Search Results - EGA European Genome-Phenome Archive

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90706

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 522 samples; filetype=bam

Dataset EGAD00001004744

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 626 samples; filetype=bam

Dataset EGAD00001004748

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 636 samples; filetype=bam

Dataset EGAD00001004754

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2057 samples; filetype=bam

Dataset EGAD00001004720

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 561 samples; filetype=bam

Dataset EGAD00001004757

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96150A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 656 samples; filetype=bam

Dataset EGAD00001004764

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75617A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 692 samples; filetype=bam

Dataset EGAD00001004727

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 232 samples; filetype=bam

Dataset EGAD00001004725

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95722A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 968 samples; filetype=bam

Dataset EGAD00001004755

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96139A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1436 samples; filetype=bam

Dataset EGAD00001004762

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96145A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 589 samples; filetype=bam

Dataset EGAD00001004763

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 648 samples; filetype=bam

Dataset EGAD00001004765

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 612 samples; filetype=bam

Dataset EGAD00001004728

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90553C

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1700 samples; filetype=bam

Dataset EGAD00001004729

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95670A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 615 samples; filetype=bam

Dataset EGAD00001004753

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95624A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 604 samples; filetype=bam

Dataset EGAD00001004747

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95724A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 480 samples; filetype=bam

Dataset EGAD00001004756

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96187A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

Dataset EGAD00001004770

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1222 samples; filetype=bam

Dataset EGAD00001004743

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 628 samples; filetype=bam

Dataset EGAD00001004730

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 928 samples; filetype=bam

Dataset EGAD00001004759

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90685

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 481 samples; filetype=bam

Dataset EGAD00001004738

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96156B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 375 samples; filetype=bam

Dataset EGAD00001004766

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96165A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 755 samples; filetype=bam

Dataset EGAD00001004767

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90560B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 766 samples; filetype=bam

Dataset EGAD00001004734

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90648B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 620 samples; filetype=bam

Dataset EGAD00001004736

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 378 samples; filetype=bam

Dataset EGAD00001004739

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90694A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 493 samples; filetype=bam

Dataset EGAD00001004742

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95736A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1072 samples

Dataset EGAD00001004761

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A96171A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 492 samples; filetype=bam

Dataset EGAD00001004768

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 230 samples; filetype=bam

Dataset EGAD00001004724

Clinal phenotype dataset

Clinical data from IMvigor010: Clinical data include race, sex, baseline ecog, tumor stage, node status, prior neoadjuvant, PD-L1 status, number lymph nodes resected, pridis, arm, overall survival and disease free survival for 809 patients across IMvigor010.

Dataset EGAD00001007576

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 596 samples; filetype=bam

Dataset EGAD00001004731

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A75616C

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 239 samples; filetype=bam

Dataset EGAD00001004726

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90682

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 624 samples; filetype=bam

Dataset EGAD00001004737

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689C

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 718 samples; filetype=bam

Dataset EGAD00001004741

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90689B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 735 samples; filetype=bam

Dataset EGAD00001004740

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 606 samples; filetype=bam

Dataset EGAD00001004752

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 465 samples; filetype=bam

Dataset EGAD00001004751

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73044A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1340 samples; filetype=bam

Dataset EGAD00001004719

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95621B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 488 samples; filetype=bam

Dataset EGAD00001004745

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632D

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples; filetype=bam

Dataset EGAD00001004749

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A90554C

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1735 samples; filetype=bam

Dataset EGAD00001004732

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95622A

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 509 samples; filetype=bam

Dataset EGAD00001004746

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95732B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples

Dataset EGAD00001004760

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73046B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1970 samples; filetype=bam

Dataset EGAD00001004721

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73047D

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 2091 samples; filetype=bam

Dataset EGAD00001004722

Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A73056B

Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1267 samples; filetype=bam

Dataset EGAD00001004723

MicroRNA profiling by next-generation sequencing for colorectal cancer screening

The dataset contains raw miRNA sequencing data of plasma samples from 20 newly diagnosed colorectal cancer cases and 20 controls free of colorectal neoplasms matched by age and sex. It includes files in the FASTQ compressed (.gz) format.

Dataset EGAD00001006966

Healthy control cfMeDIP-seq

This dataset comprises 46 raw fastq files derived from 23 plasma cfDNA samples from 23 healthy (CTL) cancer-free donors. For each sample, 10ng of cfDNA was used for library preparation utilizing the cfMeDIP-seq technology based on the 5mC antibody-immunoprecipitation strategy. Libraries were validated via Bioanalyzer trace analysis and sequenced on the Illumina NovaSeq 6000 platform with paired-end 150-bp model for ~100 million reads per sample.

Dataset EGAD50000000652

Single-cell T-cell receptor sequencing of intraepithelial gammadelta T-cells in celiac disease

Single-cell paired TCR sequencing of intraepithelial γδ T-cells in gluten-free diet treated and untreated celiac disease patients and in controls. (Paired end, amplicon sequencing).

Study EGAS00001003897

106 mouse cases and 10 human cases

Consists of 76 mouse plasma cell-free DNA, 30 mouse Liver DNA, 10 human plasma cell-free DNA

Dataset EGAD00001008838

Whole genome sequencing data for five Japanese subjects

WGS was performed for five Japanese subjects. DNA samples isolated from whole blood were sequenced at Macrogen Japan Corporation. All libraries were constructed using the TruSeq DNA PCR-Free Library Preparation Kit according to the manufacturer’s protocols. Libraries were sequenced on HiSeqX (Illumina, San Diego, CA, USA) or Novaseq6000 (Illumina, San Diego, CA, USA).

