4777 results for "*oma"

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• Whole exome sequencing (bam files) of 55 samples of myxofibrosarcoma and 44 matched pairs

  Whole exome sequencing data (bam files) of 55 samples of myxofibrosarcoma and 44 matched pairs.

  Dataset EGAD00001007824

• Single cell targeted RNA sequencing

  Single cell hybrid-capture targeted sequencing of CD19 CAR T-cell infusion products used for standard of care treatment for relapsed/refractory large B-cell lymphoma.

  Dataset EGAD00001006327

• Immune profiling reveals enrichment of distinct immune signatures in oral epithelial dysplasia

  The dataset contains transcriptomic information of 36 oral potentially malignant disorders (OPMD), 14 fibroepithelial polyps (FEP), and 6 early stage oral squamous cell carcinoma (OSCC) from the Asian population. Total RNA was extracted from formalin-fixed paraffin embedded (FFPE) tissue sections. RNA libraries were prepared using the NEB NextUltra RNA kit with Illumina Ribo-Zero rRNA removal as per manufacturer’s instructions. RNA sequencing was performed on the HiSeq2500 platform to generate paired-end 150 nucleotides reads and with a coverage of 50 million reads per sample. Uploaded bam files have been mapped to the GRCh38 human genome using TopHat2. Clinical and demographic data for these patients are available from the associated publications or by request.

  Dataset EGAD00001007970

• Dataset for leiomyosarcoma-RNA

  Rare cancer sequencing data of 87 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008849

• A practical guide for mutational signature analysis in hematological malignancies

  Analysis of mutational signatures is becoming routine in cancer genomics, with implications for pathogenesis, classification, prognosis, and even treatment decisions. However, the field lacks a consensus on analysis and result interpretation. Using whole-genome sequencing of multiple myeloma (MM), chronic lymphocytic leukemia (CLL) and acute myeloid leukemia, we compare the performance of public signature analysis tools. We describe caveats and pitfalls of de novo signature extraction and fitting approaches, reporting on common inaccuracies: erroneous signature assignment, identification of localized hyper-mutational processes, overcalling of signatures. We provide reproducible solutions to solve these issues and use orthogonal approaches to validate our results. We show how a comprehensive mutational signature analysis may provide relevant biological insights, reporting evidence of c-AID activity among unmutated CLL cases or the absence of BRCA1/BRCA2-mediated homologous recombination deficiency in a MM cohort. Finally, we propose a general analysis framework to ensure production of accurate and reproducible mutational signature data.

  Dataset EGAD00001005028

• Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient

  Genome and transcriptome sequence data from a metastatic pancreatic adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001008914

• Dataset for liposarcoma-RNA

  Rare cancer sequencing data of 40 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008854

• UAMS Smoldering Myeloma Timeline Cohort

  To better understand the pattern of genetic changes over time, we performed whole exome sequencing of sequential bone marrow samples from 9 patients taken overtime including some paired SMM/newly diagnosed MM/Relapse MM samples. Samples from 9 patients (9 controls and 53 tumors) underwent whole exome sequencing with an additional capture for the IGH, IHK, IGL, and MYC loci. DNA was obtained from either CD138+ cells from the bone marrow of smoldering myeloma patients through time (tumor) or from stem cell harvests or peripheral blood cells from the same patient (control). 100 ng of DNA was fragmented, end-repaired, and adapters ligated using NimbleGen's MedExome. After PCR amplification hybridized libraries underwent further amplification before being sequenced on a NextSeq500 (Illumina) using 75 bp paired end reads.

  Dataset EGAD00001005056

• Dataset for melanoma-RNA

  Rare cancer sequencing data of 49 runs in tumor/control pairs, which were uploaded to umbrella studies. The sequencing was always paired

  Dataset EGAD00001008858

• lcWGS inform data of neuroblastoma patients

  97 samples of individuals with ALT-positive neuroblastoma tumors, low coverage whole genome sequencing

  Dataset EGAD00001006638