14982 results for "cancer studies using rna-seq"

in 18.08 milliseconds.

• Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities RNA-Seq

  Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically uniquely defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to Notch inhibitors, which corresponded to high expression of Notch receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

  Study EGAS00001006866

• GEI Studies - Psoriasis

  The GEI Studies Project was started as an NIH consortium involving 5 disease groups with funding provided through the Genes, Environment, and Health Initiative (GEI). The objective of the project was to optimize strategies for identifying rare variants as a follow up to genome-wide association studies (GWAS) using next-generation sequencing technology. One of the five targeted diseases, Psoriasis, is a multifactorial skin disease characterized by epidermal hyperproliferation and chronic inflammation that affects approximately 2% of Americans. Because only about one-third of all patients with psoriasis have a relative who is also affected with the disorder, psoriasis is not widely recognized as a genetic disease. However, previous research on families and identical twins has shown psoriasis has a strong genetic component, although environmental factors (such as infections, stress, and injuries) are also important. Although no definite psoriasis gene has yet been identified, research during the last ten years has revealed over forty potential gene locations that may contribute to the disease. Large amounts of data generated using next-generation sequencing technology would provide a more detailed characterization of sequence variation which would in turn increase the likelihood of detecting causative loci. With the presumption that rare variants are frequently the cause of a large portion of phenotypic variation, it was necessary to use large sample sets. In the main body of this study, we sequenced 4,966 samples (812 dermatologist-diagnosed cases of purely cutaneous psoriasis (PsC), 1,497 cases of rheumatologist-diagnosed psoriatic arthritis, 665 cases of cutaneous psoriasis with uncertain psoriatic arthritis status (PsV) and 1,992 controls) across 5.7 Mb of sequence containing 100 psoriasis candidate loci and 769 genes. For each candidate locus, we considered sequences within 250 kb of the strongest association signal. Within this window, three strategies were employed. For ten of the strongest psoriasis signals, we used a whole-region approach which included non-coding intergenic and intronic sequence. For four established loci of lesser significance, we targeted all full transcription units within the +/- 250 kb interval. For the remaining signals, we targeted the exons of all transcription units within the +/- 250 kb interval. Due to complexities of high-efficiency targeting of HLA genes we selected 5 specific candidate genes for sequencing near the HLA-C gene.

  Study phs000766

• LuCaP cell line ChIP-seq

  ChIP-seq of 2 LuCaP cell lines with different factors. LuCaP cell line 189.4 was ChIP-sequenced for 6 factors with different conditions as well as the input DNA (n=31 in total). LuCaP 189.4 ChIP-sequence experiments include; 3 H3K27ac/DMSO, 3 H3K27ac/vorinostat, 3 H3K27ac/dexamethasone, 3 H3K27ac/dexamethasone/vorinostat, 3 GR dexamethasone, 3 GR dexamethasone/vorinostat, 3 HDAC3/DMSO, 3 AR, 3 FOXA1, 3 H3K27ac and 1 input sample. LuCaP 35 ChIP-sequence experiments as well as input include (n=10 in total); 3 H3K27ac, 3 AR, 3 FOXA1 and 1 input sample. All 41 samples were sequenced using paired-end reads on Illumina NovaSeq 6000. Each sample has 2 fastq files, one for the forward and reverse read, respectively.

  Dataset EGAD50000001345

• Data access committee for "Detection of brain cancer using genome-wide cell-free DNA fragmentomes"

  The data access committee for “ Detection of brain cancer using genome-wide cell-free DNA fragmentomes”. The DAC is comprised of Drs. Dimitrios Mathios, Jillian Phallen, Victor Velculescu, Robert Scharpf, Noushin Niknafs, and Shashikant Koul, and can be contacted at skoul3@jh.edu.

