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• Comprehensive copy number aberration analysis using digital Multiplex Ligation-dependent Probe Amplification (digitalMLPA) in pediatric B-cell precursor acute lymphoblastic leukemia

  In this study a next-generation sequencing based method was applied to comprehensively screen for recurrent, disease-relevant copy number aberrations in a cohort of Hungarian patients. Diagnostic bone marrow samples from 260 children with B-cell acute lymphoblastic leukemia as well as 72 control samples and were investigated by digital multiplex ligation-dependent probe amplification using the disease-specific D007 probemix. Whole chromosome gains and losses, as well as subchromosomal copy number aberrations were simultaneously profiled.

  Dataset EGAD00001010878

• Single-cell expression of Hodgkin and Reed-Sternberg (HRS) cell

  Hybrid capture sequencing was performed to 3 purified Hodgkin and Reed-Sternberg (HRS) cell samples. In brief, Probes for 177 genes were designed and synthesized by Twist Bioscience. Hybridization capture of DNA libraries was performed using Twist Hybridization and Wash Kit (Twist Bioscience). The captured library was measured using Agilent Bioanalyzer High Sensitivity chip and Qubit dsDNA HS Assay Kit and run on Illumina Nextseq550. The BAM files were generated from the raw sequencing data using Cell Ranger (v6.0.2) mkfastq and count commands

  Dataset EGAD00001010892

• Facioscapulohumeral muscular dystrophy (FSHD): RNA-seq of isogenic TIRM+, TIRM- muscle and PBMCs from patients and matched controls

  FASTQ files describing paired-end RNA-sequencing of isogenic TIRM+ and TIRM- muscle biopsies from 24 FSHD patients (48 samples) and vastus lateralis muscle biopsies from 11 matched control individuals. FASTQ files are also provided describing RNA-sequencing of 15 FSHD peripheral blood mononuclear samples and 14 matched controls. For muscle biopsies sequencing was at 21.7-35.5 million reads/sample. RNA was extracted from PBMCs followed by globin depletion with sequencing at 19.7-46.5 million reads/sample.

  Dataset EGAD00001011077

• Bulk RNA sequencing of SARC PDOs and UroCa PDOs.

  This dataset contains raw FASTQ files from bulk RNA sequencing of SarBC-01 organoids at different passages (Passage 6, Pssage 19, Passage 59), UroBC-01 organoids (Passage 70), UroBC-16 organoids (Passage 19) and UroBC-22 organoids (Passage 8). RNA was isolated using the Quick-DNA/RNA Miniprep kit (Zymo Research, Irvine, CA, USA, D7001) and subjected to bulk RNA sequencing. TruSeq Stranded mRNA kit (Illumina, 20020594) was used for the library preparation according to manufacturer’s guidelines. Sequencing was performed on Illumina NovaSeq 6000 using paired-end 100-bp reads.

  Dataset EGAD00001011156

• Sequencing data for oesophageal and related samples - Black et al (WGS)

  Data supporting: "Understanding the malignant potential of gastric metaplasia of the oesophagus and its relevance to Barrett’s Oesophagus surveillance: individual-level data analysis" Black et al (WGS OACs/BOs/normals)

  Dataset EGAD00001011187

• Sequencing data for oesophageal and related samples - Zamani et al

  Data supporting: "Genomic and epidemiological similarities between phenotypically distinct esophageal adenocarcinoma suggest a single entity" Zamani et al

  Dataset EGAD00001015435

• Raw molecular data for "Subclonal immune evasion in non-small cell lung cancer"

  Whole exome, RNA sequencing and TCR sequencing of organoid samples derived from TRACERx patients. The dataset also includes whole exome sequencing from the tumour samples from which the organoids were generated, as well as whole exome sequencing from PDX derived from said tumours.

  Dataset EGAD00001015537

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• Lung Cell Atlas: Paediatric RNA (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015722

• Lung Cell Atlas: Paediatric Spatial (2025-10-02)

  Single cell sequencing will be carried out by multiome profiling (RNAseq and ATACseq). Additonal modalities may be examined. Spatial profiling may involve Visium, Curio and other technologies. This data set will feed into a larger analysis of the human lungs over development, that aims to detail all the cell types of the human lungs and airways and will extend current knowledge by providing chromatin accessibility data that will allow us to link GWAS data and identify regulatory networks and then compare these against fetal and adult data sets . This dataset contains all the data available for this study on 2025-10-02.

