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• Data Quality Control

  Data Quality Control High-throughput sequencing techniques have become the leading method to study, decode and discover the genomic origins of biological phenomenons. EGA provides a secure archival of such identifiable genomics data with the purpose of data-upcycling, i.e. to re-use these data for research. High-quality data standards are essential to ensure the quality and credibility of the research. Moreover, a quality check report can assure a researcher beforehand about the data that they will request access, therefore saving time and effort. The EGA has developed a File Quality Control Report (QC Report) to provide generic quality control reports for Fastq, SAM/BAM/CRAM, and VCF files deposited at EGA. This QC Report will allow users to get information regarding the files submitted within a specific dataset. The data requesters will obtain information such as the quality of reads, mapped reads, number of variants, and other features before starting the requesting process, which will save the efforts and time.Accessing file quality control reportsIn each dataset page, the user can explore the files that it contains by clicking the "files" tab. The Quality Control report of a file has two sections. The first one, contains general information about the file, such as the inferred assembly, total reads, the dataset or study where it comes from, etc. The second section contains plots that summarise interesting information about the file, for example, the base coverage distribution, base quality or mapped reads. The description of each plot is accessible by clicking the "i" button at the top-right corner of each plot box. Technical Description For analysing the fastq, SAM/BAM/CRAM and VCF files, the EGA applies a set of tools widely used in the bioinformatics community. FASTQ: FastQC, recognised as the gold standard tool by the community.Per base sequence quality, per sequence quality scores, per base sequence content, per sequence GC content, sequence duplication levels, etc.SAM/BAM/CRAM: samtools, also the gold standard, generates results plots useful to get an overall idea of the quality of the file.base coverage distribution, base quality, % of mapped reads, % of both mates mapped, singletons, duplicates, etc.VCF: vcftools and bcftools, combined with a custom script to infer the genome assembly.site frequency distribution, Ts/Tv, base changes, indel distribution, etc.

  Documentation access/request-data/quality-control-reports

• RNA-sequencing of tumors from 45 patients with recurrent or metastatic gastric cancer treated with immune checkpoint inhibitors

  Genomic profiling can provide prognostic and predictive information to guide clinical care. Biomarkers that reliably predict patient response to chemotherapy and immune checkpoint inhibition in gastric cancer are lacking. In this work, we used our machine learning algorithm NTriPath to identify a gastric-cancer specific 32-gene signature. Using unsupervised clustering on expression levels of these 32 genes in tumors from 567 patients, we identified four molecular subtypes that were prognostic for survival. We then built a support vector machine with linear kernel and the binary classifier to generate a risk score that is prognostic for 5-year overall survival and validated the risk score using three independent datasets. We also found that the molecular subtypes predicted response to adjuvant 5-fluorouracil and platinum after gastrectomy and immune checkpoint inhibitors in patients with metastatic or recurrent disease. The 32-gene signature is a promising prognostic and predictive biomarker to guide the clinical care of gastric cancer patients and should be validated in a prospective manner. This EGA archive includes both St.Mary hospital cohort samples (n=28) and Yonsei immunotherapy patient samples (n=17).

  Study EGAS00001005588

• H3Africa - Kidney Disease Research Network

  Chronic kidney disease (CKD) affects an estimated 14% of adults in sub-Saharan Africa but very little research has been done on the etiology, progression and prevention of CKD on the continent. As part of the Human Heredity and Health in Africa (H3A) Consortium, the H3Africa Kidney Disease Research Network was established to study prevalent forms of kidney disease in sub-Saharan Africa and increase the capacity for genetics and genomics research. The study is performing comprehensive phenotypic characterization with analysis of environmental and genetic factors from seven clinical centers in two African countries (Ghana and Nigeria) over a five-year period. Approximately 4,000 participants with specified kidney disease diagnoses and 4000 control participants will be enrolled in the four African countries. In addition, approximately 50 families with hereditary glomerular disease will be enrolled. The study includes both pediatric and adult participants ages <1 to 74yrs across a broad spectrum of kidney diseases secondary to hypertension, diabetes, human immunodeficiency virus, sickle cell disease, biopsy-proven glomerular disease and CKD of unknown origin. Clinical and demographic data with biospecimens are collected for assessment of clinical, biochemical and genetic markers of kidney disease.

