5735 results for "canc*"

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• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  ZPM WES Pilot consisting of 30 samples paired tumor/normal analyzed with WES at four different laboratories in Germany.

  Dataset EGAD00001011087

• SNP data for Breast cancer PRS

  SNP data for 313 loci required for calculation of the Breast cancer PRS

  Dataset EGAD00001008144

• Bulk BCR NGS data from metastatic breast tumours from donors with therapy-resistant lethal metastatic breast cancer.

  Bulk B Cell Receptor high-throughput sequencing data across 27 metastatic breast tumours obtained from 8 donors with therapy-resistant lethal metastatic breast cancer at the time of a warm autopsy. The 35 samples were sequenced on an Illumina MiSeq instrument and their raw FastQ files deposited here.

  Dataset EGAD00001010023

• Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Molecular analysis of cancer genomes in children with Lynch syndrome: exploring causal associations WGS

  Dataset EGAD00001010042

• Tracking early lung cancer metastatic dissemination in TRACERx using ctDNA dataset

  Whole-exome sequencing of tumour regions and deep targeted sequencing of plasma samples.

  Dataset EGAD00001010031

• Dataset_for_linked_WES_and_WGS_data_from_EGAS00001004813 which belong also to EGAS00001005537 for germline controls of rare cancers

  WES/WGS sequencing data of 37 germline runs, which were uploaded to umbrella studies. The sequencing was always paired. The WGS sequencing was on HiSeq X Ten using the Illumina TruSeq DNA Nano Kit. The WES Sequencing was on HiSeq4000 with Agilent Sureselect V5+UTR.

  Dataset EGAD00001010046

• Germline variants in patients with rare cancers - control samples WGS and WES

  The control samples (mostly blood) of 351 samples (paired WGS and WES sequencing) are in this dataset. The WGS was in nearly all cases at an Illumina HighSeq X Ten with the Illumina TruSeq Nano DNA Kit. The WES mostly on Illumina HighSeq 4000 with the Agilent SureSelect V5 plus UTRs Kit.

  Dataset EGAD00001010047

• RNA sequencing of high-risk paediatric cancers for identifying T-cell infiltration signatures

  Transcriptome profiling of 121 high-risk paediatric cancer samples for identifying T-cell infiltration signatures using poly-A capture by Truseq and sequenced on NextSeq 500

  Dataset EGAD00001010920

• The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes

  The dataset for Detecting Liver Cancer Using Cell-Free DNA Fragmentomes includes 444 BAM files from whole genome next-generation sequencing on the Illumina NovaSeq 6000. The samples analyzed include plasma samples from individuals with and without cancer.

  Dataset EGAD00001010931

• Reliable detection of somatic mutations in solid tissues by laser-capture microdissection and low-input DNA sequencing

  Somatic mutations accumulate in healthy tissues as we age, giving rise to cancer and potentially contributing to ageing. To study somatic mutations in non-neoplastic tissues, we developed a series of protocols to sequence the genomes of small populations of cells isolated from histological sections. Here, we describe a complete workflow that combines laser-capture microdissection (LCM) with low-input genome sequencing, whilst circumventing the use of whole-genome amplification (WGA). The protocol is subdivided broadly into 4 steps: tissue processing, LCM, low-input library generation and mutation calling and filtering. The tissue processing and LCM steps are provided as general guidelines which may require tailoring based on the specific requirements of the study at hand. Our protocol for low-input library generation utilises enzymatic rather than acoustic fragmentation to generate WGA-free whole-genome libraries. Finally, the mutation calling and filtering strategy has been adapted from previously published protocols to account for artefacts introduced via library creation. To date, we have used this workflow to perform targeted and whole-genome sequencing of small populations of cells (typically 100-1,000 cells) in thousands of microbiopsies from a wide range of human tissues. The low-input DNA protocol is designed to be compatible with liquid handling platforms and make use of equipment and expertise standard to any core sequencing facility. However, obtaining low-input DNA material via LCM requires specialized equipment and expertise. The entire protocol from tissue reception through whole-genome library generation can be accomplished in as little as a week, though 2-3 weeks would be a more typical turnaround time.

  Dataset EGAD00001006088