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• 'Targeted High Throughput Sequencing in Clinical Cancer Settings: Formaldehyde fixed-paraffin embedded (FFPE) tumor tissues, input amount and tumor heterogeneity'

  "Background: Massively parallel sequencing technologies have brought an enormous increase in sequencing throughput. However, these technologies need to be further improved with regard to reproducibility and applicability to clinical samples and settings. Methods: Using identification of genetic variations in prostate cancer as an example we address three crucial challenges in the field of targeted re-sequencing: Small nucleotide variation (SNV) detection in samples of formalin-fixed paraffin embedded (FFPE) tissue material, minimal amount of input sample and sampling in view of tissue heterogeneity.Results: We show that FFPE tissue material can supplement for fresh frozen tissues for the detection of SNVs and that solution-based enrichment experiments can be accomplished with small amounts of DNA with only minimal effects on enrichment uniformity and data variance. Finally, we address the question whether the heterogeneity of a tumor is reflected by different genetic alterations, e.g. different foci of a tumor display different genomic patterns. We show that the tumor heterogeneity plays an important role for the detection of copy number variations, but is of minor importance for the detection of somatic variations.Conclusions: The application of high throughput sequencing technologies in cancer genomics opens up a new dimension for the identification of disease mechanisms. In particular the ability to use small amounts of FFPE samples available from surgical tumor resections and histopathological examinations facilitates the collection of precious tissue materials. However, care needs to be taken in regard to the locations of the biopsies taken, which can have an influence on the prediction of copy number variations. Bearing these technological challenges in mind will significantly improve many large-scale sequencing studies and will - on a long-range - result in a more reliable prediction of individual cancer therapies."

  Study EGAS00001000136

• Spiradenocarcinoma

  • Spiradenocarcinoma is a rare cutaneous sweat gland adnexal cancer with potential for aggressive behaviour. They are classified histologically into low- and high-grade tumours, with morphologically low-grade tumours thought to behave more favourably. However, limited information is available, with only 18 published cases. • We have collected morphologically low-grade spiroadenocarcinomas (one with a lung metastasis) and high-grade spiroadenocarcinomas, as well as some spiradenomas (benign lesions), cylindromas (another type of malignant cutaneous sweat gland adnexal tumour) and hybrid spiradenoma-cylindromas. • H&E-stained sections were reviewed, follow-up was obtained, and immunohistochemistry for Ki-67, p53 and, MYB has been performed. The tumours were solitary, measuring 0.8-7?cm (median: 2.7?cm), with a predilection for the head and neck of elderly patients (median age: 72 years; range 53-92) without gender bias. Histologically, the tumours were multinodular and located in deep dermis and subcutis. A pre-existing spiradenoma was present in all cases. The malignant component was characterized by expansile growth with loss of the dual cell population, up to moderate cytological atypia and increased mitotic activity (median: 10/10 HPF; range 1-28). Additional findings included squamoid differentiation (n=9), necrosis (n=7), and ulceration (n=5). P53 expression was variable and no significant differences were noted in the benign compared with the malignant parts of the tumours. In contrast, in the malignant components the Ki-67 proliferative index was slightly increased, and MYB expression was lost. Follow-up (median: 67 months; range: 13-132) available for 16 patients (84%) revealed a local recurrence rate of 19% but no metastases or disease-related mortality. • Here we wish to exome sequence these cases to define the first genomic landscape for this malignancy.

  Study EGAS00001001799

• Analysis of error profiles in deep next-generation sequencing data

  BackgroundSequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors introduced at various steps of a conventional NGS workflow, such as sample handling, library preparation, PCR enrichment, and sequencing. In this study, we use current NGS technology to systematically investigate these questions.ResultsBy evaluating read-specific error distributions, we discover that the substitution error rate can be computationally suppressed to 10-5 to 10-4, which is 10- to 100-fold lower than generally considered achievable (10-3) in the current literature. We then quantify substitution errors attributable to sample handling, library preparation, enrichment PCR, and sequencing by using multiple deep sequencing datasets. We find that error rates differ by nucleotide substitution types, ranging from 10-5 for A>C/T>G, C>A/G>T, and C>G/G>C changes to 10-4 for A>G/T>C changes. Furthermore, C>T/G>A errors exhibit strong sequence context dependency, sample-specific effects dominate elevated C>A/G>T errors, and target enrichment PCR led to aprox 6-fold increase of overall error rate. We also find that more than 70% of hotspot variants can be detected at 0.1% - 0.01% frequency with the current NGS technology by applying in-silico error suppression.ConclusionsWe present the first comprehensive analysis of sequencing error sources in conventional NGS workflows. The error profiles revealed by our study highlight new directions for further improving NGS analysis accuracy both experimentally and computationally, ultimately enhancing the precision of deep sequencing.