  Study EGAS00001006558

• Thymic epithelial transplantation for complete DiGeorge syndrome: RNA (2025-07-22)

  Single cell transcriptomics study of thymic transplant biopsies Allogeneic thymus transplantation is the only curative therapy for complete DiGeorge Syndrome (cDGS), a rare severe primary immunodeficiency characterised by athymia. GOSH is one of only two centres worldwide to offer this treatment. Despite a lack of major histocompatibility complex (MHC)-matching between donor and host, transplanted thymus becomes repopulated by recipient bone marrow derived precursor cells and supports development of functional T-cells. The mechanisms underlying thymopoiesis in this context are poorly understood, but over time we observe reconstitution of T-cell immunity, with the ability to produce host naïve T-cells showing a broad T-cell receptor (TCR) repertoire and to generate MHC-restricted T-cell proliferative responses. Although lifesaving, the achieved immunological reconstitution is typically not complete with circulating T-cell numbers usually remaining below the age related normal ranges. Additionally, we observe persistence of donor-derived T-cells of unknown clinical significance. To gain more insight into the mechanisms by which MHC-mismatched transplanted thymus supports T-cell development with self-tolerance, as well as into the basis of suboptimal T-cell immunity, we now aim to investigate immune reconstitution after thymus transplantation in further detail by using single-cell transcriptomics, applied to thymic transplant biopsies and peripheral blood samples collected during standard post-transplant patient care. By identifying which lineages of host- derived cells repopulate the thymic tissue after transplantation, we will be able to address the role of MHC in positive and negative T-cell selection during T-cell differentiation. We will also be able to clarify the exact ontogeny of the persistent donor T-cells, as well as their possible role. Understanding the mechanisms of action of HLA-mismatched transplanted thymus will contribute to treatment optimisation. Additionally, our research provides a unique opportunity to further investigate key immunological concepts, such as tolerance and autoimmunity, challenging existing paradigms in thymus immunology. 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/ . This dataset contains all the data available for this study on 2025-07-22.

  Dataset EGAD00001015648

• INCLUDE Data Hub: NDA GUIDs for Down Syndrome Research

  The INCLUDE (INvestigation of Co-occurring conditions across the Lifespan to Understand Down syndromE) Project is an NIH-wide collaboration that seeks to improve health and quality of life for people with Down syndrome. The INCLUDE Project Data Coordinating Center (DCC) and partners created the INCLUDE Data Hub, a centralized data resource that allows access to large-scale clinical and multi-omics datasets specific to Down syndrome and supports collaborative, cloud-based analysis to accelerate scientific discoveries related to Down syndrome and its co-occurring conditions. The INCLUDE Data Hub includes an innovative researcher data repository, a portal, and a cloud-based platform for data analysis. The portal provides access to de-identified demographics and clinical metadata, as well as multi-omics datasets, including whole genome sequences, transcriptomes, proteomes, and metabolomes. The INCLUDE Data Hub uses a 'registered access' model, whereby users can access the portal and associated data after agreeing to terms of use. From the Data Hub, users can also reach 'controlled access' data (e.g., whole genome sequences) only for those studies for which they have obtained approval by an NIH Data Access Committee through the corresponding dbGaP study. A thoughtful linkage strategy to identify duplicate participants across studies enables researchers to merge multiple datasets and data types to create richer datasets and reduce costly redundancies in large-scale data generation (e.g., -omics) while mitigating potential risks introduced by linkage.Based on recommendations from the NICHD Office of Data Science and Sharing, which completed a comprehensive assessment of existing Privacy Protecting Record Linkage (PPRL) and associated data governance solutions, the INCLUDE DCC and the associated NIH Steering Committee have implemented NIMH Data Archive Global Unique Identifiers (NDA GUIDs) in the INCLUDE Data Hub. The NDA GUID Tool is a government-owned and operated PPRL technology that enables researchers to link data from multiple sources to the same individual without revealing personally identifiable information (PII). With the NDA GUID Tool, the same participant information will return the same GUID whenever or wherever it is entered. The GUID itself is not personally identifiable information or protected health information. Sharing data with NDA GUIDs allows approved researchers to link together data on a single participant, even if the data were collected at different locations or through different studies or are distributed from different data repositories. This dbGaP study enables researchers to access an INCLUDE GUID Mapping File that includes all available NDA GUIDs and their associations to study-specific Participant IDs across studies in the INCLUDE Data Hub. This dbGaP study only distributes NDA GUIDs associated with the INCLUDE Data Hub datasets. To access the associated controlled-access datasets, add the corresponding dbGaP studies to your Data Access Request. A list of these studies is available on the INCLUDE Data Hub Portal: https://portal.includedcc.org/studies.

