11768 results for "cancer rna-seq"

in 32.71 milliseconds.

• Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study

  Study population The WECARE Study is an international multicenter population-based case-control study of cases with asynchronous contralateral breast cancer (CBC) and individually matched controls with unilateral breast cancer (UBC). Recruitment and data collection for the WECARE Study were conducted in two phases, herein referred to as WECARE I (2001–2004) and WECARE II (2009–2012). The study design of the first phase (WECARE I) has been described in detail elsewhere [Bernstein JL, et al 2004, PMID: 15084244]; the second phase (WECARE II) employed a nearly identical approach [Langballe R, et al 2016, PMID: 27400983]. Participants in each phase were identified through eight population-based cancer registries, including six in the United States that contribute to the National Cancer Institute's Surveillance, Epidemiology, and End Results (SEER) program: Los Angeles County Cancer Surveillance Program; Cancer Surveillance System of the Fred Hutchinson Cancer Center (Seattle region, WA); State Health Registry of Iowa; Cancer Surveillance Program of Orange County/San Diego-Imperial Organization for Cancer Control (Orange County/San Diego, CA); the Greater Bay Area Cancer Registry (San Francisco Bay Area region and Santa Clara region, CA); and the Sacramento and Sierra Center Registry (Sacramento region, CA). Participants were additionally identified using the Ontario Cancer Registry (Canada) and the Danish Breast Cancer Cooperative Group Registry, supplemented by data from the Danish Cancer Registry. The study protocol was approved by the institutional review or regulatory ethics boards at each study site. Data collection Study participants were interviewed by telephone using a structured questionnaire aimed at evaluating known or suspected breast cancer risk factors, including personal demographics, medical history, menstrual and reproductive history, family history of cancer, use of hormones, smoking, and alcohol intake. Risk factor status was assessed during the period prior to first diagnosis, as well as between first diagnosis and reference date (i.e., the at-risk period for CBC). Detailed data on treatment and tumor characteristics were obtained directly from cancer registry records or by abstracting medical records, including pathology and surgical reports, radiation oncology clinic notes, and systemic adjuvant treatment data. Complete medical treatment history information was collected, and for all women who received radiotherapy, the radiation dose to the contralateral breast was reconstructed using radiotherapy records and radiation measurements. Biospecimens were collected from study participants for genotyping: blood collected from WECARE I women; and saliva collected from WECARE II women.

  Study phs003945

• Whole transcriptome seq from patient samples

  Exome sequencing data from FFPE preserved patient samples and patient-derived cultures. The goal of the study is to validate patient-derived cultures. Additional goal is to understand the relationship between omics and drug response.

  Study EGAS50000000172

• Highly complex single-cell mixture of 5 individuals of low cell number

  Mixture of 5 unrelated individuals sequenced by 10x as a scATAC-seq with low cell count. The dataset was then processed by Cell Ranger and deconvoluted to yield each individuals genetic profile using the De-goulash pipeline. The separation file is submitted as the processed file. The bam are submitted as unprocessed files.

  Dataset EGAD50000000479

• Paired-end Whole Exome-seq analysis of the 3D evolution of glioma cell populations. Part 1.

  Dataset contains Exome sequencing data (aligned and base quality score recalibrated BAM files) for 236 tumor samples + matched normal from blood, collected from 21 patients with adult diffuse glioma. The majority of these samples were spatially-mapped during sample collection, enabling the genomic information derived from them to be mapped in 3D space.

  Dataset EGAD00001005221

• WGA_Fulani_Database

  In total, 329 DNA samples were genotyped on the Illumina Infinium H3Africa Consortium array (designed for 2,271,503 SNPs; using BeadChip type: H3Africa_2019_20037295_B1). Genotyping was performed at the SNP&SEQ Technology Platform (NGI/SciLifeLab Genomics, Sweden). WGA Fulani dataset includes individuals from the following populations: 33 BurkinaFaso_FulaniBanfora, 32 BurkinaFaso_FulaniTindangou, 33 Mali_FulaniDiafarabe, 35 Cameroon_FulaniTcheboua, 34 Chad_FulaniBongor, 24 Chad_FulaniLinia, 25 Niger_FulaniAbalak, 32 Niger_FulaniAder, 31 Niger_FulaniDiffa, 20 Niger_FulaniBalatungur, and 30 Niger_FulaniZinder.

  Dataset EGAD50000000654

• Batch-corrected read-count matrix of the RNAseq Datasets of CLUSTER JIA pre-MTX cohort

  Samples were sequenced with NovaSeq6000 and the sequencing files were processed using the RSSnextflow workflow (https://gitlab.com/b8307038/rssnextflow). The raw read counts from all batches were combined. Analysis-ready batch-corrected read counts were generated using ComBat-seq.

  Dataset EGAD50000002169

• McGill Sperm Methylome Capture Sequencing Data

  The study includes methylC-capture sequencing (MCC-Seq) on 94 sperm DNA samples derived from both fertile and infertile individuals who were recruited from the Men’s Health Clinic at the Royal Victoria Hospital, Montreal, Quebec. All the data were generated with 100bp paired-end reads using the Illumina NovaSeq 6000 systems.