  Study EGAS00001003444

• How to use the EGA search box

  Tips on how to search Tip 1: Use simple and clear keywords No matter what you are searching: a study, a dataset or a committee; the search will look recursively in all the fields of all the entities in the database. Thus, there is no need to specify which type of data you are looking for. Try to use single and specific words and avoid long and complex expressions. Try it out: cancer rna-seq instead of cancer studies using RNA-seq. Tip 2: Narrow your results using search operators Search operators give you more control over the results. They manage the way keywords are used to restrict the search. By default, the search engine applies an OR operator when a space is inserted between two words. Include AND (capitalised) between the keywords in your search in order to show only pages containing both terms. Try it out: Search all the studies based on transcriptomic data, including those ones that use RNA sequencing to obtain this data. Tip 3: Do not worry about details The search engine automatically checks for the most common spelling mistakes of given words and suggests the use of the correct version. It also ignores capital letters and most punctuation so none of these mistakes will hamper the accuracy of your search. Besides, when using a combination of words, the search engine will suggest similar combinations with a higher number of results. Tip 4: Use words that are likely to appear within the text Unfortunately, our search engine is not able to interpret words yet. Therefore, words which do not appear in the body text will not return any result despite them denoting a group of present terms. For instance, if we are looking for studies focused on neurological diseases, using neurological as a keyword would not be the best option. Instead, you should use the name of each neurological disease such as bipolar disorder, schizophrenia or depression. In the same fashion, incomplete words do not return any result. Please include an asterisk (*) before and/or after the incomplete word in order to allow for partial matching. Try it out: canc* instead of canc(without wildcard). Also you can try out *oma, or even *geneti* Tip 5: Narrow down your search by filtering the results You can filter the results by the following options: general, study, and dataset. Under these categories, you will find more sub-filters to refine your search. Make sure that you click on Apply in order to filter the results. You can clear the filtering anytime. Advanced Searches Additional example queries: Search for DUO:0000005 and word lung example query Or write: DUO:0000005 AND lung Search for an exome sequencing study in dbGaP example query Or write: study_type: "exome sequencing" AND repository:dbGaP Search for an exome sequencing study in EGA example query Or write: study_type: "exome sequencing" AND repository:ega Search for a dataset that is at the EGA beacon and with type "Whole genome sequencing" and with number of samples between 100 and 2000 and with technology "Illumina HiSeq 2000" example query Or write: is_in_beacon:true AND dataset_types:"Whole genome sequencing" AND samples:[100 TO 2000] AND dataset_technologies:"Illumina HiSeq 2000" Search for PMIDS example query Or write: pmids:32025007

  Documentation discovery/metadata/search-box

• Single Cell Analysis Program - Transcriptome (SCAP-T)