  Dataset EGAD00001015723

• Identification of drug resistance genes in melanoma by mRNA gene expression

  We aim to sequence the mRNA transcriptome of 22 human melanoma cell lines in biological triplicate in order to define the gene expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001003244

• Identification of drug resistance genes in melanoma by small RNAs expression analysis

  We aim to sequence the small RNAs of 22 human melanoma cell lines in biological triplicate in order to define the microRNAs expression profile of each cell line. The data will be correlated to the mutation status and the sensitivity to a panel of drugs in order to identify genes whose deregulation is associated to drug resistance This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001003245

• Amplicon-based sequencing of drug resistant lung cancer cell lines (2017-07-05)

  A EGFR mutant NSCLC cell line which is sensitive to AZD9291 inhibition was mutagenised with the chemical mutagen ENU and then drug selected using a AZD9291. Single cell derived colonies were then manually picked and expanded in drug. Resistance was confirmed in a 14 day assay and DNA was collected. These then underwent targeted amplicon-based sequencing to confirm candidate resistance effectors hypothesised from currently available literature. This dataset contains all the data available for this study on 2017-07-05.

  Dataset EGAD00001003425

• SOFT study - sequencing premenopausal breast cancer (2017-11-22)

  Our project will examine the role of PIK3CA mutations and their sensitivity to endocrine therapies and its role, with the addition of complete ovarian suppression. We plan to test our hypotheses using tumour samples collected from patients enrolled in the SOFT/IBCSG24-02 clinical study (Suppression of Ovarian Function Trial - (NCT00066690). SOFT is a phase III trial that randomised 3066 premenopausal women to evaluate if adding ovarian suppression to adjuvant endocrine therapy will improve clinical outcomes. This dataset contains all the data available for this study on 2017-11-22.

  Dataset EGAD00001003811

• Finding structural variation from the patient-derived xenografts of pediatric T-cell leukemia at the single-cell level

  In this study, we aimed to identify somatic structural variation of T-cell acute lymphoblastic leukemias (T-ALLs_ from patient-derived xenografts (PDX) at the single-cell level. For this purpose, we performed strand-specific single-cell sequencing of PDX-derived T-ALL relapse samples from two juvenile patients (P1, P33). To validate structural variation detected via scTRIP, we profiled whole exome sequencing (WES) data from P33 (samples taken during initial disease, remission, relapse), and mate-pair sequencing data from P1 (relapse).

  Dataset EGAD00001004499

• Genomic and transcriptomic determinants of therapy resistance and immune landscape evolution during anti-EGFR treatment in colorectal cancer

  Genomic and transcriptomic data from a cohort of 35 RAS wild-type colorectal cancers. All 35 cases were DNA sequenced at baseline (BL) before treatment with single agent cetuximab. Progressive disease (PD)-biopsies were taken shortly after radiological progression and successfully exome sequenced from 24/35 cases. mRNA sequencing is available for 25 Baseline and 15 PD samples. ctDNA from 9 cases that progressed after prolonged cetuximab benefit were also deep sequenced.

  Dataset EGAD00001004501

• Mannheim Liquid Biopsy Unit, Heidelberg University & DKFZ

  The dataset consists of sequenced cell free DNA (cfDNA) samples from colorectal cancer patients. The samples were sequenced on an Illumina MiSeq machine using a custom amplicon sequencing approach. These amplicons were designed to cover the most common mutation hotspots in colorectal cancer. The data include 138 cfDNA samples from 34 different patients. For each patient several samples are available derived from blood drawn at different time points during treatment. In addition the data include samples from 22 histology slides and 30 samples derived from HT29/HCT116 cell lines that were used as controls.

  Dataset EGAD00001004574

• Prognostic factors in prostate cancer: deep sequencing pilot project TAPG

  This is a pilot project to determine whether the TAPG FFPE DNA's are suitable for deep sequencing. If successful an investigation of SNP distribution in a larger cohort will follow.

  Dataset EGAD00001001237

• Targeted sequencing of genes recurrently mutated in AML - part2

  Genomic libraries will be generated from total genomic DNA derived from 4000 samples with Acute Myeloid Leukaemia. Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 64 Samples will be individually barcoded and subjected to up to one lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Dataset EGAD00001000747

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - mobile_elements

  Samples from Edwards et al 2015 - doi:10.1186/s12864-015-1685-z

  Dataset EGAD00001001048

• TMD-AMKL targeted follow-up part 2

  Genomic libraries will be generated from total genomic DNA derived from 200+ patients with childhood Transient Myeloproliferative Disorder (TMD) and or Acute Megakaryocytic Leukemia (AMKL) as well some matched constitutional samples (n < 50). Libraries will be enriched for a selected panel of genes using a bespoke pulldown protocol. 96 Samples will be individually barcoded and subjected to up to two lanes of Illumina HiSeq. Paired reads will be mapped to build 37 of the human reference genome to facilitate the characterisation of known gene mutations in cancer as well as the validation of potentially novel variants identified by prior exome sequencing.