  Study phs003678

• AmsterdamUMC Data Access Committee for the MAPS study

  The current data access committee reviews and assesses data requests of researchers that seek to gain access to data acquired from the MAping the Peritoneal immune System (MAPS) project as performed at the AmsterdamUMC, Amsterdam, Netherlands.

  Dac EGAC50000000096

• Dataset for 9 samples from the study EGAS00001007891

  This dataset links 9 samples from the study "Phosphoproteomics adds value to treatment recommendations in molecular tumor boards" (EGAS00001007891) to the study EGAS00001007934. Further information about the samples can be found in the respective studies.

  Dataset EGAD50000002316

• cell-free methylated DNA immunoprecipitation and high-throughput sequencing data for samples from liver transplant recpients with graft pathologies

  Bam and indexed bam files after removal of duplicates and trimming of the unique molecular identifiers. Sequencing was performed on NovaSeq 6000 platform.

  Dataset EGAD50000001727

• Clinical Utility of BRCA Research by Inocras, CMC and SMC (CUBRICS)

  This dataset consists of whole-genome sequences from 1,364 Korean breast cancers, with transcriptome data available for most cases

  Dataset EGAD50000001546

• The taxonomic composition of the human microbiome of healthy donors

  Single homogenized human stool samples from five healthy donors and mix were analyzed by shotgun sequencing to generate a baseline for the establishment of humanized microbiome to be transferred into mice.

  Dataset EGAD50000001119

• WGS FASTQ files studied in A first-in-human clinical study of an allogenic iPSC-derived corneal endothelial cell substitute transplantation for bullous keratopathy

  This data set contains 2 paired fastq files (WGS).

  Dataset EGAD50000000947

• johannesburg_20150706_X

  Genotype data and (in binary PLINK format) and imputed data (with merged 1000Gp3 and AGVP reference panel in GEMMA BIMBAM dosage format) for 750 individuals from Respiratory and Meningeal Pathogens Unit in Soweto, South Africa - X chromosome.

  Dataset EGAD00010002580

• NanoString raw data

  NanoString raw data for a noeadjuvant combination PD-L1 plus CTLA-4 blockade trial on patients with cisplatin-ineligible operable urothelial carcinoma. All samples were FFPE tumor samples. Raw probe count data (.RCC files) were generated from nCounter Digital Analyzer (4.0.0.3).

  Dataset EGAD00010001852

• Sequencing data for oesophageal and related samples - BOs release 3 (RNA)

  Dataset EGAD00001003901

• Whole genome bisufite sequencing for smoking and non-smoking mother-child pairs

  WGBS data of whole blood samples from smoking and non-smoking mothers and their children at gestation/birth and follow-up years.