  Dataset EGAD00001005795

• scRNA-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell gene expression was produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006452

• scRNA-seq dataset to study interactions between HSPCs, BMSCs and immune microenvironment

  Mechanisms of clonal evolution in myeloid neoplasms remain incompletely understood. Darwinian theory predicts that the (micro)environment of clone-propagating stem cells may contribute to clonal selection. Here, we provide data fitting this model, establishing a relationship between stromal niche inflammation, inflammatory stress in HSPCs, clonal resistance and leukemic evolution in human MDS.

  Dataset EGAD00001015770

• Dataset for the study - Detection of cell-free DNA fragmentation and copy number alterations in cerebrospinal fluid from glioma patients

  FASTQ files from sequencing to < 0.4x depth of coverage of thirteen glioma patients. Indexed sequencing libraries were prepared using a commercially available kit (ThruPLEX-Plasma Seq, Rubicon Genomics). Libraries were pooled in equimolar amounts and sequenced on a HiSeq 4000 (Illumina) generating 150-bp paired-end reads.

  Dataset EGAD00001004425

• scTCR-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell T cell receptor clonotypes were produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006451

• The landscape of cancer genes and mutational processes in breast cancer

  The landscape of cancer genes and mutational processes in breast cancer

  Dataset EGAD00001000133

• Dataset for Manuscript: Cancer genome standards for long-read sequencing using cancer cell line mixtures

  Dataset for Manuscript: Cancer genome standards for long-read sequencing using cancer cell line mixtures

  Dataset EGAD00001015628

• Exome sequencing of 142 gastric cancer and matched normal from Japanese cohorts (UT)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 142 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002891

• Exome sequencing of 102 gastric cancer and matched normal from Japanese cohorts (YCU)

  As a contribution to the International Cancer Genome Consortium, exome sequencing of 102 Japanese gastric cancer with various histological subtypes have been conducted. This study aims to identify unique and common driver genes and molecular subtypes in Japanese gastric cancer. Please refer ICGC website for detail: http://icgc.org/icgc/cgp/69/420/1012357

  Study EGAS00001002892

• WGS of gastric cancer in the Japanese population (81 gastric cancers of NCC)

  As a contribution to The International Cancer Genome Consortium Accelerating Research in Genomic Oncology (ICGC ARGO), whole-genome sequencing of 81 cases from Japanese gastric cancer with various histological subtypes has been conducted. This study aims to reveal the landscape of structural variants (SV) in gastric cancer and analyze mutational and rearrangement signatures simultaneously

  Study EGAS00001006051

• RNA_sequencing

  All cancers arise due to somatically acquired mutations in their genomes which alter the function of key cancer genes. Understanding the critical mutational events underlying the development of cancer is paramount for advancing prevention, early detection and effective treatment of the disease. Breast cancer is the most common cause of cancer death among women. Extraordinary recent advances in sequencing now make it a realistic aim to sequence large numbers of breast cancer genomes to find somatic mutations on a massive scale. NB bam files for manuscript A_Proteomic_Chronology_of_Gene_Expression_through_the_Cell_Cycle_in_Human_Myeloid_Leukemia_Cells are now available at the following link:http://www.ebi.ac.uk/ena/data/view/ERP008483

  Study EGAS00001000310

• Single cell RNA sequencing of relapsed/refractory multiple myeloma

  Study EGAS00001004805

• SF6996

  RNA-exome

  Dataset EGAD00001006760

• SF9135

  RNA-exome

  Dataset EGAD00001006747

• SF10750

  RNA-exome

  Dataset EGAD00001006748

• SF10931

  RNA-exome

  Dataset EGAD00001006765

• SF4324

  RNA-exome

  Dataset EGAD00001006766

• SF12165

  RNA-exome

  Dataset EGAD00001006745

• SF8963

  RNA-exome

  Dataset EGAD00001006764

• Gene expression matrix

  Log2 gene expression count data from RNA sequencing.

  Dataset EGAD00001008793

• SF11094

  RNA-exome

  Dataset EGAD00001006755

• SF11780

  RNA-exome

  Dataset EGAD00001006757

• SF10770

  RNA-exome

  Dataset EGAD00001006761

• SF7196

  RNA-exome

  Dataset EGAD00001006762

• SF6587

  RNA-exome

  Dataset EGAD00001006772

• SF6839

  RNA-exome

  Dataset EGAD00001006769

• SF6136

  RNA-exome

  Dataset EGAD00001006754

• SF8642

  RNA-exome

  Dataset EGAD00001006749

• SF9490

  RNA-exome

  Dataset EGAD00001006753

• SF12243

  RNA-exome

  Dataset EGAD00001006758

• SF9301

  RNA-exome

  Dataset EGAD00001006759

• SF11215

  RNA-exome

  Dataset EGAD00001006763

• SF11587

  RNA-exome

  Dataset EGAD00001006770

• SF9640

  RNA-exome

  Dataset EGAD00001006771

• SE4987

  RNA-exome

  Dataset EGAD00001006835

• SE10497

  RNA-exome

  Dataset EGAD00001006834

• SF10228

  RNA-exome

  Dataset EGAD00001006756

• SE4831

  RNA-exome

  Dataset EGAD00001006830

• SE9581

  RNA-exome

  Dataset EGAD00001006837

• SE6136

  RNA-exome

  Dataset EGAD00001006833

• SE9037

  RNA-exome

  Dataset EGAD00001006832

• SF10064

  RNA exome

  Dataset EGAD00001006744

• SF4209

  RNA-exome

  Dataset EGAD00001006768

• SF10127

  RNA-exome

  Dataset EGAD00001006767