  Dac EGAC50000000605

• DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  DNA WGS Short Read Sequence (Illumina NovaSeq) for manuscript titled: "Performance of Somatic Structural Variant Calling in Lung Cancer using Oxford Nanopore Sequencing Technology"

  Dataset EGAD00001015399

• CMF_RNA_sequencing

  RNA sequencing will be undertaken to reconstruct rearrangements at level of transcription to determine pathogenomic genomic events in chondromyxoid fibroma

  Study EGAS00001000470

• Collagen Proteostasis in Health and Disease

  This study uses human iPSC-derived cartilage to investigate the effects of the p.Arg719Cys mutation in the COL2A1 gene, which is linked to precocious osteoarthritis. Using a CRISPR-edited isogenic cell line pair, we compared wild-type and mutant cartilage for matrix defects and cellular stress responses. We performed RNA-sequencing and quantitative proteomics to characterize changes in gene expression, protein interactions, and collagen folding.

  Study phs004112

• Bulk RNAseq FASTQ files of three PDAC organoid lines treated with LGK974 or DMSO for 24h

  This dataset contains raw FASTQ files from bulk RNA sequencing of three patient-derived pancreatic ductal adenocarcinoma (PDAC) organoid lines (P28, P40, P47). Each organoid line was treated with either the WNT secretion inhibitor LGK974 or DMSO for 24 hours, with three biological replicates per treatment condition. RNA was extracted using the Qiagen QiaSymphony SP system, and libraries were prepared with the Illumina Truseq stranded polyA kit. Sequencing was performed on an Illumina NextSeq2000 platform using single-end 50bp reads. Quality control was conducted with FastQC, and reads were trimmed with TrimGalore as appropriate. Data are controlled-access and intended for transcriptomic analysis of WNT pathway perturbation in PDAC organoid models.

  Dataset EGAD50000002219

• Single-cell multi-omics reveals clonal evolution and T-cell dynamics underlying differential responses to ibrutinib in Waldenström macroglobulinemia.

  To elucidate the molecular basis underlying differential response and resistance to ibrutinib in Waldenström’s macroglobulinemia (WM), we conducted a prospective phase II trial (NCT02604511) of ibrutinib monotherapy in treatment-naïve patients. Seventy-four sequential bone marrow (BM) aspirates from 17 patients, collected from baseline through 48 treatment cycles, were profiled using single-cell RNA and V(D)J sequencing.

  Study EGAS50000001596

• Capture Hi-C on Hodgkin lymphoma cell line L-428

  In situ promoter capture Hi-C on Hodgkin lymphoma cell line L-428 in experimental triplicates. Hi-C libraries were prepared as previously described (Orlando et al., 2018, https://currentprotocols.onlinelibrary.wiley.com/doi/pdf/10.1002/cphg.63). Promoter capture was based on 32,313 biotinylated 120-mer RNA baits (Agilent). Hi-C libraries were sequenced using Illumina HiSeq 2000 technology. The files are in FASTQ format.

