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• DATA FILES FOR SJINF RNASeq

  DATA FILES FOR SJINF RNASeq

  Dataset EGAD00001001098

• Deep sequencing of melanoma for driver mutations

  Deep sequencing of melanoma for driver mutations

  Dataset EGAD00001001445

• Australian genomes

  Mapped data (bam files) for high-throughput whole genome sequence data for 83 modern Aboriginal Australians

  Dataset EGAD00001002001

• Integrated Genomic and Transcriptomic Analysis of Small Cell Lung Cancer Reveals Inter- and Intratumoral Heterogeneity and a Novel Chemotherapy-Refractory Subtype

  We integrated histology, transcriptome, exome, and treatment outcomes of small cell neuroendocrine cancer (SCNC) from a range of metastatic sites, revealing complex intra- and intertumoral heterogeneity of neuroendocrine (NE) differentiation and transcriptomic subtypes (ASCL1, NEUROD1, POU2F3, YAP1 and ATOH1). High NE SCNCs were more likely to benefit from replication stress-targeted therapies, in contrast to non-NE tumors which were more likely to respond to immune response-targeted therapies.

  Study phs002541

• Landscape of somatic mutations and DNA copy number alterations and transcriptomic profiling identifies metabolic reprogramming as a hallmark of ibrutinib resistance

  Whole-exome sequencing (WES) was conducted on the clinical specimens of 14 cases that had sufficient isolated tumor DNA, including 7 ibrutinib-sensitive cases and 7 ibrutinib-resistant cases. Whole transcriptome sequencing (RNA-seq) was performed on clinical specimens isolated from 14 ibrutinib-sensitive and 7 ibrutinib-resistant cases. Unsupervised hierarchical clustering of MCL tumors using RNA-seq gene expression data showed a response-specific gene expression signature.

  Study EGAS00001003418

• In this study, we performed exon sequencing (WXS) of 80 paired Brain cancer tumors and adjacent normal tissues to identify novel potential biomarkers. We extracted mutational signatures which induce somatic mutations . Our study covers a comprehensive genetic framework that can be used in clinical trials and treatment modalities in Brain cancer.

  In this study, we performed exon sequencing (WXS) of 80 paired Brain cancer tumors and adjacent normal tissues to identify novel potential biomarkers. We extracted mutational signatures which induce somatic mutations . Our study covers a comprehensive genetic framework that can be used in clinical trials and treatment modalities in Brain cancer.

  Study EGAS00001002352

• Total RNA sequencing of 32 chronic lymphocytic leukemia (CLL) patients

  Peripheral blood mononuclear cells (PBMC) of CLL patients were isolated by density-gradient centrifugation over Linfosep (Biomedics, Madrid, Spain). B cells were purified with a CD19+ magnetic-bead system (MidiMACS, Miltenyi Biotec, Bergish Gladbash, Germany) according to the manufacturers’ instructions. Mean B-cell purity was >99% and the mean percentage of CD5+/CD19+ cells after purification was >98%, as measured by flow cytometry. Total RNA was extracted from purified cells in a single step using TriPure Isolation Reagent (Roche Applied Science, Vilvoorde, Belgium).Whole transcriptome sequencing libraries were prepared using the TruSeq Stranded Total RNA Sample Preparation Kit (Illumina). Libraries underwent 2 × 76 bp paired-end sequencing on a HiSeq 2500 instrument (Illumina). The median number of paired-end reads was 60.5 million (range, 49.7-79.7 million).

  Dataset EGAD00001004047

• Systemic mutagen exposures reported by normal kidney cell genomes - kidney cancer samples (whole-genome sequencing)

  Lifestyle, environmental and other exposures to exogenous mutagens generate somatic mutations in normal human cells in vivo and increase cancer risk. However, the global repertoire of exogenous mutagen exposures is uncertain. Using single-molecule duplex sequencing of normal kidney (n=319) and blood (n=272) samples from 10 countries, we show that kidney proximal tubule cells exhibit higher mutation rates than most normal cell types despite low cell division rates. Compared to cells from kidney glomeruli, medulla, distal tubules, or peripheral blood, proximal tubule cells show marked enrichment of mutational signatures due to the exogenous carcinogenic mutagens, aristolochic acids, and of several signatures of unknown causes. The results suggest the existence of multiple, common, systemically circulated mutagens affecting human populations and indicate that the genomes of kidney proximal tubule cells report such exposures with high sensitivity.