  This initiative is part of the Single Cell Analysis Program (SCAP) and is funded through the NIH Common Fund (See http://nihroadmap.nih.gov/), which supports cross-cutting programs that are expected to have exceptionally high impact. Common Fund initiatives address key roadblocks in biomedical research that impede basic scientific discovery and its translation into improved human health. In addition, these programs capitalize on emerging opportunities to catalyze progress across multiple biomedical fields. Single cell analysis has recently emerged as an important field of research because technologies have improved in sensitivity and throughput sufficiently to begin measuring and understanding heterogeneity in complex biological systems and correlating it with changes in biological function and disease processes. By profiling individual cells it is possible to resolve rare cells, transient cell states, and the influence of organization and environment on such cells and states, which cannot be described by ensemble measurements. The long-term goal of the SCAP is to accelerate this move towards personalizing health to the cellular level by understanding the link between cell heterogeneity, tissue function and emergence of disease through the discovery, development and translation of innovative approaches which will dramatically change the way cells are characterized. The SCAP will focus on research, which will systematically measure, analyze and model cell-to-cell variation, and identify crucial differences and rare biological states, which may have important functional consequences. Under SCAP, there are three studies to evaluate the cellular heterogeneity using transcriptional profiling of single cells (U01): University of Pennsylvania: Role of single cell mRNA variation in systems associated electrically excitable cells University of Southern California: Evaluation of cellular heterogeneity using patchclamp and RNA-seq of single cells University of California at San Diego: Single cell sequencing and in situ mapping of RNA transcripts in human brains The SCAP has been designed as a five-year program with several components: (1) the collection, analysis and sharing of comprehensive expression datasets to understand the role of heterogeneity in tissues and systemically and identify critical parameters and states; (2) the discovery of new, innovative tools for spatiotemporal imaging, manipulation, analysis and modeling of a biologically relevant population of cells with minimal perturbation; (3) milestone-driven validation and translation of technologies for characterizing single cells in situ meeting the needs of end-users; and (4) development and coordination of a multidisciplinary research community through workshops and other collective endeavors. Further details about the NIH SCAP-T program can be found here http://commonfund.nih.gov/singlecell/. The SCAP-T data sets include the detailed phenotype information, experimental protocols, QC information, RNA-sequencing data and NGS results from human heart and human brain cells. The first data release includes 697 single cells from human brain and heart. The second data release includes an additional 978 single cells from human brain and heart. The third data release includes an additional 1631 single cells from human brain and heart. The fourth data release is a correction to this study, but adds no new cells. The fifth data release includes an additional 2984 single cells from human brain and heart. The sixth data release includes an additional 944 single cells from human brain and heart. The seventh data release includes an additional 1977 single cells from human brain and heart. The SCAP-T data portal provides a customized interface for users to quickly identify and retrieve files by phenotypes, and data properties such as sequencing facility or coverage for all of these 9231 single cells. For more information about the SCAP-T study and the data portal, please visit http://www.scap-t.org.

  Study phs000833

• FHS-Net Social Networks

  Note: Data Use Restrictions: The data must only be used for genetic research projects solely in the area of health-related social-network research. This study compiles detailed information on family and social ties linked to participants in the offspring cohort of the Framingham Heart Study. The investigators took computerized information from self-report data used by the FHS for over 30 years to facilitate health exam scheduling. These tracking sheets asked participants to identify people close to them, which were assumed by the investigators to indicate a social tie. Individuals are listed as "egos" (if the ties are from their perspective) and/or "alters" (if they are linked as a friend or family members to one of the other participants). All egos were FHS offspring participants while alters could be FHS participants in any cohort or non-participants. This information was combined with internal FHS pedigree data on family ties to list family member alters (as well as the nature of their relationship). The resultant dataset therefore includes each ego-alter tie, the nature of their relationship and the start and end dates for their ties for each of seven waves for the offspring study. Due to privacy concerns, all exam dates for individuals are listed relative to the initial FHS exam date. The study investigators chose a random, confidential date, to which all initial exam dates are linked (by number of months from random date to initial exam date). With this information, researchers can have access to the temporal relationships among participants' exam dates while remaining unaware of the actual exam dates for individual participants. During each clinic exam cycle, the participants undergo a detailed examination including physical examination, medical history, laboratory testing, and electrocardiogram. Over the years, other tests (that may not be performed at every exam cycle) have included pulmonary function, lifestyle, physical function, cognitive function questionnaires, and various noninvasive cardiovascular tests including echocardiograms. This study involves phenotypic data from these exams including (when available) basic body measurements (height, weight, blood pressure), laboratory values (blood sugar levels, LDL levels), information on smoking and alcohol use, and tests of depression and cognitive functioning. Important links to apply for individual-level data Data Use Certification Requirements (DUC) Instructions to Request Authorized Access Apply here for controlled access to individual level data Participant Protection Policy FAQ In 1948, researchers recruited men and women from the town of Framingham, Massachusetts, beginning the first round of extensive physical examinations and lifestyle interviews that would later be analyzed for common patterns related to CVD development. Initially, the Framingham Heart Study enrolled 5,209 men and women from the Framingham area who were between the ages of 28 and 62 years. Beginning in 1971, the Framingham Heart Study enrolled 5,124 men and women, who were either offspring of the original cohort or spouses of those offspring. In 2002, 4,095 third generation participants (men and women) were enrolled.