  Study EGAS00001003032

• Development and Use of Network Infrastructure for High-Throughput GWA Studies

  The "Development and Use of Network Infrastructure for High-Throughput GWA Studies" project is collaboration between Group Health Cooperative (GH), the University of Washington (UW), and the Fred Hutchinson Cancer Research Center (FHCRC). It is one of 5 sites participating in The Electronic Medical Records and Genomics (eMERGE) Network funded by the National Human Genome Research Institute (NHGRI) with additional funding from the National Institute of General Medical Sciences (NIGMS). The overall eMERGE project is designed to assess whether linking biorepositories of patients in healthcare delivery systems with electronic medical records (EMRs) is an efficient strategy for high-throughput genome wide association (GWA) studies and whether information can be pooled across sites. The primary phenotype in the Group Health/UW Aging and Dementia eMERGE study project is dementia. Phenotyped participants originated from four population-based sources. Seattle-area members of GH (a large integrated health care system in Washington State) consented and enrolled in 1) the University of Washington Alzheimer's Disease Patient Registry (ADPR) and 2) the Adult Changes in Thought (ACT) study, 3) Marshfield Clinic Personalized Medicine Research Project (PMRP), a population-based DNA, plasma and serum biobank of 20,000 adults, 4) Vanderbilt's BioVU, a de-identified DNA biobank. The ADPR (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is a population-based registry of incident dementia cases designed to identify all new dementia cases within GH from 1987 to 1996. Potential dementia cases were identified through referrals from primary care physicians, mental health services, and neurologists, as well as review of CT scans, neurology, emergency room, geriatrician, and mental health clinic logs, and hospital discharge diagnoses. Medical history, physical, laboratory testing, and neuropsychological testing were performed on all consenting potential cases. These data were reviewed by a consensus conference including a neuropsychologist, study physicians, and an epidemiologist. After discussion of the case, dementia status is assigned using DSM-III-R criteria. Alzheimer's disease status was assigned using the National Institute of Neurological and Communicative Disorders and Stroke-Alzheimer's Disease and Related Disorders Association (NINCDS-ADRDA) criteria. The study base of the ADPR population was stable with an attrition rate of less than 1%/year. The ACT study (PI: Eric B. Larson; NIH/NIA U01 AG 006781) is an ongoing community-based cohort study designed to determine the incidence of Alzheimer's Disease (AD), other types of dementia, and cognitive impairment and to determine risk factors for these conditions. The original cohort of 2,581 was enrolled in 1994-1996. An expansion cohort of 811 was enrolled in 2000-2002. Continuous enrollment to keep 2,000 persons enrolled and at-risk for dementia outcomes was begun in 2005. To date the study has accrued more than 4,000 participants. Dementia-free participants are enrolled in this cohort and evaluated every two years by study personnel with many evaluations including an assessment of cognitive functioning using the Cognitive Abilities Screening Instrument (CASI), which is an extended version of the Mini-Mental State Examination that has been widely used in epidemiological studies of the elderly. Persons with CASI scores lower than 86 or in whom interviewers suspect unusual cognitive decline are followed up with dementia diagnostic evaluations which include physical and neurological examinations and neuropsychological tests. Medical records are reviewed, and laboratory tests and neuroimaging are obtained if not available. The dementia diagnoses and dementia subtypes are determined during a consensus conference attended by the examining clinicians and other study physicians, a neuropsychologist, and research nurse. After discussion of the case, dementia status is assigned using DSM-IV criteria. Alzheimer's disease status was assigned using NINCDS-ADRDA criteria. Individuals diagnosed with dementia are seen again one year following diagnosis using the same procedures. Individuals not diagnosed with dementia are returned to the pool of at-risk individuals and are seen at their next routinely scheduled biennial visit. The ACT sub-sample is stable; for the original cohort, median enrollment in GH was 19 years prior to joining the ACT study, and 85% of the cohort has ≥ 10 years of GH enrollment. DNA for the ADPR participants were obtained through a companion study, Genetic Differences in Cases and Controls (PI: Walter Kukull; NIH/NIA R01 AG007584). DNA obtained through both studies were extracted from blood using Gentra Systems Puregene methods. DNA concentration is determined by UV optical density. All samples are checked for quality by OD 260/280 ratio. For long-term storage, samples are aliquoted and stored at -70°C. The Marshfield study, Personalized Medicine Research Project (PMRP), a population-based DNA, plasma and serum biobank of 20,000 adults. PMRP was started in 2002 as a 3 Phase project. Completed in April 2004, the objectives of Phase I were to build and develop a large population-based biobank with DNA, plasma and serum samples to facilitate genomics research. Phase 1 was also to educate, inform and consult with the Marshfield Epidemiologic Study Area population and communities concerning potential studies, create the DNA foundation of the personalized medicine database and build the bioinformatics tools to store securely and analyze genotypic and phenotypic data. Phase I tasks included operation of the ethics and security advisory board, scientific advisory board and community advisory group. More than 18,000 residents aged 18 and above from 19 different zip codes surrounding Marshfield, WI were invited to participate in Phase I. After providing written informed consent, participants completed brief questionnaires that included questions about demographics, some environmental exposures, family history of disease, and adverse drug reactions, as well as family members living in the area. Participants provided 50ml of blood from which DNA was extracted and plasma and serum samples were stored. The informed consent process allowed access to electronic medical records and included language about non-disclosure of personal research results. A tick-off box was included so that participants could either allow or decline subsequent recontact for future research studied. The objectives of Phase II are to create the phenotypic database, establish the scientific and administrative infrastructure to support genetic mapping of the DNA and the initial discovery projects and genotype a sufficient portion of the genetic material to support these discovery projects. The objectives of Phase III are to expand the discovery projects, complete the genotyping of the genetic database and expand physician/health care provider education and community consultation. The Vanderbilt BioVU model uses discarded blood leftover from clinical care and de-identified clinical information, both of which are tracked with a Research Unique Identifier that is permanently disconnected from the medical record number used to generate it. The Vanderbilt IRB determined that the project does not qualify as "human subject" research under §46.102(f)(1)(2). The program has been reviewed by OHRP twice (the latest immediately prior to launch), and the determination of the Vanderbilt IRB that the project is consistent with the 8/10/2004 guidance has been validated. The model includes a simple opt out mechanism developed for patients who do not wish to have their samples included. Planning (including community involvement, ethics and IRB discussions, focus groups, development of operating procedures and pilot studies to assess them) began in May 2004, and the resource commenced sample collection in February 2007 and as of May 2009 contains approximately 56,000 samples. The current resource will be available to all Vanderbilt investigators who sign a Data Use Agreement. The resource represents Vanderbilt's broad patient population and thus provides a potential resource for research in a range of common and rare diseases as well as drug response or medication safety. BioVU patient protection model: There has been extensive involvement by the ethics community and the IRB to put in place procedures to provide privacy protection. The overall protection plan is multifaceted and includes a combination of technology and policy: (1) creation of the SD described above; (2) return of only the specific clinical data items requested by investigators (rather than the complete de-identified chart); (3) submission of any specific proposed project to the IRB and to a separate protocol review committee, both of which must approve; (4) implementing a Data Use Agreement that permits only approved queries and data analyses, specifically prohibits attempts at re-identification (at the risk of institutional sanctions), and mandates redeposit of all genetic information generated in a research study back into a genomic database; and (5) tracking and auditing all use.