  Dataset EGAD00001000366

• WGS data for medulloblastoma samples (SJMB)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003126

• Low-coverage whole genome sequencing data to study "A biobank of patient-derived pediatric brain tumor models"

  Low-coverage whole genome sequencing data for 30 PDOX models (28 early passages, 4 late passages (2 overlaps)), 3 cell lines, and 21 matching human tumors

  Dataset EGAD00001003545

• sWGS of tumor samples for HGSOC copy-number signatures study

  This dataset contains 319 bam files of shallow WGS data (0.1X) aligned to human genome assembly GRCh37 (hg19) from 300 tumor samples sequenced on HiSeq2500 in SE-50bp mode.

  Dataset EGAD00001004174

• RNA-seq colorectal adenomas NKI-AvL TGO series Gut2009

  The dataset "RNA-seq colorectal adenomas NKI-AvL TGO series Gut2009" includes 2 x 32 fastq files from paired-end mRNA sequencing on Illumina HiSeq2500 for 32 snap-frozen colorectal adenomas.

  Dataset EGAD00001004058

• RNA-seq colorectal carcinomas NKI-AvL TGO series Gut2009

  The dataset "RNA-seq colorectal carcinomas NKI-AvL TGO series Gut2009 " includes 2 x 29 fastq files from paired-end mRNA sequencing on Illumina HiSeq2500 for 29 snap-frozen colorectal carcinomas.

  Dataset EGAD00001004059

• H3Africa H3AChipDesign AWI-Gen

  60 samples from Burkina Faso and Ghana generated for the H3Africa Chip Design Study. The dataset includes BAM, FASTQ and decompressed gVCF files.

  Dataset EGAD00001004448

• Pilot Fetal Cell Atlas_RNAseq (2018-08-20)

  As part of the Human Cell Atlas we will study fetal tissue. . This dataset contains all the data available for this study on 2018-08-20.

  Dataset EGAD00001004305

• Ewing's Sarcoma Whole Genome Sequencing

  54 WGS Ewing's sarcoma samples sequenced at The Hospital for Sick Children Toronto (Adam Shlien's lab) and published on Science 2018. Reference Anderson et al. "Rearrangement bursts generate canonical gene fusions in bone and soft tissue tumors"

  Dataset EGAD00001004589

• Genetics and Networks of Congenital Heart Defects

  Exome sequencing of families with Congenital Heart Defects of diverse sub-phenotypes. Comprises both parent-offspring trios for sporadic cases and multiplex families. Collaboration with David Brook, University of Nottingham. Funded by the British Heart Foundation.

  Dataset EGAD00001002251

• Genome-wide prediction of human embryos

  This dataset includes whole genome sequence information for three individuals (Mother, Father and Newborn) used in this study. Genomes were sequenced using Illumina HiSeq technology. Files included are fastq files in paired read format.

  Dataset EGAD00001002257

• RNA sequencing of 20 intra/extra hepatic bileduct organiods

  This dataset contains RNA sequencing data for 20 intra/extra hepatic bileduct organiods. Data is in BAM format and was processed by STAR.

  Dataset EGAD00001005225

• Whole genome sequencing generated from metastatic gliosarcoma patient samples

  This dataset contains whole genome sequencing data aligned to the b37 reference genome for 4 spatially and temporally distinct tumors from one patient with a matched normal blood sample.

  Dataset EGAD00001005745

• Small variant calling for 110 Egyptian individuals

  This data set comprises WGS small variants and structural variants called in a cohort of 110 Egyptian individuals (10 individuals have been sequenced as part of this study and 100 are from EGAD00001001372/EGAD00001001380).

  Dataset EGAD00001006039

• single-cell ATAC-seq

  Single-cell ATAC-seq data for 5 CLL samples (2 controls, 3 tumor) of the CancerEpiSys-PRECiSe project.