Dataset EGAD00001010075

Center for Common Disease Genomics [CCDG] - Cardiovascular: Pharmacokinetic Polymorphisms in Japanese General Population

This study is a part of NHGRI's Center for Common Disease Genomics, which is a collaborative large-scale genome sequencing effort to comprehensively identify rare risk and protective variants contributing to multiple common disease phenotypes. Current estimates anticipate that the CCDG program will sequence approximately 140K whole genomes and 225K whole exomes during the life of the project. The Cardiovascular Disease working group of the CCDG considered five diseases: early-onset coronary artery disease (EOCAD), stroke, atrial fibrillation, congestive heart failure and type 2 diabetes. Atrial fibrillation will affect between 6-12 million individuals in the US by 2050. AF also is associated with increased risks of stroke, dementia, heart failure, death, and high health care costs. Many risk factors for AF have been identified, including advancing age, cardiovascular disease (CVD), and CVD risk factors. However, there is little knowledge how to prevent AF. Furthermore, therapies for AF are only partially effective, and are themselves associated with substantial morbidity. Previously, heritable forms of AF have been considered rare; yet in the last decade, it has been established that AF, and in particular early-onset forms of AF, are heritable. Genome-wide association studies (GWAS) provide a powerful tool to identify common variants underlying disease risk. The AFGen Consortium currently consists of investigators from more than 25 studies with >20,000 individuals with AF and >100,000 without AF. In the latest analyses, 14 loci have been identified for AF1 . Broadly, the loci implicate genes related to cardiopulmonary development, cardiac-expressed ion channels, and cell signaling molecules.Source: https://ccdg.rutgers.edu/sites/default/files/CCDG_CVD_EOAF_FINAL_w_link.pdfAnalysis of 165 pharmacokinetic-related gene polymorphisms (the number of polymorphisms may increase) using DNA derived from the blood of approximately 1,000 Japanese general populations. Tokai University School of Medicine Molecular Life Sciences 2 Isogo Lab has been trying to find new genes which contribute to the development of multiple diseases and to develop new methods for human genome diversity analysis that will lead to the development of technology for disease screening by finding genes related to diseases and incorporating gene analysis technology. Using this method, we are trying to clarify the relationship between the characteristics of rheumatoid arthritis and psoriasis vulgaris and genes to seek effective treatments and prevention methods. Raw sequencing data, metadata, vcf and phenotype data at individual level are available at https://anvilproject.org/data. For questions about availability contact help@lists.anvilproject.org.

Study phs002985

Gluten-free microbiome study UMCG

Study EGAS00001005225

Finnish_population_cohort_genotyping_B

The FINRISK cohorts comprise the respondents of representative, cross-sectional populationsurveys that are carried out every 5 years since 1972, to assess the risk factors of chronicdiseases (e.g. CVD, diabetes, obesity, cancer) and health behavior in the working agepopulation, in 3-5 large study areas of Finland. DNA samples were collected in the followingsurvey years: 1987, 1992, 1997, 2002, 2007, and 2012. The MONICA and EHES (EU)procedures were applied in phenotype collection (cf. MORGAM) and a wide spectrum oflaboratory tests was carried out from serum and plasma samples. Background information onsocioeconomic status, medical history, diet, exercise, measured anthropometric measures,etc. was collected by questionnaires and during a clinical visit. Plasma/serum samples arestill available for the 2002-2012 cohorts. The cohort sizes are 6000-8800 per survey. Thecohorts have been followed up by linking them to the national hospital discharge register,causes-of-death register and cancer register.This project is an extension to previous efforts to build a catalogue of Finnish genome widedata on population-based Finsrisk samples with rich phenotypic characterisations and healthregistry link-up. These samples will extend the current Sequencing Initiative Suomi (SISu)samples with a combination of genotyping using Illumina HumanCoreExome array and SISu-based imputation. This will lead to high confidence common and low frequency variantcatalogue. The project will be funded by Aarno Palotie’s remaining faculty fundscomplemented by Finnish funding from FIMM.

Study EGAS00001001047

Copy number variations and fragmentation features in cell-free DNA predict response in advanced non-small cell lung cancer patients under anti-PD-(L)1 therapy

Anti-PD-(L)1 therapy is routinely used in metastatic NSCLC. However, response rates vary and biomarkers predicting treatment efficacy are lacking. Liquid biopsies allow monitoring of residual disease during therapy. Residual circulating tumor DNA (ctDNA) after therapy represents a predictive marker for adverse outcome. Here, we assessed copy number variations (CNVs) in serial plasma samples of NSCLC patients receiving PD-(L)1 blockade. We profiled CNV and fragmentation features in 118 plasma samples of advanced NSCLC patients by low-coverage whole genome sequencing taken at baseline, after four therapy cycles and at disease progression. CNVs and fragment features (i.e., fragment length, end motifs, position) were significantly altered in patients compared to healthy donors. Furthermore, fragment length changes at baseline and residual CNVs after four therapy cycles correlated with short progression-free survival. Our results highlight the suitability of plasma-based CNV and fragment analysis for disease monitoring and as a predictive marker for response duration in NSCLC patients under anti-PD-(L)1 therapy.

Study EGAS50000000441

Clinical utility of combined low-pass whole genome and targeted sequencing in liquid biopsies for diagnosis and monitoring of pediatric solid tumors

We designed a liquid biopsy (LB) platform employing Low-Pass Whole Genome Sequencing (LP-WGS) and targeted sequencing of cell-free (cf) DNA isolated from plasma for detecting genome-wide copy number alterations and targeted gene fusions in pediatric solid tumors. A total of 143 plasma samples were analyzed from 19 controls (patients with non-oncologic diagnoses) and 73 patients, including 44 with bone or soft tissue sarcomas, 12 with renal tumors, 10 with germ cell tumors, 5 with hepatic tumors, and 2 with thyroid tumors.

