11810 results for "cancer rna-seq"

in 12.78 milliseconds.

• B-ALL bone marrow and CNS xenograft RNA sequencing

  This dataset includes TruSeq paired-end, total RNA sequencing data from primary B-precursor acute lymphoblastic leukaemia (B-ALL) xenografts. It comprises 43 pairs of matched bone marrow (BM) and central nervous system (CNS) human leukaemia cells from individual immunodeficient mice. Xenografts were generated from 6 patients with B-ALL and include samples taken at diagnosis and relapse from 3 of 6 patients.

  Dataset EGAD00001008183

• IG-MYC ALL - DNA and RNA sequencing

  The dataset is composed by the raw RNA sequencing (n=6), targeted DNA sequencing (n=18) and whole exome sequencing (n=17) from 19 patients with IG-MYC-rearrangements.

  Dataset EGAD00001008705

• Multi-modal single-cell analysis of salivary glands from patients with Sjogren's syndrome

  Sjogren's syndrome (SS) is an autoimmune disease that causes salivary gland dysfunction due to immune-mediated destruction. In this study, we apply multi-modal single-cell technologies - single-cell RNA sequencing and T-cell receptor sequencing - to salivary gland lesions, aiming to uncover transcriptional signatures and TCR sequence linked to autoantibody profiles.

  Study JGAS000808

• Investigation of relapse prediction in infants with MLL-rearranged Acute Lymphoblastic Leukemia

  In infants with ALL, accurate relapse prediction would enable treatment strategies that take relapse risk into account, with potential benefits for both low- and high-risk patients. Through analysis of bone marrow biopsies taken at initial diagnosis, we show that single-cell RNA sequencing can predict future relapse occurrence.

  Study EGAS00001003986

• Multiomics analyses of Parkinson's disease midbrains

  Understanding the key pathological mechanisms underlying Parkinson's Disease pathology is fundamental for the development of novel and more effective therapeutic strategies. In this study, post-mortem human midbrain tissue from a cohort of 13 PD patients and 10 controls was analyzed with a set of multi-omics technologies including small RNA sequencing, transcriptomics and proteomics profiling.

  Study EGAS00001004966

• 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

• Isolation of bacteria in infected brains in patients with Parkinsons disease. Here we used next generation sequencing of 16S ribosomal RNA gene PCR amplicons (NGS 16S amplicon analysis).

  Dac EGAC00001001197

• Direct RNA sequencing of 10 postmortem human brain samples

  Contains fast5 data for each of the 10 samples sequenced.

  Dataset EGAD00001015347

• RNA sequencing BRAF fusion partners

  Contains RNAseq data for 14 transduced/non-transduced organoids

  Dataset EGAD00001005380

• GBM Up and Down Responder EZH2 ChIPseq

  ChIPseq using anti-EZH2 with a sheared input DNA control to assess EZH2 genomic biding in one longitudinal pair of samples (pre- and post-treatment) from one UP and one DOWN responder GBM patient

  Dataset EGAD50000000134