  Study phs000234

• Organoid drug profiling identifies methotrexate as a therapy for SCCOHT, a rare pediatric cancer

  Small cell carcinoma of the ovary, hypercalcemic type (SCCOHT) is a rare and lethal tumor in adolescent and young adult patients. Currently, there is no standard-of-care treatment for these patients. Reliable models that represent this disease and can be used for translational research are scarce. To model SCCOHTs, we have established eight patient-derived tumoroid lines from tumor lesions of three patients with SCCOHT. The tumoroids recapitulate genomic and transcriptomic characteristics of the corresponding patient tumors and capture intrapatient tumor heterogeneity. Organoid drug profiling using a library of 153 clinical compounds identified methotrexate as an effective and selective drug against SCCOHTs with a clinically relevant IC50 of 35 nmol/L. RNA sequencing demonstrated that methotrexate induced TP53 pathway activation and apoptosis. These data underscore that organoid technology can support the design of therapeutic strategies for rare cancers.

  Study EGAS00001007911

• Single-cell and spatial transcriptomic profiling of hormone-naïve localised prostate cancer

  Localised prostate cancers (PCa) are heterogeneous and multifocal, with diverse outcomes. Current prognostic methods are epithelium-centric, overlooking the complex cellular landscape within the tumour microenvironment (TME), which remains incompletely characterised. We performed a comprehensive analysis of cancerous and adjacent-benign cores from 24 patients with hormone therapy-naïve localised PCa using single-cell RNA-sequencing. By integrating copy number variation and transcriptional signatures, we classified epithelial cells across a malignant spectrum, revealing widespread molecular perturbation. We found an expansion of Club cell phenotypes, suggestive of Luminal dedifferentiation. We also performed a detailed annotation of stromal phenotypes, focusing on fibroblasts, and identified a novel peri-neural fibroblast population. Spatial transcriptomics elucidated the precise anatomical distribution of CAFs within the PCa TME. This study provides a valuable foundation for advancing our understanding of PCa pathobiology and developing a comprehensive cellular model of the disease.