Study EGAS00001006913

Error-corrected flow-based sequencing at whole genome scale and its application to circulating cell-free DNA profiling

Differentiating sequencing errors from true variants is a central genomics challenge calling for error suppression strategies that balance costs when sparse material or ultra-rare variants require high-accuracy methods. For example, circulating cell-free DNA (ccfDNA) sequencing for cancer monitoring is limited by sparsity of circulating tumor DNA (ctDNA), abundance of genomic material in samples, library preparation error rates and sequencing errors. Whole-genome sequencing (WGS) can overcome the low abundance of ccfDNA by integrating signal across the mutation landscape, but higher cost limits adoption compared with targeted panels, where ccfDNA abundance limits maximal coverage depths. Here we applied deep (~120x) lower-cost WGS (Ultima Genomics) with analytic error correction for tumor-informed ctDNA detection within the part-per-million range. We further developed high-coverage duplex error-corrected WGS of ccfDNA, achieving 7.7x10-8 error rates, to assess disease burden in melanoma and urothelial cancer patients without matched tumor sequencing. Together, we show that deeply sequenced error-corrected WGS accurately calls somatic variants, demonstrating the feasibility of WGS for tumor-informed and tumor-agnostic ctDNA detection.

Study EGAS50000000844

Assessment of RNA-Seq Sample Preparation Methodology

The goal of this study was two-fold, to determine if common purification techniques have any effect on downstream differential expression analysis and to evaluate combinations of alignment and differential expression software for reliability. To this end, blood was collected from three individuals and pooled during and after extraction. After pooling and mixing was completed, samples were divided into three aliquots for testing. The first aliquot was a control and not purified or concentrated. It was diluted to produce samples of varying concentrations for testing. The second aliquot was diluted to 20 ng/μL and used to test six different variations on the AMPure XP bead purification procedure. The last aliquot was also diluted to varying concentrations of 60, 30, and 9.6 ng/μL and purified using MinElute columns. Samples were submitted for total RNA-Seq library preparation and sequencing. Library preparation was performed using the TruSeq Stranded Total RNA with Ribo-Zero Globin kit (20020612, Illumina Inc.), and 2x150 bp PE sequencing was done on an Illumina NovaSeq 6000 with the S4 reagent kit. Comparisons were made between methods (AMPure vs. unpurified, AMPure vs. MinElute, MinElute vs. unpurified) to assess the effects of purification method on downstream differential expression. Comparisons were also made within methods using the varying concentrations tested for unpurified samples and for MinElute purified samples to assess the effects of concentration on differential expression. Variations of the AMPure procedure were also compared to assess the effectiveness of the variations tested in comparison to the unmodified procedure. A subset of samples was selected for use with alignment and differential expression package comparison. Unpurified high concentration samples eluted in RNAse-free water were compared to unpurified high concentration samples eluted in BR5, a buffer from the PAXgene blood miRNA kit, with the expectation that there should be no or very few differentially expressed genes. Unpurified high concentration samples eluted in RNAse-free water were also compared to unpurified low concentration samples also eluted in RNAse-free water, with possibly a small number of differentially expressed genes anticipated. A third dataset of simulated RNA-seq data was created with a known rate of differential expression. These files were aligned using Bowtie2, HISAT2, kallisto, RSEM, Rsubread, Salmon, and STAR. Results were then analyzed for differential expression using ALDEx2, baySeq, DEGseq, DESeq2, edgeR, limma, NOISeq, PoissonSeq, and SAMseq. Differential expression results of all three comparisons were evaluated to determine which combinations provided the most reliable results for both real and simulated data.

Study phs003001

Fragmentomics analyses of urinary cell-free DNA permit multi-urologic cancer detection and reduction in tissue biopsies for prostate cancer

This study demonstrated the close association between urinary cell-free DNA (cfDNA) methylation status and the fragmentation patterns in healthy controls and patients with various diseases. Fragmentomics-based methylation analysis (FRAGMA) enables accurate estimation of methylation levels in urinary cfDNA, which is proved by paired bisulfite sequencing and non-bisulfite sequencing data. FRAGMA showed high accuracy in deducing tissue-of-origin of urinary cfDNA in transplantation patients and pregnant women. Moreover, FRAGMA showed great potential in the detection and classification of multiple cancers from the urinary system, including bladder, kidney, and prostate cancer. This study demonstrated that FRAGMA could be applied to improve current diagnostic strategies based on urine samples.

Study EGAS50000001431

Mitochondrial DNA sequencing of iPSC, parental cells, and iPSC derived cardiomyocytes

The aim of this work was to analyze to which extent mitochondrial DNA (mtDNA) variants in human induced pluripotent stem cells (iPSC) originate from their parental cells or from de novo mutagenesis, and whether dynamics in variant heteroplasmy levels during prolonged expansion culture of iPSC are caused by inter- or intra-cellular selection or genetic drift. Hence, mtDNA of 26 early passage iPSC clones from, in total, 10 donors and the corresponding parental cell populations (here endothelial cells) were sequenced. Furthermore, 7 iPSC clones were expanded up to passage 50 and the change in variant heteroplasmy levels was monitored. Lastly, the effect of differentiation on the variant heteroplasmy levels was investigated during directed cardiomyocyte differentiation of 4 iPSC clones.

Study EGAS00001005560

'IL-17A-Producing ILC3s and Duodenal Adenoma in FAP'

Familial Adenomatous Polyposis (FAP) is a hereditary tumor syndrome that significantly enhances the risk of duodenal adenomas, with variations observed even among carriers of the same genetic variant. In this study, intestinal ILCs were isolated from 82 FAP and 26 non-FAP patients and analyzed through flow cytometry, qRT-PCR, and bulkRNA-sequencing. The data revealed a heightened frequency of ILC3s in FAP patients, and increased IL-17A production of duodenal NKp44(-)ILC3s was associated with FAP. Significant elevations in IL1B, IL23A, and DLL4 mRNA expression levels were found in FAP duodenal adenoma tissue, along with enhanced expression of DUOX2 and DUOXA2. The results suggest the involvement of IL-17A-producing NKp44(-)ILC3s in duodenal adenoma formation in FAP.