  Dataset EGAD00001005965

• Sci Trans Med - Mouliere et al, 2018. Non-ovarian cancer samples - STM4

  fastq files for shallow whole genome sequencing data as described in Mouliere et al, 2018. Files are those not included in STM2 i.e. these are largely non-ovarian cancer samples

  Dataset EGAD00001006132

• Whole-exome sequencing and microRNA profiling predicted relapse risk of stage I lung adenocarcinomas

  This dataset contains BAM files for RNA-sequencing of stage I lung adenocarcinomas from Asian patients. In total, there are 107 patients and 107 tumor samples.

  Dataset EGAD00001006187

• Bulk RNAseq fastq files

  RNAseq FASTq files from 15 samples from patients with ovarian cancer, 5 samples for each of the 3 tumor immune phenotypes (Infiltrated, Excluded and Desert).

  Dataset EGAD00001006975

• CBD-RAW-RNASEQ-MINI: Mini-bulk RNAseq data

  SmartSeq2 RNAseq data from 16 samples. For further information regarding this dataset, please contact Julian Knight and Alexander Mentzer at contact@combat.ox.ac.uk.

  Dataset EGAD00001007932

• TPM matrix

  TPM matrices of counts from RNAseq data for IMvigor010 from bulk pre-treatment tumors.

  Dataset EGAD00001007653

• mRNA capture sequencing and RT-qPCR for the detection of pathognomonic, novel and secondary fusion transcripts in formalin-fixed paraffin-embedded tissue: a sarcoma showcase

  mRNA capture sequencing data (FASTQ files) of 28 FFPE sarcoma tumors

  Dataset EGAD00001007696

• Genome-wide data Iberian Roma

  VCF file with genome-wide data for 62 Iberian Roma samples.

  Dataset EGAD00001006358

• Cell-free DNA TAPS provides multimodal information for early cancer detection

  TAPS data from 21 patients with HCC, 23 patients with PDAC, 30 non-cancer controls, 4 patients with cirrhosis, and 7 patients with pancreatitis.

  Dataset EGAD00001006871

• Whole exome sequencing datasets for Low-grade Serous Ovarian Carcinoma

  This dataset includes whole exome sequencing reads from 10 normal and 14 cell lines based on Agilent SureSelect XT Human All Exon v6. They are all 2*100bp reads sequenced using Illumina HiSeq4000.

  Dataset EGAD00001006440

• single cell RNAseq data of lung adenocarcinoma

  Single-cell RNA sequencing was performed for cells from five early-stage LUADs and fourteen multi-region normal lung tissues of defined spatial proximities from the tumors.

  Dataset EGAD00001006936

• Response labels from NABUCCO cohort 1 (NCT03387761)

  Data from NABUCCO cohort 1 (NCT03387761). This dataset includes the Response labels used for the analysis of the data. Details about the clinical definitions of Response can be found on the paper (https://doi.org/10.1038/s41591-020-1085-z)

  Dataset EGAD00001006853

• Target pilot trial

  In vitro and in vivo drug screens of tumor cells identify novel therapies for high-risk child cancer

  Dataset EGAD00001008358

• RNA-seq

  This dataset contains the raw sequencing data (Runs) for all 10x Genomics single-cell RNA-seq Experiments.

  Dataset EGAD00001009823

• Raw data for "Spatial and temporal transcriptomics of medulloblastoma with chromothripsis identifies multiple genetic clones that resist to treatment and lead to relapse"

  FASTQ files from Illumina sequencing of 10x Visium experiments.

  Dataset EGAD00001010260

• RNA-seq

  Stranded RNA-seq libraries were performed for 150 ng of mRNA using the TruSeq library kit (Illumina, San Diego, CA, USA). Libraries were sequenced on a NextSeq 2000 (Illumina) in a 2x50bp length.