  Dataset EGAD00001000879

• ICGC Prostate Cancer Whole Genome Sequencing

  Whole Genome Sequencing Illumina HiSeq data from 20 men with prostate cancer. 20 samples were taken from primary tissue obtained at prostatectomy (target sequencing depth 50X) with matched blood control (target sequencing depth 30X). These were submitted for use in the ICGC Pan-Cancer Analysis of Whole Genomes project. Same raw data submitted in EGAD00001001116. As of September 2020, some of the studies using these data include: Wedge et al, Nature Genetics 2018 (PMID: 29662167) Pan-Cancer Analysis of Whole Genomes, Nature 2020 (PMID: 32025007)

  Dataset EGAD00001000892

• Congenital anosmia 1

  Congenital anosmias can be complete (the lack of a sense of smell) or specific (the inability to detect specific smells). To date, only a single recessive gene underlying complete anosmia has been identified. Here we sequenced the exomes of 10 individuals from a single family, including three with complete anosmia, across three generations to identify the genetic basis of congenital anosmia in this family. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001002210

• Sequence Data for DEEP Release August 2016

  DEEP (German Epigenome Project) sequence data of following samples (Sequencing Types: Chip-Seq, WGBS-Seq, RNA-Seq, sncRNA-Seq, NOMe-Se, DNase-Seq): 41_Hf01_LiHe_Ct, 41_Hf02_LiHe_Ct, 41_Hf03_LiHe_Ct, 01_HepG2_LiHG_Ct1, 01_HepG2_LiHG_Ct2, 01_HepaRG_LiHR_D31, 01_HepaRG_LiHR_D32, 01_HepaRG_LiHR_D33, 43_Hm01_BlMo_Ct, 43_Hm03_BlMo_Ct, 43_Hm05_BlMo_Ct, 43_Hm03_BlMa_Ct, 43_Hm05_BlMa_Ct, 43_Hm03_BlMa_TO, 43_Hm05_BlMa_TO, 43_Hm03_BlMa_TE, 43_Hm05_BlMa_TE, 51_Hf01_BlCM_Ct, 51_Hf03_BlCM_Ct, 51_Hf04_BlCM_Ct, 51_Hf02_BlCM_Ct, 51_Hf05_BlCM_Ct, 51_Hf06_BlCM_Ct, 51_Hf06_BlCM_T1, 51_Hf06_BlCM_T2, 51_Hf03_BlEM_Ct, 51_Hf04_BlEM_Ct, 51_Hf02_BlEM_Ct, 51_Hf05_BlEM_Ct, 51_Hf06_BlEM_Ct, 51_Hf06_BlEM_T1, 51_Hf06_BlEM_T2, 51_Hf03_BlTN_Ct, 51_Hf04_BlTN_Ct, 51_Hf02_BlTN_Ct, 51_Hf05_BlTN_Ct, 51_Hf06_BlTN_Ct, 51_Hf06_BlTN_T1, 51_Hf06_BlTN_T2, 51_Hf07_BmTM4_Ct, 51_Hf08_BlTM4_Ct, 51_Hf08_BmTM4_SP1, 51_Hf08_BmTM4_SP2, 51_Hf05_BlTA_Ct, 44_Mm01_WEAd_C2, 44_Mm03_WEAd_C2, 44_Mm02_WEAd_C2, 44_Mm07_WEAd_C2, 44_Mm04_WEAd_C1, 44_Mm05_WEAd_C1

  Dataset EGAD00001002527

• Sequencing data for oesophageal and related samples - Mourikis et al (WGS)

  Data supporting: "Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma." Mourikis et al. WGS (BAM files) 521 samples

  Dataset EGAD00001004775

• Whole-genome bisulfite sequencing

  Raw reads from whole-genome bisulfite sequencing. Whole-genome bisulfite sequencing library preparations and Illumina sequencing of DNA samples from TET2 mutation carriers (Ly9, Ly11, Ly14, Id1) and their age-matched controls (Ly8, Ly10, Ly13, Id2, Id3) was done as a service at BGI (BGI Tech Solutions Co., Ltd., China). Bisulfite treatment was done with EZ DNA Methylation-Gold Kit (Zymo Research, CA, USA) for 300-400bp size-range fragments with methylated adapters in 5' and 3' ends. Sequencing was done with the HiSeq X-Ten platform using paired-end 150 base-pair read length.