Study EGAS00001007347

Cell-free DNA Sequencing Data Access Committee

Dac EGAC00001003304

Characterization of CNS Metastases

Metastatic disease to the central nervous system (CNS) is devastating, with a poor prognosis. There are limited treatment options for patients with CNS metastases, and in particular with leptomeningeal carcinomatosis (LMD). In this study, we evaluated the molecular and cellular features of parenchymal brain metastases and LMD. We used single-cell RNA and cell-free DNA profiling of CSF from patients with LMD receiving immunotherapy to demonstrate shifts in the liquid LMD tumor microenvironment. We also characterize the tumor microenvironment of parenchymal brain metastases using single cell sequencing, before and after treatment with immunotherapy.

Study phs002416

Single Nucleus Transcriptomes from the Ventral Midbrain of Opioid Overdose Cases and Controls

We generated ventral midbrain single nuclei RNA-seq libraries for 95 brain donors, including 45 subjects with documented histories of opioid abuse and overdose, and 50 demographically-matched, opioid-free control subjects, collected from two geographically distinct regions within the U.S. (greater Detroit area, Michigan and Miami, Florida). Each sample included both substantia nigra and the adjacent ventral tegmental area. Nuclei were processed in pools of 3-4 brains using the 10X Chromium system followed by Illumina sequencing, read alignment and processing by 10X Cellranger.

Study phs003260

Circulating tumour DNA abundance and potential utility in de novo metastatic prostate cancer

Several systemic therapeutic options exist for metastatic castration sensitive prostate cancer (mCSPC). Circulating tumour DNA can profile metastatic castration resistant prostate cancer and influence treatment decisions, but remains untested in mCSPC. We set out to determine ctDNA abundance at de novo mCSPC diagnosis and whether ctDNA provides complementary clinically relevant information to a prostate biopsy. We collected and sequenced 77 plasma cell-free DNA samples from 53 newly diagnosed patients with mCSPC. Targeted sequencing was also performed on DNA from 48 diagnostic prostate tissue samples.

Study EGAS00001003351

Multi-institutional collaboration to characterize 5hmC in prostate cancer, both tumor biopsies and cfDNA.

This study used pull-down sequencing to measure 5-hydroxymethylcytosine (5hmC) levels in tissue biopsy specimens from patients with localized and metastatic castration-resistant (mCRPC) prostate cancer. For a subset of the cohort, the same technique was used to sequence cell-free DNA (cfDNA) isolated from patient plasma. To assess 5hmC levels in cfDNA from a larger number of specimens, plasma samples from another mCRPC cohort were also assayed with this method. The larger cohort of cfDNA samples was further anlayzed with a targeted sequencing gene panel.

Study EGAS00001004942

Methylation Biomarkers can Distinguish Pleural Mesothelioma from Healthy Pleura and other Pleural Pathologies

Pleural mesothelioma (PM) is a rare cancer type. This study developed a methylation-based biomarker assay to distinguish PM from healthy pleura and other pleural conditions. By analyzing methylation data, 744 hypermethylated CpG sites specific to PM were identified and validated with high accuracy. Using the bisulfite-free IMPRESS technique, the assay was further validated in a diverse cohort, showing strong performance in distinguishing tumoral from non-tumoral samples and PM from pleural metastases. These findings support the assay’s potential as a robust diagnostic tool for PM.

Study EGAS00001008153

Division of Cancer Epidemiology and Genetics (DCEG) Imputation Reference Dataset

We have built a new resource for imputation of SNPs for existing and future genome-wide association studies (GWAS), known as the Division of Cancer Epidemiology and Genetics (DCEG) Reference Set. The first build of the data set includes 728 cancer-free individuals of European descent from three large prospectively sampled studies, 98 African-American individuals from the Prostate, Lung, Colon, and Ovary Cancer Screening Trial (PLCO), 74 Chinese individuals from a Chinese clinical trial in Shanxi, China (SHNX), and 349 unrelated individuals from the HapMap Project (see Molecular Data Section for details on arrays used). The final harmonized dataset includes 2.8 million autosomal polymorphic SNPs on 1,249 subjects after rigorous quality control metrics were applied.

Study phs000396

Case Study of Acquired Resistance to FGFR Inhibition in Cholangiocarcinoma using Targeted DNA and RNA Sequencing

Targeted sequencing was performed on blood, tumor, and cell free DNA samples from an FGFR2-fusion positive cholangiocarcinoma patient before and after treatment with an FGFR targeted therapy.

Study phs001924

Tumor Profiler Project - OV cell-free DNA data additional samples

The dataset contains amplicon sequencing data from 7 samples from 7 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format. These samples are from patients not classified as having high-grade serous adenocarcinoma.

Dataset EGAD50000001412

Genome-Wide Bisulfite Sequencing of Urinary Cell-Free DNA

The current sequencing dataset consists of 85 bisulfite sequencing data files (Fastq files) of human cell-free urine DNA samples. These extracted cfDNA samples were then constructed into DNA libraries using the KAPA HTP Library Preparation Kit (Kapa Biosystems) with bisulfite modification using the EpiTect Bisulfite Kit (Qiagen) and subsequently sequenced on the Nextseq500 platform (Illumina).

Dataset EGAD50000001902

Human lymphoma plasma cfRNA - raw data

This study contains total RNA sequencing data from plasma of 65 different human donors: 30 diffuse large B-cell lymphoma patients, 13 primary mediastinal large B-cell lymphoma patients and 22 cancer-free controls.