  Dataset EGAD00001010841

• Dataset for WES PCNSL

  WES sequencing of 23 samples from PCNSL tumor and blood control samples. Sequencing was performed on a NovaSeq 6000 and NextSeq 500 using Agilent SureSelectXT HS Human All Exon V7 and V8. Sequencing was always paired.

  Dataset EGAD00001010847

• Covacta RNAseq counts

  RNA-seq data from PAXgene extracted whole blood of patients enrolled in the COVACTA trial. This dataset includes read counts per gene. Read counts were generated for the Gencode v27 annotation using the summarize Overlaps method from bioC in mode “IntersectionStrict”

  Dataset EGAD00001011164

• High Density SNP Association Analysis of Melanoma: Case-Control and Outcomes Investigation

  This research builds upon an extensive resource of melanoma cases and hospital based controls collected over several years at the U.T. M.D. Anderson Cancer Center. The goal of this research is to identify novel susceptibility and outcome-related genes for melanoma using a systematic genome-wide association-based approach. Our goal is to conduct high-density SNP association and outcome studies. This dbGaP study contains samples from 2000 European ancestry cases and 1000 European ancestry controls using the Illumina OMNI1-Quad SNP chip. As a part of an ongoing R01 project, we have epidemiological data together with candidate gene results for 1000 of the melanoma cases and the controls. With regard to the outcome aspect of our design, as part of our melanoma Specialized Program of Research Excellence (SPORE) grant, our MelCore database contains comprehensive, prospectively maintained clinical information from all melanoma patients included in the study cohort, including primary tumor histopathology and staging information, standard and investigational blood tumor markers, details of surgical and systemic therapies, and extensive follow-up information, including time to relapse or recurrence, pattern of recurrence and survival duration. Finally, we intend to collaborate with the GenoMEL collaboration so we can jointly evaluate each other's findings. The goal of our analysis will be to identify novel genetic factors predisposing the development of melanoma, as well as genetic factors controlling melanoma stage at presentation, recurrence and progression. This study is part of the Gene Environment Association Studies initiative (GENEVA, http://www.genevastudy.org) funded by the trans-NIH Genes, Environment, and Health Initiative (GEI). The overarching goal is to identify novel genetic factors that contribute to melanoma through large-scale genome-wide association studies of 2000 European ancestry cases and 1000 European ancestry controls. Genotyping was performed at the Johns Hopkins University Center for Inherited Disease Research (CIDR). Data cleaning and harmonization were done at the GEI-funded GENEVA Coordinating Center at the University of Washington.

  Study phs000187

• Whole Exome Sequencing of Congenital Diaphragmatic Hernia Patients and Trios

  Congenital diaphragmatic hernia (CDH) is a common and severe birth defect characterized by structural defects of the diaphragm and by pulmonary hypoplasia. Congenital diaphragmatic hernia patient may present either as an isolated phenotype or together with other congenital anomalies in a complex phenotype. Despite the clinical significance of CDH, the underlying genetic and developmental pathways are incompletely understood. In order to establish a catalog of human genetic variation for this condition, we performed whole exome sequencing (WES) on 275 carefully phenotyped individuals with CDH in the Pediatric Surgical Research Laboratories at the Massachusetts General Hospital (Boston, MA, USA) and Boston Children's Hospital (Boston, MA, USA). The exome data generated are valuable for comparison of candidate genes derived from WES of other CDH cohorts or affected kindreds, and to provide ideal candidates for further functional studies with the ultimate goal of enhancing our understanding of the heterogeneous and, possibly, oligogenic molecular etiology of CDH. While familial clustering has been reported in rare kindreds, the majority of probands with CDH have no family history of CDH leading to the hypothesis that de novo variants are an important and relatively frequent etiological mechanism. In the second version of the study, we performed WES analysis on 87 trios, to assess the contribution of de novo mutations in the etiology of diaphragmatic and pulmonary defects and to identify previously unknown candidate genes. This dbGaP submission includes WES data on: (a) 20 new probands, (b) 9 probands also reported in the previous version (dbGaP accession no. phs000783.v1.p1), (c) 174 unaffected parents, including the parents of 67 previously reported probands. Combined analysis with other available cohorts of congenital diaphragmatic hernia revealed a genome-wide enrichment of likely gene-disrupting de novo variants (i.e., nonsense, frameshift or splice site), and missense de novo variants predicted in silico to be damaging.