  Dataset EGAD00001004779

• Deep exome sequencing

  Bam files from deep exome sequencing of blood DNA samples from five TET2 mutation carriers (Ly1, Ly2, Ly9, Ly11, Ly14) and three wild-type family members (Ly8, Ly10, Ly13) extracted at multiple time points. Library preparations were performed with SeqCap EZ Exome v3 (Roche, Switzerland) using six different index primers per sample for which paired-end Illumina sequencing was done with 75bp read length and HiSeq4000 sequencer. After alignment (bwa version 0.7.12), base recalibration (GATK 3.5), realignment around indels (GATK 3.5) and duplicate removal (MarkDuplicates; Picard Tools version 1.79), data from libraries with six different indexes were merged.

  Dataset EGAD00001004780

• Low input LC (WGS) (2019-04-01)

  R&D project to develop low input library construction methods. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004878

• Evolution of the cancer epigenome in myeloproliferative neoplasms. (2019-04-01)

  Evolution of the cancer epigenome in myeloproliferative neoplasms. . This dataset contains all the data available for this study on 2019-04-01.

  Dataset EGAD00001004879

• Exome Sequencing to Identify Causes of Leukaemia Predisposing Congenital Neutropenias (2019-08-19)

  The objective of this study is to identify the causative genes in two unrelated congenital neutropenia families. We aim to whole exome sequence the affected individuals, unaffected siblings and parents in both cases in an effort to idenitfy the causative genetic mutation. Exome capture will be performed using Agilent SureSelect system. Subsequently, exome libraries will sequenced using the Illumina HiSeq platform. Sequence variant calling will be done in house and common variants excluded using public databases and data from unaffected family members. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005264

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (scRNA)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. scRNAseq (BAM files) 38 Barrett's and normal samples

  Dataset EGAD00001005438

• small RNA-sequencing and RNA-sequencing of human brain tissue with temporal lobe epilepsy

  This data set contains the raw .fastq files from two RNA-sequencing experiments and two small RNA-sequencing experiments. Both control brain tissue and tissue from sufferers of mesial temporal lobe epilepsy were sequenced. Two different brain regions were sequenced; the cortex and the hippocampus. For more details please see: Mills, James D., et al. "Coding and non-coding transcriptome of mesial temporal lobe epilepsy: Critical role of small non-coding RNAs." Neurobiology of disease 134 (2020): 104612.

  Dataset EGAD00001005735

• RNA-seq data from 121 tumor samples with muscle invasive bladder cancer.

  In this study, a total of 300 patients with MIBC receiving chemotherapy were included; 62 received NAC before cystectomy and 245 received first-line chemotherapy upon detection of locally-advanced (T4b) or metastatic disease. Treatment response, defined as pathological downstaging (< pTa,CIS,N0) after NAC or complete or partial response after first-line treatment (RECIST criteria). RNA-seq was performed using the QuantSeq kit FWD HT kit (Lexogen) using 500 ng input RNA from 121 tumor samples. Data provided here consist of 780 fastq files for RNA-seq.

  Dataset EGAD00001006238

• miRNA-seq data for Molecular Characterization of ETMR

  This dataset contains miRNA-seq data from 10 patients. Small RNAs were isolated as described previously57,58 from fresh-frozen tumour material. In brief, total RNA was extracted using guanidinium isothiocyanate/phenol extraction followed by 3′-adaptor ligation of barcoded adenylated adaptors. Samples were pooled in two sets of five samples. Subsequently, gel electrophoresis was used to isolate small RNAs (19–35 nt) and purified using ethanol precipitation. Fragments were then amplified using standard PCR, isolated using gel electropho- resis and purified using ethanol precipitation. Samples were sequenced on a HiSeq 2000 v.4 machine resulting in 10 Fastq files.

  Dataset EGAD00001006218

• Whole Genome Sequencing of Human Organoid Lines (2020-02-20)

  The study will use WGS to aid in benchmarking different culture conditions in a set of genetically annotated human organoid lines. The data will be used to assess whether there is any clonal differences introduced when culturing these lines in different conditions. . This dataset contains all the data available for this study on 2020-02-20.

  Dataset EGAD00001005995

• Transcriptomic profiling of primary tumor and paired hepatic oligometastasis of PDAC

  The dataset was generated for studying metastatic mechanism of pancreatic ductal adenocarcinoma (PDAC). It is consisted of pair-end raw RNA sequencing reads of 33 fresh froze PDAC specimens, which includes 6 tumor-adjacent normal tissues (N), 13 primary tumors (PT), and 14 hepatic metastases (HM) from 14 PDAC patients (6 N-PT-HM trios, 7 PT-HM paires, and 1 HM).