Study EGAS00001007127

Circulating tumor DNA in urine and plasma of glioma patients - sequencing data

Dataset consisting of sequence data from 36 glioma patients. Data includes; -Whole exome sequencing of tumour tissue and matched germline -Shallow whole genome sequencing of urine cell-free DNA -Targeted capture sequencing of plasma and CSF cell-free DNA Additional sequencing data are provided from non-glioma and healthy controls

Dataset EGAD00001006156

Single-cell T-cell receptor sequencing of intraepithelial CD8+ αβ T-cells in celiac disease

Single-cell paired TCR sequencing of intraepithelial CD8+ αβ T-cells in gluten-free diet treated and untreated celiac disease patients and in controls. (Paired end, amplicon sequencing).

Study EGAS00001004989

Extracellular transcriptome in seminal plasma for non-invasive prostate cancer diagnosis

A diagnostic non-invasive biomarker test for prostate cancer at an early stage, with high sensitivity and specificity, would improve diagnostic decision making. Extracellular RNAs present in seminal plasma might contain biomarker potential for the accurate detection of clinically significant prostate cancer. So far, the extracellular messenger RNA (mRNA) profile of seminal plasma has not been interrogated for its biomarker potential in the context of prostate cancer. Here, we investigate the mRNA transcriptome in seminal plasma samples obtained from prostate cancer patients (n=25), patients with benign prostate hyperplasia (n=26) and individuals without prostatic disease (n=6). Seminal plasma harbors a complex mRNA repertoire that reflects prostate as its tissue of origin. The endogenous RNA content is higher in the prostate cancer samples compared to the control samples. Prostate cancer antigen 3 (PCA3), a long non-coding RNA with prostate cancer-specific overexpression, and ATP-binding cassette transporter 1 (ABCA1), known to be involved in the prostate cancer pathogenesis, were more abundant in the prostate cancer group. In addition, twelve high confidence fusion transcripts could be detected in prostate cancer samples, including the bona-fide prostate cancer fusion transcript TMPRSS2-ERG. Our findings provide proof-of-principle that the extracellular transcriptome of seminal plasma can reveal information of an underlying prostate cancer.

Study EGAS00001005277

Ultra-Low-Pass Whole Genome Sequencing of Cell-Free DNA for Large B-Cell Lymphoma

While deep targeted DNA sequencing of liquid biopsies has shown prognostic utility in large B-cell lymphoma (LBCL), the routine clinical adoption of these assays remains limited due to their high costs. Here, leveraging a well-annotated cohort of encompassing both frontline and relapsed/refractory (R/R) LBCL, we profiled patient plasma samples with two complementary modalities – ultra-low-pass whole genome sequencing (ulpWGS) and deep targeted DNA sequencing, the former being a cost-effective method to profile large scale chromosomal abnormalities and estimate tumor burden. Our findings revealed a strong association of high cell-free tumor burden by both genomic profiling modalities with established measures of tumor burden and patient survival. Notably, the associations with survival remained statistically significant after accounting for international prognostic index scoring. Furthermore, we showed that del(17p) in circulating tumor DNA as detected by ulpWGS was strongly associated with TP53 mutation status and predicted for significantly inferior patient outcome in frontline but not R/R LBCL patients. Our study demonstrates that ulpWGS can provide robust prognostic biomarkers for both frontline and R/R LBCL, highlighting its broad applicability for risk stratification.

Study EGAS50000001027

Cell Free Plasma Methyl-DNA Data Access Committee

Dac EGAC00001002626

cfDNA methylation profiling in Metastatic Cancer and Cancer of Unknown Primary

This study contains methyl-binding domain sequencing and shallow whole genome sequencing from circulating cell-free DNA (cfDNA) for 143 patients with metastatic cancer of known type, 41 patients with Cancer of Unknown Primary (CUP) and 27 non-cancer controls.

Dataset EGAD00001011178

EGA account management

How to manage your EGA account Welcome to the documentation page for creating an EGA user. The European Genome-Phenome Archive (EGA) is a platform for archiving, managing, and sharing human genomic and phenotypic data. To submit, access, and manage requests for the data hosted on the EGA platform, users are required to register for an account. This documentation page provides step-by-step instructions for creating an EGA user account, as well as information on the different types of EGA user accounts and their associated privileges. You can check the EGA data flow for a better understanding. Manage EGA account step-by-step guide Contact Information Public Keys Password Authenticator Federated Identity Sessions Request an EGA account step-by-step guide Fill in this form.You cannot use a generic email account (e.g., Gmail). Make sure you use your institutional email account.Your email is by default your username.The criteria for a strong password is: It should contain between 8 and 32 charactersIt should contain at least one uppercase letterIt should contain at least one numberIt should contain at least one special characterYou will need to wait for the Helpdesk team to check your identity. Please allow two business days for this step.After the Helpdesk validation step, you will receive an email with a link to validate your institutional email.Click the link to verify your email. It will redirect you to the EGA website.As soon as your account has been validated, you will be able to start adding more information to your EGA profile. For that, you first need to log in using your credentials from step 1. Manage EGA account step-by-step guide As a logged-in user, go to your profile by clicking on Welcome > My Profile. To modify it, click the Edit button.You will see the following options: Contact Information In this section, you can modify the personal information of your EGA account. Public Keys Adding a public key is necessary for downloading data via Live Outbox distribution. If you don’t know how to generate your key, you can follow the instructions available on How do I create a key? Password In the Password tab, you can change your password anytime to ensure the security of your account. However, if you receive an email notifying you that your password was modified and you did not initiate the change, it could be a sign that your account has been compromised. In this case, you should immediately contact our Helpdesk team to report the issue and receive assistance in restoring your account security. Authenticator You can set your two-factor authentication (2FA) system for your EGA account as an identity and access management security method that requires two forms of identification to access resources and data. To obtain your code, please follow the instructions below, also available in the Authenticator tab in your profile. Sessions The Sessions tab displays a list of all devices where you are currently logged in as an EGA user. This includes any open sessions you have on your computer, phone, or other devices. By reviewing the list of active sessions, you can monitor the devices that have access to your account and ensure that there are no unauthorised logins. If you notice any suspicious activity, you can close the sessions from this page to immediately terminate access to your account from the unauthorised device.