  Study phs000153

• Selenium Chemoprevention: Benefits and Harms

  Selenium is a trace element that may have anti-carcinogenetic effect, but heterogenous treatment effects have been observed. This genome-wide association study investigates if genetic variation modifies the effect of selenium chemoprevention in the Selenium and Celecoxib Trial, a randomized, double-blind, placebo-controlled trial conducted at the University of Arizona Cancer Center. The objective of the clinical trial was to determine whether daily intake of 200 µg/d of selenium as a supplement could reduce the risk for developing metachronous colorectal adenomas. The study participants were recruited between 2001 and 2011. Genome-wide association study was performed for 1,323 study participants who provided blood sample at the time of study entry.

  Study phs002283

• The Genomic Analysis of Medulloblastoma

  Medulloblastoma is a heterogenous disease made up of at least four distinct subtypes of disease which appear to exploit and disrupt naturally occurring developmental pathways of cellular growth and hindbrain development. To better understand the driver mutations of this disease, we performed whole genome sequencing of 37 medulloblastomas and the corresponding normal DNA of the 37 affected children treated at St. Jude Children's Research Hospital. We have found several novel mutations which appear subtype specific. These mutations were checked for frequency in a separate tumor cohort of 56 children with medulloblastoma, also treated on the St. Jude Medulloblastoma 2003 trial, and were tested in several animal models of medulloblastoma for proof of oncogenic potential.

  Study phs000409

• Genomic Psychiatry Cohort (GPC) Whole Genome Sequencing and Genotyping Study

  The Center for Genomic Psychiatry at the University of Southern California (USC), SUNY Downstate and an extensive network of academic medical centers have created the Genomic Psychiatry Cohort (GPC). The GPC consists of a large clinical cohort of patients with schizophrenia, bipolar disorder, and healthy controls. The data generation of genotyping and whole genome sequencing of the GPC has been done in collaboration with the USC and the Broad Institute of MIT and Harvard. Genome-wide association studies are being performed with the samples to identify genetic risks for psychiatric disease. Genotyping is also being used to determine ancestry informative markers and replication of candidate genes. Whole genome sequencing identifies functional variants associated with disease risk.

  Study phs001020

• Genomic Landscape of High-Grade Neuroendocrine Neoplasms

  This project is a multi-omics study of high grade (grade 3) neuroendocrine neoplasms across diverse organs. Genomic analysis using low-pass whole genome sequencing for copy number analysis, whole exome sequencing and whole transcriptomic sequencing using RNAseq were performed. As high grade neuroendocrine neoplasms are highly lethal with a median survival of approximately 7 months, new insights are urgently needed for better prognosis, diagnosis and management. This study focuses on gene and pathway discoveries in this cancer, and includes samples from a diverse set of organs, including the lungs, gastroenteropancreatic tract, breast, prostate, head and neck and bladder. This study was made possible by a generous donation from The Helen B. Rodde Fund.

  Study phs002070

• Improved Detection and Identification of Microsatellite Instability Features in Colorectal Cancer

  In this study, we analyzed a series of colorectal cancers using a new sequencing technology that sequences more than 200 microsatellite regions in parallel. With this technology, we evaluated mono-, di- , tri- and tetranucleotide repeats to provide a broad spectrum of microsatellite instability (MSI) events. This deep sequencing technology provides greater than 2000X coverage and eliminates the need for PCR amplification. Because every read corresponds to a single DNA molecule, we eliminated artifacts introduced by PCR that obscured true MSI events. Also included in our analysis is a new method for detection of somatic copy number changes in 83 cancer genes, with which we can infer chromosomal instability (CIN) status.

  Study phs001914

• Mega-GWAS ALS I

  Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disorder clinically characterized by rapidly progressive paralysis and death due to respiratory failure, typically within two to three years of symptom onset. The number of ALS cases across the globe will increase to nearly 400,000 in 2040, predominantly due to aging of the population. Unraveling the genetics underlying ALS provides insights into the cellular mechanism leading to motor neuron death and provides targets for therapeutic intervention. We performed a genome-wide association study involving a meta-analysis of 20,806 ALS cases and 59,804 controls. The current study release makes available genotype data of the 15,480 subjects assayed in the Laboratory of Neurogenetics for this effort.