  Study EGAS00001008332

• Single-Cell and Bulk RNA Sequencing of Oncolytic Measles Virus Treatment in Pediatric Medulloblastoma and ATRT

  This dataset includes single-cell RNA sequencing profiles from five mice bearing Group 3 medulloblastoma (CSCG) treated with oncolytic measles virus (MV-NIS) and three mice treated with MV-NIS combined with anti-PD1 therapy. Additionally, bulk RNA sequencing data were generated from 12 samples across PBS control, heat-inactivated (HI) control, MV mid-treatment, and treatment resistance conditions. Pediatric patient data were collected from the PNOC005 trial, which enrolled patients into three strata: Stratum A (focal recurrence, local MV-NIS administration post-surgical resection), Stratum B (disseminated recurrence, single MV-NIS dose via lumbar puncture), and Stratum C (disseminated recurrence, two consecutive MV-NIS doses via lumbar puncture on Day 0 and Day 7). Whole blood and PBMC samples were collected from 17 patients across all strata, generating 72 bulk RNA-seq datasets at multiple time points. All datasets are provided as raw sequencing data in FASTQ format.

  Dataset EGAD50000001197

• RNASeq profiles from Indian HFrEF Cohort

  The dataset contains whole transcriptomics profiling from a cohort of 49 HFrEF patients. The myocardium samples were collected from these patients during heart transplant of LVAD implantation procedure. The RNA samples were collected in RNAlater. Total transcriptome libraries were prepared using TruSeq Stranded Total RNA Library Prep with Ribo-Zero Gold kit and sequenced on Illumina HiSeq4000.

  Dataset EGAD50000001196

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005738

• Genome-wide cell-free DNA termini in patients with cancer

  The structure, fragmentation pattern, length and terminal sequence of cell-free DNA (cfDNA) is under the influence of nucleases present in the blood. We hypothesized that differences in the diversity of bases at the end of cfDNA fragments can be leveraged on a genome-wide scale to enhance the sensitivity for detecting the presence of tumor signals in plasma. We surveyed the cfDNA termini in 72 plasma samples from 319 patients with 18 different cancer types using low-coverage whole genome sequencing. The fragment-end sequence and diversity were altered in all cancer types in comparison to 76 healthy controls. We converted the fragment end sequences into a quantitative metric and observed that this correlates with circulating tumor DNA tumor fraction (R = 0.58, p < 0.001, Spearman). Using these metrics, we were able to classify cancer samples from control at a low tumor content (AUROC of 91% at 1% tumor fraction) and shallow sequencing coverage (mean AUROC = 0.99 at >1M fragments). Combining fragment-end sequences and diversity using machine learning, we classified cancer from healthy controls (mean AUROC = 0.99, SD = 0.01). Using unsupervised clustering we showed that early-stage lung cancer can be classified from control or later stages based on fragment-end sequences. We observed that fragment-end sequences can be used for prognostication (hazard ratio: 0.49) and residual disease detection inresectable esophageal adenocarcinoma patients, moving fragmentomics toward a greater clinical implementation.

  Study EGAS00001005747

• RNA sequencing of Non-Small Cell Lung Cancer and adjacent normal tissue

  RNA sequencing was performed on 108 NSCLC tumor samples and their paired adjacent normal tissues (n=21) to identify associations with clinical and immune characteristics.

  Study EGAS50000000246

• Uncovering Inversion Formation in the Human Genome and its Impact to Disease

  The relevance of inversions for disease causation, speciation and adaptation is broadly recognized, although the prevalence of inversions is unknown. In humans, de novo inversions are associated with congenital anomalies in approximately 9.6% of patients. Yet, despite the biological relevance of inversions, their molecular features, formation mechanism, impact to the genomic structure of carriers, as well as their contribution to clinical phenotypes, have not been further explored. Inversions are typically classified as balanced reciprocal events generated by ectopic recombination, although recent studies reveal a distinct picture whereby inversions originate from mechanisms that concomitantly generate copy number variants (CNVs). Surprisingly, those complex inversions underlie as much as 30% of neurodevelopmental-associated CNVs. The hypothesis of this project are: inversions are often generated de novo by mechanisms other than ectopic recombination a relevant fraction of inversions are associated with complex genomic rearrangements (CGRs), often overlooked in sporadic diseases, and inversions are a "hidden" type of structural variation for which contribution to a clinical phenotypes has been under assessed due to the lack of appropriate detection tools. A combined strategy using multiple genomic tools will be applied to characterize inversions and associated genomic alterations in individuals with neurodevelopmental disorders and controls: whole genome sequencing (WGS) with short-and long-reads; genome mapping; classical cytogenetics; and array CGH. This project will establish common ground to bridge studies of rare and common diseases, human evolution, and population genetics.