Documentation how-to-manage-your-account

Whole blood RNAseq from a large ALS case-control study at Univ of Michigan

This dataset consists of 694 bulk RNA-seq data (sorted aligned BAM files) from whole blood of ALS participants meeting the Gold Coast definition of ALS during their clinical visit (n=422) and healthy controls (n=272) at the University of Michigan (UM). Samples were collected as part of the UM Pranger ALS Clinic between 2011-2021, and prepared either using poly-A selection of rRNA depletion (see Experiments). RNAseq was performed on the NovSeq 6000 S4 at the UM Advanced Genomics Core, resulting in 150bp paired-end reads. Raw reads were trimmed using Cutadapt (v2.3) and aligned to hg38 using STAR (v2.5.3a). Age provided is the age at blood sample collection date.

Dataset EGAD50000001488

Pancreatic, Small-intestinal and Pulmonary Neuroendocrine Tumors

Purpose: The primary origin of neuroendocrine tumor metastases can be difficult to determine by histopathology alone, but is critical for therapeutic decision making. DNA methylation-based profiling is now routinely used in the diagnostic workup of brain tumors. This has been enabled by the availability of cost-efficient array-based platforms. We have extended these efforts to augment histopathological diagnosis in neuroendocrine tumors. Experimental Design and Results: We compiled data of 69 small-intestinal, pulmonary, and pancreatic neuroendocrine tumors. These data were used to build a ridge regression calibrated random forest classification algorithm (NEN-ID) that predicts the origin of tumor samples with high accuracy (&gt; 95%). The model was validated during 3x3 nested cross validation and tested in a local (n=26) and external (n=172) cohort. In addition, we show that our diagnostic approach is robust across a range of possible confounding experimental parameters such as tumor purity and array quality. A software infrastructure and online user interface was built to make the model available to the scientific community. Conclusions: This DNA methylation-based prediction model can be used in the workup for patients with neuroendocrine tumors of unknown primary. To facilitate validation and clinical implementation, we provide a user-friendly, publicly available web-based version of NEN-ID.

Study EGAS00001004878

Targeted sequencing of 72 prostate cancer driver in 712 plasma cell free DNA samples

Dataset contains targeted sequencing data of 712 plasma cell free DNA samples and 428 white blood cell samples collected from 428 men with metastatic prostate cancer. Target capture was performed using a hydridization-based custom Roche SeqCap EZ Choice kit, designed to capture all exons of 72 prostate cancer driver genes. Cell free DNA was extracted from 10 mL blood samples. Libraries were sequenced using Illumina HiSeq 2500 or Illumina MiSeq instruments to a median coverage of 750x. 62% of samples had ctDNA fraction above 2% of total cfDNA. Note that "Dataset type" is erroneously listed as "Amplicon sequencing", because "Captured-based targeted sequencing" or "Hybridization-based targeted sequencing" were not available options in EGA at the time of submission.

Dataset EGAD00001004208

Nuclease deficiencies alter plasma cell-free DNA methylation profiles (Human samples)

The dataset contains 2x75bp paired-end sequencing data in DNASE1L3-deficient human subjects. We performed bisulfite sequencing of plasma samples from three DNASE1L3-deficient subjects and one heterozygous parent to investigate how nuclease deficiencies alter plasma cell-free DNA methylation profiles.

Dataset EGAD00001007750

The effect of blood tube and time delay on the genome-wide methylation pattern of cfDNA

In this study, we evaluated the effect of preservation agens on the effect of the methylation pattern of cell-free DNA. The methylation pattern was assessed with cell-free reduced representation sequencing (cf-RRBS). All 45 samples were sequenced on a NovaSeq6000, and samples are provided as raw fastq files.

Dataset EGAD00001006007

ECCO-GEN Valve Methylation Dataset (non-diseased)

The valve methylation dataset consists of 12 bam files of human non-diseased valve tissue samples that are free from calcification (6 aortic and 6 mitral valves - matched; 10 males: 2 females; age range 42 – 64 years, mean age 52.2 years, SD 9.9682). Donor hearts are free from cardiovascular and valvular complications.

Dataset EGAD00001006303

Oncogenic Ectodomain deletion of FGFR1 caused by Breakage-Fusion-Bridges in Squamous Cell lung Cancer

The identification of recurrent 8p11.23 amplifications including FGFR1 raised the hope of a treatable target in squamous cell lung cancer (SQLC). However, only a minority of patients with FGFR1-amplified tumors respond to single agent inhibitor therapy targeting FGFR. To understand the underlying mechanism of FGFR1 dependency, we performed whole genome and transcriptome sequencing of 25 FGFR1-amplified primary tumors with unknown response upon FGFR inhibition. In addition, we performed deep sequencing of 26 FGFR1-amplified samples whereof the response upon FGFR inhibition was known for 25 samples. In both cohorts we identified intra-chromosomal tail-to-tail breaks close to the FGFR1 transcription start site, being responsible for focal amplification of FGFR1. These specific breaks are caused by a Breakage-Fusion-Bridge-like (BFB-like) mechanism. Here, we associate these breaks with FGFR inhibitor sensitivity. Moreover, in some cases these breaks are located within the open reading frame of FGFR1, which leads to the expression of an ΔEC-FGFR1 transcript that lacks the ecto-domain. Overexpression of ΔEC-FGFR1 transforms Baf3 cells and lead to an FGFR1-dependent phenotype. Our results demonstrate that the truncation of the FGFR1 ectodomain is a frequent event in 8p11.23-amplified squamous cell lung cancer caused by tail-to-tail breaks. These breaks might be used as a predictive therapeutic marker to stratify patients for FGFR-inhibitor therapy.