  Dataset EGAD00001006598

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (WGS)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. WGS (BAM files) 5 Barrett's samples 5 normal oesophageal samples 5 normal gastric cardia samples 5 normal duodenal samples

  Dataset EGAD00001006874

• Sequencing data for oesophageal and related samples - Nowicki-Osuch, Zhuang et al (bulk RNA)

  Data supporting: “Deep molecular phenotyping reveals the identity of Barrett’s esophagus and its malignant transition.” Nowicki-Osuch, Zhuang et al. RNAseq (BAM files) 12 Barrett's samples 12 normal oesophageal samples 11 normal gastric cardia samples

  Dataset EGAD00001006882

• RNA of peripheral blood for pancreatic cancer and chronic pancreatitis

  Samples of nucleated cells found in peripheral blood from over 300 patients suffering from resectable pancreatic ductal adenocarcinoma, non-resectable pancreatic cancer, chronic pancreatitis, or none of these. Please cite this article when using data: Al-Fatlawi, A.; Malekian, N.; García, S.; Henschel, A.; Kim, I.; Dahl, A.; Jahnke, B.; Bailey, P.; Bolz, S.N.; Poetsch, A.R.; Mahler, S.; Grützmann, R.; Pilarsky, C.; Schroeder, M. Deep Learning Improves Pancreatic Cancer Diagnosis Using RNA-Based Variants. Cancers 2021, 13, 2654. https://doi.org/10.3390/cancers13112654

  Dataset EGAD00001006915

• Circulating cell-free DNA analyses for Patient Monitoring in Small Cell Lung Cancer

  This study consists of over 200 data files from cfDNA and germline DNA from 69 patients and 32 healthy normal volunteers discussed in this publication.

  Dataset EGAD00001007070

• 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

• Sequence data for study: Mobilization of tissue-resident memory CD4+ T lymphocytes from bone marrow and their contribution to a systemic secondary immune reaction

  Short Description: This study contains 7 RRBS samples, including 3 ex vivo CD4+ Trm (2 x spleen and 1 x bone marrow) and 4 blood tetanus (TT) and measles (Me) antigen-reactive memory CD4+ cells before and one day post DTaP (diphtheria-tetanus-pertussis) and MMR (measles-mumps-rubella) vaccination, respectively (1 x tetanus D0, 1 x tetanus D1, 1 x measles D0, 1 x measles D1). Technology: Illumina HiSeq 2500 Filetype: fastq format

  Dataset EGAD00001007886

• HCA Female Reproductive Adult WSSS RNA

  HCA Endometrium_LM The endometrium regenerates monthly and its transformation is executed through dynamic changes in states and interactions of multiple cell types. Using transcriptomics methods we seek to profile changes of the endometrium across the menstrual cycle. Our map will have implications in women's health and cancer, by enabling the interpretation of GWAS analyses or the studying functional consequences of somatic mutations. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/

  Dataset EGAD00001007909

• sWGS of OV04 PDX samples for ACN rascal study

  This dataset contains 148 .bam files of shallow WGS data (~0.1X) from OV04 PDX samples. Sequencing reads were aligned to the 1000 Genomes Project GRCh37-derived reference genome using the BWA aligner (v.0.07.17; CRUK-CI alignment pipeline).

  Dataset EGAD00001008119

• Neuroblastoma patient WGS data

  Paired tumor and normal WGS of primary neuroblastomas. This is an update of the „Berlin Neuroblastoma Dataset” (EGAS00001004022). This data was used for the analysis of circular RNA expression and regulation in neuroblastoma.

  Dataset EGAD00001008123

• Differential Gene Expression in Cryptorchid Testes

  Differential Gene Expression in Cryptorchid Testes Study uses whole-genome RNA profiling of testicular biopsies to determine a potential causative role of isolated congenital cryptorchidism in azoospermia and/or infertility in the context of our previously published GeneChip data. Cryptorchid patients, aged 7 months to 5 years and otherwise healthy, were enrolled in this prospective study. During surgery, testicular tissue biopsies were obtained for histological examination and RNA-sequencing (RNA-seq). Fifteen patients were selected based on the histological results and were divided into two groups. Seven were classified as belonging to the high infertility risk (HIR) and eight to the low infertility risk (LIR) group. Cryptorchid boys in the high infertility risk group lacked transformation of gonocytes into Ad spermatogonia due to impaired mini puberty. This group of patients will be infertile despite successful surgery.

  Study phs001275