabis use, the perceived and real benefits and risks of use, potential interactions with cancer treatment and other medications, and impact on comorbid conditions are uncertain. Clinicians should be aware of the extent of use in order to assess potential drug-drug interactions, side effects, and contraindications; hence, an understanding of how cancer patients and clinicians engage in discussions about cannabis use is essential. Twelve NCI-designated cancer centers were awarded supplemental funding to conduct surveys assessing cannabis use among recently diagnosed cancer patients. Selected sites were in 8 states with varied legal status for medical and recreational cannabis use at the time of the survey. The 12 cancer centers independently received approval from their institutional review boards (IRB) and collected data from September 2021 to August 2023. Eligible participants were cancer patients or survivors who resided in their respective cancer center's catchment area. Cancer centers were responsible for sampling patients within their catchment area with the goal of 1,000 completed surveys. Ten out of 12 cancer centers drew probability samples of patients from patient lists defining their catchment area with some stratifying the sample in various ways including by cancer type, by sex, by race/ethnicity or by a combination of demographic variables.

  Study phs004046

• EGAD00010000748

  Genotyping using Illumina Human OmniExpress12v1.0

  Dataset EGAD00010000748

• EGAD00010000417

  Han Chinese samples using Illumina OMNIExpress (cases)

  Dataset EGAD00010000417

• EGAD00010000423

  Han Chinese samples using Illumina OMNIExpress (controls)

  Dataset EGAD00010000423

• Array_dataset_TS

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001261

• Infinium Omni2.5

  Case control samples using Infinium Omni2.5

  Dataset EGAD00010001198

• PDX-OmniExpress24

  Primary and PDX SqCC samples using Infinium OmniExpress-24

  Dataset EGAD00010001228

• Botswana Identifiler dataset

  Autosomal STR genotypes using 15 Identifiler loci

  Dataset EGAD00010001255

• Array_dataset_Male

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001260

• Array_dataset_Female

  DNAm Case samples using Illumina Infinium 450K

  Dataset EGAD00010001262

• Illumina_HumanCoreExome

  Genotyped samples using Illumina Infinium HumanCoreExome Beadchip

  Dataset EGAD00010001410

• PanNEN_Methylation

  Methylation data of tumors using illumina Infinium MethylationEPIC

  Dataset EGAD00010002253

• EpS_methylation_850K

  Methylation profile (array data using EPIC_850K) from tumour samples (epithelioid sarcoma)

  Dataset EGAD00010002571

• Genome-wide methylation detection and episignature analysis using PacBio long-read sequencing

  Study EGAS00001008250

• Metadata associated with sequencing data

  Metadata associated with 16SV4 ribosomal RNA gene sequencing and Long read microbiome whole metagenome sequencing of pediatric GI samples.

  Dataset EGAD50000000483

• EAC-scRNA

  This dataset contains single cell RNA-sequencing of EAC samples by 10x Genomics. Total number of files - 24. File format - FASTQ.

  Dataset EGAD50000000752

• BE-scRNA

  This dataset contains single cell RNA-sequencing of BE samples by 10x Genomics. Total number of files - 28. File format - FASTQ.

  Dataset EGAD50000000753