Study EGAS00001005059

NHLBI TOPMed: GOLDN Epigenetic Determinants of Lipid Response to Dietary Fat and Fenofibrate

The GOLDN study was initiated to assess how genetic factors interact with environmental (diet and drug) interventions to influence blood levels of triglycerides and other atherogenic lipid species and inflammation markers (registered at clinicaltrials.gov, number NCT00083369). The study recruited Caucasian participants primarily from three-generational pedigrees from two NHLBI Family Heart Study (FHS) field centers (Minneapolis, MN and Salt Lake City, UT). Only families with at least two siblings were recruited and only participants who did not take lipid-lowering agents (pharmaceuticals or nutraceuticals) for at least 4 weeks prior to the initial visit were included. The diet intervention followed the protocol of Patsch et al. (1992). The whipping cream (83% fat) meal had 700 Calories/m2 body surface area (2.93 mJ/m2 body surface area): 3% of calories were derived from protein (instant nonfat dry milk) and 14% from carbohydrate (sugar). The ratio of polyunsaturated to saturated fat was 0.06 and the cholesterol content of the average meal was 240 mg. The mixture was blended with ice and flavorings. Blood samples were drawn immediately before (fasting) and at 3.5 and 6 hours after consuming the high-fat meal. The diet intervention was administered at baseline as well as after a 3-week treatment with 160 mg micronized fenofibrate. Participants were given the option to complete one or both (diet and drug) interventions. Of all participants, 1079 had phenotypic data and provided appropriate consent, and underwent whole genome sequencing through the Trans-Omics for Precision Medicine (TOPMed) program. Comprehensive phenotypic and pedigree data for GOLDN study participants are available through dbGaP phs000741.

Study phs001359

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort

The Human Phenotype Project (HPP) is a large-scale deep-phenotype prospective longitudinal and ethnically diverse cohort and biobank that we established. To date, approximately 28,000 participants have enrolled in the study, with over 13,000 having completed their initial visit. The project is aimed at identifying novel molecular signatures with diagnostic, prognostic and therapeutic value, and at developing AI-based predictive models for disease onset and progression. A unique feature of the HPP is its deep and longitudinal profiling that includes medical history, lifestyle and nutritional habits, vital signs, anthropometrics, blood tests, continuous glucose and sleep monitoring, imaging modalities and molecular profiling of the transcriptome, genetics, gut, vaginal and oral microbiome, metabolome and immune system. For several of these modalities, the HPP is the first or largest cohort of its kind. Our analyses of this data provide novel insights into the variation of phenotypes with age and ethnicity, highlighting the importance of having ethnically diverse cohorts and the need for establishing age-dependent norms. We demonstrate how the HPP can be used to unravel personalized molecular signatures of disease by comparison to patient-specific and disease-specific matched healthy controls. Leveraging the extensive dietary and lifestyle HPP data, we systematically identify associations between lifestyle factors and health outcomes. Finally, we present a multi-modal foundation AI model that is trained using self-supervised learning on diet and CGM data and outperforms existing methods in predicting future onset of disease. We extend this AI framework to integrate all data modalities of each subject as a continuous sequence of diverse medical events, creating a digital twin that can simulate interventions and predict health trajectories and outcomes.

Study EGAS00001008040

Genome-wide cell-free DNA biological patterns in patients with cancer

The structure of cell-free DNA (cfDNA) is altered in the blood of cancer patients. From whole genome sequencing we retrieved the cfDNA fragment-end composition using a new software (FrEIA), as well as the cfDNA size and tumor fraction in three independent cohorts (n=925 cancer from >10 types and 321 control samples). At 95% specificity, we detect 72% of cancer samples using at least one cfDNA measure, including 64% of early-stage cancer (n=220). cfDNA detection correlates with a shorter overall (p=0.018) and recurrence-free (p=0.006) survival in patients with resectable esophageal adenocarcinoma. Integrating cfDNA measures with machine learning in an independent test set (n=396 cancer, 90 controls) achieve a detection accuracy of 82% and AUROC of 96%. In conclusion, harnessing the biological features of cfDNA can improve at no-extra cost the diagnostic performance of liquid biopsies.

Study EGAS00001007400

cfRRBS methylation profiling of cfDNA from cerebrospinal fluid from pediatric CNS tumor patients

In this study, we explore the potential of classifying pediatric brain tumors based on methylation profiling of the cell-free DNA in cerebrospinal fluid (CSF). For this proof-of-concept study, we collected 20 cerebrospinal fluid samples of pediatric brain cancer patients via a ventricular drain placed for reasons of increased intracranial pressure. For 11 patients in this study we collected matched tumor DNA. This cohort contains fastQ files of cfRRBS data of these samples.

Dataset EGAD50000000554

Regulatory T cell transcriptomic reprogramming characterizes adverse events by checkpoint inhibitors in solid tumors

Tregs were sorted as CD4+CD25+CD127- cells from peripheral blood of patients with advanced metastatic melanoma, stage III(B-D)-IV, who were receiving treatment with anti-PD1 (n =26); and patients with kidney, non-small cell lung, liver and bladder cancer who were receiving treatment with anti-PD1. RNA was extracted and polyA libraries were prepared using the Illumina Truseq sample preparation kit v.2. Single-end sequencing was performed on NextSeq500.

Dataset EGAD00001006415

Mitochondrial DNA sequencing of human iPSC, parental cells, and iPSC derived cardiomyocytes

Dataset contains whole mitochondrial DNA sequencing data in fastq format (Illumina MiSeq paired-end) of 62 samples, in total. Those samples include sequencing data of the endothelial cell populations of 10 different donors and of 26 early-passage iPSC clones derived thereof. Moreover, the dataset contains the data of 7 of those iPSC clones sequenced additionally in passage 30 and 50, each. Lastly, 4 iPSC clones were sequenced during directed cardiomyocyte differentiation, each at day 0, 5, and 15 of differentiation.

