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• cfDNA dataset with expanded panel for cfDNA cohort

  Cell free DNA sequencing data for 9 samples with expanded panel across multiple cancer types for cfDNA cohort

  Dataset EGAD50000000667

• PPGL RNA-Seq dataset 2

  Dataset includes fastq files for RNA-Seq experiments for tumor samples of PPGL patients. Single end reads fastq files are available for 81 different samples

  Dataset EGAD50000000019

• 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

• Effective screening strategy for deafness using a new-genetation sequencing platform: a consecutive analysis

  The diagnosis of the genetic etiology of deafness contributes to the clinical management of patients. We performed the following four genetic tests in three stages for 52 consecutive deafness subjects in one facility. We used the Invade assay and Sanger sequencing for the GJB2 gene or SLC26A4 gene in the first stage test, TaqMan genotyping assay in second stage test, and targeted exon sequencing using the massively parallel DNA sequencing in third stage test. Overall, we identified the genetic cause in 40% (21/52) of patients. The diagnostic rates of the first-, second- and third-stage genetic testing were 17%(9/52), 9%(4/43) and 21% (8/39), respectively. The combination approach using these genetic tests appears to be useful as a diagnostic tool for deafness patients. We recommended that genetic testing for the screening of common mutations in deafness genes using the Invader assay or TaqMan genotyping assay be performed as the initial evaluation. For the remaining undiagnosed cases, targeted exon sequencing using MPS is clinically and economically beneficial. This data set was MPS reads data (fastq) for 39 sensorineural hearing loss patients.

  Study JGAS000032

• Pipeline Olympics: Continuous benchmarking of computational workflows for DNA methylation sequencing data

  DNA methylation is a widely studied epigenetic mark and a powerful biomarker of cell type, age, environmental exposure, and disease. Genome-wide DNA methylation profiling is usually performed using whole-genome sequencing following selective conversion of unmethylated cytosines into thymines via bisulfite treatment or enzymatic methods. Numerous software tools facilitate processing of raw sequencing data for DNA methylation profiling, but a comprehensive benchmarking has been lacking. In this study, we systematically compared methods and tools for processing DNA methylation sequencing data. We established a dedicated benchmarking dataset comprising genome-wide DNA methylation profiling data for four reference samples using five experimental protocols each. The results of data processing were compared to highly quantitative locus-specific DNA methylation measurements available for 46 genomic loci. Based on this gold-standard reference dataset, we identified workflows that consistently demonstrated high performance. We present our results in an interactive application that provides a “living benchmark” ready for continuous updating as new workflows are proposed and require benchmarking against existing methods. In summary, our study provides guidance for any laboratory studying DNA methylation on a genome-wide scale.

  Study EGAS50000000541

• MGP Panel: a comprehensive targeted genomics panel for molecular profiling of multiple myeloma patients

  We designed a comprehensive multiple myeloma (MM) targeted sequencing panel to identify common genomic abnormalities in a single assay and validated it against known standards. The panel comprised 228 genes/exons for mutations, 6 regions for translocations, and 56 regions for copy number abnormalities (CNAs). Toward panel validation, targeted sequencing was conducted on 233 patient samples and further validated using clinical fluorescence in situ hybridization (FISH) (translocations), multiplex ligation probe analysis (MLPA) (CNAs), whole genome sequencing (WGS) (CNAs, mutations, translocations) or droplet digital PCR (ddPCR) of known standards (mutations). Canonical IgH translocations were detected in 43.2% of patients by sequencing, and aligned with FISH except for one patient. CNAs determined by sequencing and MLPA for 22 regions were comparable in 103 samples and concordance between platforms was R2=0.969. VAFs for 74 mutations were compared between sequencing and ddPCR with concordance of R2=0.9849. In summary, we have developed a targeted sequencing panel that is as robust or superior to FISH and WGS. This molecular panel is cost effective, comprehensive, clinically actionable and can be routinely deployed to assist risk stratification at diagnosis or post-treatment to guide sequencing of therapies.

  Study EGAS00001006222

• Demographic History and Local Adaptation in Asian Population

  Due to harboring high genetic and cultural diversity of populations, Central Asia is one key area for understanding the recent evolutionary history of humans. In this project, our aims include: (1) to resequence genome sequences with high sequencing depth for Central Asian populations Balti; (2) to discern the genomic diversity, populations structure and demographic history of Balti; (3) to investigate the genetic mechanisms for local adaptations in Balti.

  Study JGAS000238

• Characterization of a novel MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line WXS derived

  The lack of a well-characterized model system for many subtypes of leukemia hinders the development of targeted therapy and immunotherapy. A novel in-house-made pediatric MEF2D-BCL9 fusion positive acute lymphoblastic leukemia cell line was characterized. This cell line is highly presentative for the major clone of the original material and thus a valuable resource to examine novel therapeutic for MEF2D fused patients.

  Study EGAS00001006801

• Whole-genome sequencing data of human hematopoietic stem and progenitor cells in post-transplant clonal hematopoiesis

  This dataset contains BAM files of whole-genome sequencing data of single human HSPCs after colony expansion, for three individuals who harbor a DNMT3A mutant clonal hematopoiesis clone in their blood system after hematopoietic cell transplantation. 29 samples are present in this dataset; 10 samples for LTHIT005, 10 samples for LTHIT131, and 9 samples for LTHIT069. In the sample name, samples are annotated for being DNMT3A wildtype (wt) or mutant (mut), except for LTHIT069 (wt samples: F13, H4, K2, L16, N12, mut samples: C8, E10, L9, N5). Whole-genome sequencing was performed after standard Illumina WGS library preparation and sequenced on a Novaseq 6000 using 150 bp paired-end sequencing. The sequencing depth is 15x genome coverage, or 50Gbases per sample.

  Dataset EGAD50000001347

• Fastq data for smRNA-Seq assays for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency as part of the International Human Epigenome Consortium.

  Fastq data for smRNA-Seq assays assay for reference epigenomes generated at Centre for Epigenome Mapping Technologies, Genome Sciences Center, B.C. Cancer Agency, Vancouver, Canada as part of the International Human Epigenome Consortium.

  Dataset EGAD00001001401