  Study phs002999

• WES and RNA-seq of pre-invasive lung adenocarcinoma

  The prevalence of lung adenocarcinoma (LUAD) has increased sharply in East Asia. Early diagnosis leads to better survival rates, but this requires an improved understanding of the molecular changes during early tumorigenesis, particularly in non-smokers. We performed whole exome-sequencing and RNA-sequencing of samples from 94 East Asian patients with precancerous lesions (25 with atypical adenomatous hyperplasia [AAH]; 69 with adenocarcinoma in situ [AIS]) and 73 patients with early invasive lesions (minimally invasive adenocarcinoma [MIA]). This datasets contains the sequencing raw data (FASTQ format).

  Dataset EGAD50000000637

• atrial appendage miRNA-seq in non-, paroxysmal and persistent atrial fibrillation

  64 left atrial appendages from patients without atrial fibrillation (AF) undergoing cardiac surgery, patients with paroxysmal AF and with persistent AF (~20 per group). Trizol RNA isolation, size selection, single end miRNA sequencing on 4 lanes of illumina NextSeq 500. Provided are FastQ files, one per lane per sample. Additional data (e.g. clinical characteristics, RIN values etc.) can be provided upon request. The same RNA samples (62) were used for transcriptome sequencing. Results from transcriptome sequencing are stored in the EGA database and are managed by the same DAC.

  Dataset EGAD00001007694

• RNA and ChIP Sequencing datasets from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

  This dataset contains the RNA and ChIP Sequencing data from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma. The data is organized in 7 experiments which are divided by both sequencing technology or the application of siRNA or drug interventions (or lack thereof) on neuroblastoma cell lines. The experiment names and the file names have been chosen in each respective experiment to guide future users of the data to replicate the analyses in the manuscript.

  Dataset EGAD00001006964

• Whole genome, RNA-seq and single-cell Multiome profile of multiple myeloma

  We analyzed multiple myeloma samples from two patients included in the observational prospective cohort MYRACLE before talquetamab treatment and after relapse. Five other myelomas from the same cohort were included for comparison. Normal plasma cells were also retrieved. All samples were analyzed by whole genome sequencing and single-nucleus Multiome, except one that could only be analyzed by bulk RNA sequencing.

  Dataset EGAD00001010057

• Genome-wide DNA-methylation assessment by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison

  DNA-methylation is an important epigenetic feature in health and disease. Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). However, objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples obtained from 65 glioblastoma and 5 non-tumoral brain tissues, using a gold standard free Bayesian modeling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. Also the genome-wide characteristics were compared, revealing that the HM450 probes assess less than 10% of the regions identified as methylated by MethylCap-seq. Hence the latter method may detect more potentially relevant DNA-methylation, defined by either functional location or previously reported differentially methylated candidate regions. Our results therefore indicate that – at least for the tissue under study - both methodologies are complementary, with a higher sensitivity for HM450, but a far larger genome-wide coverage for MethylCap-seq. Note that here only the relevant MethylCap-seq data is deposited, for the HM450 data we refer to GEO (GSE60274).

  Study EGAS00001001191

• Combining transcription factor binding affinities with open chromatin data for accurate gene expression prediction

  The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid cost and labour intensive TF ChIP-seq assays.It is important to develop reliable and fast computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices.TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq, using either peaks or footprints as input.In addition to open-chromatin data, also Histone-Marks (HMs) can be used in TEPIC to identify candidate TF binding sites.TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength.Using machine learning techniques, we show that incorporating low affinity binding sites improves our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites.Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance.In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets.Finally, we show that these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

  Study EGAS00001002073