  Study phs000101

• Cutaneous Melanoma GWAS Combining Multiple Populations and Risk Phenotypes

  Most genetic susceptibility to cutaneous melanoma (CM) remains to be discovered. Meta-analysis genome-wide association study (GWAS) of 36,760 melanoma cases (67% newly-genotyped) and 375,188 controls identified 54 significant loci with 68 independent SNPs. Analysis of risk estimates across geographical regions and host factors suggests the acral melanoma subtype is uniquely unrelated to pigmentation. Combining this meta-analysis with nevus count and hair colour GWAS, and transcriptome association approaches, uncovered 31 potential secondary loci, for a total of 85 CM susceptibility loci. These findings provide substantial insights into CM genetic architecture, reinforcing the importance of nevogenesis, pigmentation, and telomere maintenance together with identifying potential new pathways for CM pathogenesis.

  Study phs001868

• NHLBI TOPMed - NHGRI CCDG: UCSF Atrial Fibrillation Study

  The University of California San Francisco (UCSF) Cardiovascular Research Institute (CVRI) Resource in Arteriosclerosis and Metabolic Disease is an ongoing multi-ethnic study of adults ≥ 18 years of age which was started in 1989 and now includes 28,000 participants recruited from the UCSF medical system. Within the Resource lies data and biospecimens from nearly 1,000 patients presenting to the electrophysiology laboratory for electrophysiology procedures that were densely phenotyped for electrophysiologic characteristics with biospecimens collected from various intra and extra-cardiac chambers. Phenotyping of all participants was achieved via interview and review of medical records. A subset of 113 participants with early-onset atrial fibrillation underwent WGS as a part of the TOPMed Program.

  Study phs001933

• Cryptic Splice Mutation in the Fumarate Hydratase Gene in Patients With Clinical Manifestations of Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC)

  Four patients with hysterectomy were evaluated for biochemical and molecular evidence of autosomal dominant Fumarate Hydratase (FH) alterations causing Hereditary Leiomyomatosis and Renal Cell Cancer (HLRCC). HLRCC is an autosomal dominant condition characterized by the development of cutaneous and uterine leiomyomas, and risk for development of an aggressive form of papillary renal cell cancer. Enzyme assay, western blot analyses, direct nanopore RNA sequencing, and whole genome sequencing (WGS) were utilized. The study identified a cryptic splice mutation in intron 9 of the FH gene that results in retention of 57 base pairs of intronic sequence in the affected allele of the mature FH mRNA.

  Study phs003381

• ROBUST (NCT02285062)

  The ROBUST clinical trial is a Phase III, randomized, double-blind, placebo-controlled study designed to compare the efficacy and safety of lenalidomide plus R-CHOP chemotherapy (R2-CHOP) versus placebo plus R-CHOP in newly diagnosed Diffuse Large B-cell Lymphoma (DLBCL). Molecular data was collected for all patients at screening, but the only patients of the Activated B-cell (ABC) cell-of-origin subtype were eligible for study inclusion and clinical follow-up. We have performed unsupervised clustering on this cohort and identified 7 novel transcriptional subtypes of DLBCL, one of which represents a high-risk subset of patients with high MYC expression, ABC-associated biology, and low immune infiltration.

  Study EGAS50000000333

• Genomics of Acute Myeloid Leukemia

  Sequence data from the Genomics of AML PPG program at Washington University since 2009 is made available. This repository contains data from tumors (bone marrow or peripheral blood) from Acute Myeloid Leukemia (AML) and several other related disorders - myelodysplastic syndromes (MDS), secondary AML (sAML) and therapy-related AML (tAML). It also contains matched normal data (skin or buccal swab) and healthy donors for comparison. A variety of DNA sequencing assays were used, including whole genome sequencing (WGS), exome sequencing, targeted panels of AML genes, or targeted panels for validation. Other modalities, including RNA-seq, small RNA-seq, whole genome bisulfite sequencing, CHIP-seq, ATAC-seq, and single-cell RNAseq are also represented.