  Study phs000783

• NHLBI Recipient Epidemiology Donor Evaluation Study (REDS)-III - Red Blood Cell Omics (RBC-Omics) Study

  The Recipient Epidemiology and Donor Evaluation Study-III (REDS-III) is an initiative launched by the National Heart, Lung, and Blood Institute (NHLBI) with the goal to improve transfusion medicine practice, ensure safety and reduce risks. Extensive variation exists in donor iron metabolism, hemoglobin production, and hemolysis. Despite this variation, current blood banking guidelines regulating blood donation frequency, donation volume, and storage time and conditions remain uniform for all donors. The RBC-Omics study proposed to investigate if this approach is appropriate. Specifically, the RBC-Omics study: Established a multi-ethnic cohort of blood donors with well-characterized demographic, behavioral, and donation history. Developed a database linking donations from these blood donors to outcomes in transfusion recipients. Identify genetic factors impacting hemoglobin, donation history, ferritin, and iron metabolism. Identify markers and clinical factors associated with the iron-related disorders pica and restless leg syndrome (RLS). Define the genetic and metabolic basis for donor-specific differences in spontaneous, osmotic and oxidative hemolysis at the end of storage. RBC-Omics study has 13,403 blood donors over the age of 18 that were recruited from December 2013 to December 2015 at four REDS-III blood centers: the American Red Cross (Farmington, CT), the Institute for Transfusion Medicine (ITxM, Pittsburgh, PA), Blood Center of Wisconsin (Milwaukee, WI), and the Blood Centers of the Pacific (San Francisco, CA). All blood donors are healthy volunteers who passed donation screening and were not anemic. The samples were genotyped with a customized Affymetrix Axiom array called the TM-Array. The TM-array was specifically designed to cover genetic variations related to transfusion medicine. Also copy number polymorphisms in the alpha globin, beta globin and Rh gene clusters were added. The genetic variations among different ethnicity groups were considered as well.

  Study phs001955

• A Genome-Wide Association Study of Sporadic ALS in an Irish Population (SIALS) and Sequencing and Analysis of an Irish Human Genome

  Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by loss of motor neurons. Epidemiological studies indicate that 2-5% of cases are familial, usually with an autosomal dominant pattern of inheritance. For a portion of these, causative genes have been identified. The remaining 95% of ALS cases are described as sporadic, and believed to result from a combination of genetic and environmental factors. This study utilized samples from Irish patients with sporadic ALS and Irish control individuals. The aim of the study was to identify susceptibility alleles for ALS in the Irish population. Genome-wide, single-nucleotide polymorphism (SNP) genotyping was undertaken using Illumina 550K version 3 chips. Genotyping data are available on 221 SALS patients and 211 controls. Future work will aim to examine ALS genetic risk at individual sequence level. As an initial step, as of September 2010 we have made available the human genome sequence from a single anonymous male control individual from the SIALS collection. Recent studies generating complete human sequences from Asian, African and European subgroupings have revealed population specific variation and illuminated disease susceptibility loci. The Irish population is of interest because of its location at the periphery of Europe and also the impact its emigrants have had on the genetics of populations in a number of other countries. We have identified sequence variants that may be specific to this population and have identified potentially novel disease associated variants. We describe a novel method for improving SNP calling accuracy at low genome coverage using haplotype information. Overall we demonstrate utility in generating whole genome sequences to test general principles and reveal specific instances of human biology. With increasing access to low cost sequencing we would predict that similar studies will emerge.

  Study phs000127