Dataset EGAD00001008021

Multicenter International Lymphangioleiomyomatosis Efficacy of Sirolimus Trial (The MILES Trial)

Lymphangioleiomyomatosis (LAM) is an uncommon, progressive, cystic lung disease that predominantly affects young women. It is believed to be caused by defects within cellular pathways that regulate nutrient uptake, cell size, cell migration, and cell proliferation. The disease is caused by mutations in tuberous sclerosis complex (TSC) genes. Individuals with Lymphangioleiomyomatosis (LAM) often experience pneumothorax and chylothorax, as well progressive loss of lung function. Lymphangioleiomyomatosis (LAM) is frequently fatal and existing therapies for the disease have not proven effective. Lung transplantation can be considered as a last option, but alternative treatments are needed. Sirolimus is an immunosuppressive drug that is often used in people who have had kidney transplants. It directly affects the genetic pathway that causes Lymphangioleiomyomatosis (LAM). This study will evaluate the safety and effectiveness of sirolimus in stabilizing or improving lung function in people with Lymphangioleiomyomatosis (LAM). Individuals interested in participating in this 2-year, double-blind study will first report to the study sites for pulmonary function testing to determine their eligibility for participation. Participants deemed eligible will be randomly assigned to receive either sirolimus or placebo for 1 year. Sirolimus or placebo will be administered in 2 tablet doses (2 mg for sirolimus) for the duration of the study. Study visits will occur at baseline, Week 3, every 3 months for 12 months, and Months 18 and 24. Study visits will include a physical exam, questionnaires, a pregnancy test, blood and urine collection, and functional lung tests. A 6-minute walk test will occur at most study visits; a chest x-ray will be taken at baseline and Month 24; and a volumetric computed tomography scan will occur at baseline Month 12, and Month 24. Adverse events, medication side effects, and lung function will be assessed at each visit.

Study phs000605

Differential Presence of Exons in Cell-Free DNA (NIMGenetics/IIS-FJD)

Dac EGAC00001002885

Methylation-based deconvolution of cell-free DNA

Study EGAS00001007493

Identification_of_synthetic_lethal_genes_by_CRISPR_Cas9_library

Sequencing is performed on PCR products from the amplification of gRNA segments introduced into cell lines (some are commercial, some are derived by collaborators, as described in HMDMC 13/076). Cellular DNA or RNA are not sequenced. This data is defined as "Other Biological/Biochemical Assay Data" under the WTSI datasharing guidelines and consequently will be released at the time of publication and/or through faculty websites. SEQUENCING DETAILS: in October 2016 3 DNA samples will be submitted for PCR amplification and purification through CGP pipeline using Thompson's custom primer set and PCR settings and sequencing with Hiseq using a custom protocol (with 3 forward reads to read sgRNA1, sgRNA2 and the index, optimized with Illumina Bespoke Sanger team); read length 50bp. The following set of samples will be submitted in later 2016 and ealry 2017 as cell pellet to be processed through CGP Cas9 pipeline (Thompson's oligos and protocols) and sequences on Hiseq (same custom sequencing protocol described above) We are utilizing a custom CRISPR/Cas9 library to identify synthetic lethal gene pairs. Cells will be transduced with LV expressing Cas9, then infected with LV expressign the library of 42'000 sgRNA pairs. Cell pellet will be collected from the cell population at different timepoints. The samples will be processed by CGP pipeline customized for the specific protocol and then sequenced to identify the 19bp of the sgRNA and quantify their representation.

Study EGAS00001002117

ILyAD (Indolent Lymphoma And vitamin D)

Indolent non-Hodgkin lymphomas are incurable diseases, and require intermittent and often morbid and expensive therapy during their prolonged natural history. Lower intensity and better-tolerated, cost-effective treatment strategies are needed for these patients. Low vitamin D levels at diagnosis of indolent lymphomas are strongly associated with inferior outcomes to treatment. Standard therapy for low tumor burden, indolent lymphoma includes a single agent monoclonal antibody (rituximab). In our double-blind, placebo-controlled, randomized trial we evaluated if vitamin D supplementation with 2000IU oral cholecalciferol daily for three years improved the progression-free survival of patients with indolent lymphoma treated with single agent rituximab. Stratification factors for randomization included histology and Follicular Lymphoma International Prognostic Index (FL-IPI) prognostic score. The primary endpoint of the trial was progression-free survival over three years; secondary endpoints included response at 13 weeks, and overall survival. Eligible participants were adults with biopsy proven follicular lymphoma (grades 1-3a), small lymphocytic lymphoma, marginal zone lymphoma and mucosal-associated lymphoid tissue with no prior anti-lymphoma systemic therapy. Participants had Ann Arbor stage II or greater, measurable disease defined by Lugano criteria. Participants with osteoporosis requiring prescription treatment, symptomatic primary hyperthyroidism, hypercalcemia, creatinine greater than 1.5 times the upper limit of normal or a history of calcium-related kidney stones were excluded. Germline DNA was isolated from saliva samples obtained from participants at baseline. Whole exome sequencing was performed and SNPs were analyzed using the Agilent SureSelectXT Human All Exon V6 +UTR array. SNP data from 185 participants are available through dbGaP.

Study phs003503

Whole genome sequencing of mature B-cell lymphomas to identify MYC, BCL2, and BCL6 rearrangements

Whole genome sequencing (WGS) data of 12 tumours was generated on an Illumina NovaSeq or HiSeqX instrument. For frozen samples, libraries were constructed using a PCR-free library construction method. For tumours preserved by formalin fixation and paraffin embedding (FFPE), libraries were constructed with a method that included S1 nuclease treatment. Reads were aligned to the grch37 reference with bwa-mem 0.7.17.

Dataset EGAD50000000474

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