  Study phs000159

• South Asia Rheumatic Heart Disease Genetics Network

  Rheumatic heart disease (RHD) is a major cause of cardiovascular death and disability amongst young adults. Building on a sample collection established for and genotyped in several earlier successful candidate gene studies, this case-control study investigated host genetic susceptibility to RHD using a genome-wide approach. The current dataset comprises over 850 individuals recruited in Uttar Pradesh, India, including cases of RHD based on echocardiographic diagnosis and controls recruited on the basis of normal echocardiograms. For this analysis all available samples were genotyped using the Illumina HumanCore-24 BeadChip platform. Efforts are now underway to establish new sample collections in other areas of India as well as Pakistan and later other neighbouring countries.

  Study EGAS00001003565

• Multi-layered molecular characterization defines prognostic subtypes of lung adenocarcinoma in Asian never-smokers

  Multi-layered genomic studies such as the TCGA project have greatly advanced our understanding on molecular pathogenesis of lung cancer. For Asian nonsmoker patients, however, majority of studies have been limited to mutational analyses, emphasizing ethnic differences in driver mutations (e.g. more frequent EGFR mutations and ALK fusions). In essence, a comprehensive multi-layered characterization that could lead to molecular etiology and patient stratification scheme to be translated into clinical applications for this patient group is still missing. Here we report molecular profiling of tumor and matched normal tissues from 114 non-small-cell lung adenocarcinoma patients using whole exome sequencing, transcriptome sequencing, and array comparative genomic hybridization (CGH).

  Study EGAS00001003705

• Genetic landscape of pediatric Medulloblastoma

  Medulloblastoma is a heterogenous disease made up of at least four distinct subtypes of disease which appear to exploit and disrupt naturally occurring developmental pathways of cellular growth and hindbrain development. To better understand the driver mutations of this disease, we performed whole genome sequencing of 37 medulloblastomas and the corresponding normal DNA of the 37 affected children treated at St. Jude Children's Research Hospital. We have found several novel mutations which appear subtype specific. These mutations were checked for frequency in a separate tumor cohort of 56 children with medulloblastoma, also treated on the St. Jude Medulloblastoma 2003 trial, and were tested in several animal models of medulloblastoma for proof of oncogenic potential.

  Study EGAS00001000347

• Correction of the cytosine deamination artifacts in FFPE-based sequencing experiments

  Formalin-fixed paraffin-embedded (FFPE) samples are widely used in research and diagnostics, but cytosine deamination during fixation introduces sequencing artifacts, particularly C>T substitutions, which complicate reliable mutation detection. In this study, we systematically evaluated five computational methods and an enzymatic repair approach for FFPE artifact removal, as well as their combined application, using a custom dataset based on whole exome sequencing. Our results demonstrate that while computational strategies improve data quality, the enzymatic approach provides the most effective artifact correction. The study provides guidelines for both computational and enzymatic artifact correction strategies for reliable downstream analyses.

  Study EGAS50000001354

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Genetic Epidemiology of COPD Study (COPDGene)

  Cohort Description The Genetic Epidemiology of COPD (COPDGene) study is a non-interventional, multicenter, longitudinal, case-control study at 21 US sites of smokers with a ≥10 pack-year history of smoking, with and without COPD, and healthy never smokers. The initial goal was to characterize disease-related phenotypes and explore associations with susceptibility genes. Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 3683 COPDGene participants in C4R. Wave 2 questionnaire data includes 447 variables for up to 2191 COPDGene participants in C4R. Dried Blood Spot/Serosurvey data includes 7 variables for up to 1692 COPDGene participants in C4R. Derived data includes 43 variables for up to 4082 COPDGene participants in C4R. Phenotype data includes 113 variables for up to 4082 COPDGene participants in C4R.

  Study phs002910

• EGAD00000000054

  NCI-H209 is an immortal cell line derived from a bone marrow metastasis of a patient with small cell lung cancer, taken before chemotherapy. The specimen showed histologically typical small cells with classic neuroendocrine features. NCI-BL209 is an EBV-transformed B-cell line derived from the same patient as the small cell lung cancer cell line, NCI-H209

  Dataset EGAD00000000054

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000612

• Whole exome sequencing of a cold agglutinin disease patient

  We performed whole exome sequencing of bone marrow monoclear cells derived from a cold agglutinin disease patient. Aim of our study is to elucidate the pathogenesis of hemolytic anemia.

  Study JGAS000583