  Dataset EGAD00001015826

• Systemic mutagen exposures reported by normal kidney cell genomes - bulk kidney samples (NanoSeq)

  Lifestyle, environmental and other exposures to exogenous mutagens generate somatic mutations in normal human cells in vivo and increase cancer risk. However, the global repertoire of exogenous mutagen exposures is uncertain. Using single-molecule duplex sequencing of normal kidney (n=319) and blood (n=272) samples from 10 countries, we show that kidney proximal tubule cells exhibit higher mutation rates than most normal cell types despite low cell division rates. Compared to cells from kidney glomeruli, medulla, distal tubules, or peripheral blood, proximal tubule cells show marked enrichment of mutational signatures due to the exogenous carcinogenic mutagens, aristolochic acids, and of several signatures of unknown causes. The results suggest the existence of multiple, common, systemically circulated mutagens affecting human populations and indicate that the genomes of kidney proximal tubule cells report such exposures with high sensitivity.

  Dataset EGAD00001015825

• Mutational landscape of the transcriptome offers putative targets for immunotherapy of myeloproliferative neoplasms

  In this study, we aimed to comprehensively characterize in 113 myeloproliferative neoplasms (MPN) patients the mutational landscape of the granulocyte transcriptome using RNA sequencing data. We implemented workflows for fusion and variant calling, and differential splicing analysis for patients with hotspot SF3B1 mutations. Finally, we characterized the neoantigen landscape on individualized level taking each patient's HLA genotype (derived from the same RNA-seq dataset) into account.

  Study EGAS00001003486

• OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864

  OLD DATA FILES FOR SJMB - Superseded by EGAD00001001864

  Dataset EGAD00001000269

• RNAseq for 8 PDX

  RNAseq for #111, #1177, #206, #201, #29, #931, WO-19, WO-2

  Dataset EGAD50000000116

• Preeclampsia InterPregGen Consortium: GWAS meta-analysis summary statistics for European fetal preeclampsia cases versus controls and GWAS genotype data for European fetal preeclampsia cases

  Study EGAS00001001048

• sc-DECISION

  Data derived from PBMC and blood samples for the single cell and bulk RNAseq analysis for the sc-DECISION paper. https://doi.org/10.1101/2025.02.04.25321370

  Dac EGAC50000000642

• Pulldown_DNA_methylation_study_v2

  Pilot study to set up sequencing protocols for targeted pulldown methylation profiling

  Study EGAS00001000979

• PBMC_dual_10X_kit

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

  Study EGAS00001004834

• McGill EMC Release 4 for assay "H3K27ac"

  McGill EMC Release 4 for assay "H3K27ac"

  Dataset EGAD00001001298

• McGill EMC Release 4 for assay "H3K36me3"

  McGill EMC Release 4 for assay "H3K36me3"

  Dataset EGAD00001001295

• DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  DATA FILES FOR GRUBER SJAMLM7 RNASEQ

  Dataset EGAD00001003135

• McGill EMC Release 4 for assay "H3K9me3"

  McGill EMC Release 4 for assay "H3K9me3"

  Dataset EGAD00001001299

• McGill EMC Release 4 for assay "H3K4me1"

  McGill EMC Release 4 for assay "H3K4me1"

  Dataset EGAD00001001296

• WGS data for Glioblastoma (EGAS00001003953, H016)

  Whole genome sequencing data for 20 human glioblastoma patients.

  Dataset EGAD00001006545

• BLUEPRINT: DNaseI-seq for monocytes

  DNaseI-seq for monocytes

  Dataset EGAD00001000674

• Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset for "Genomic landscape of oral cancers" (CGI WGS)

  Dataset EGAD00001004339

• DATA FILES FOR Histone-NSD2_RNASeq

  DATA FILES FOR Histone-NSD2_RNASeq

  Dataset EGAD00001000655