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• The genotype of LAM disease

  Tumor biopsies from LAM disease were retrospectively analyzed by multiple techniques to characterize the alterations in patients ,to elucidate the landscape of genetic/genomic alterations.

  Dataset EGAD00001005363

• Somatic evolution in the non-neoplastic IBD affected colon

  Whole genome and whole exome sequencing data supporting the manuscript 'Somatic evolution in the non-neoplastic IBD affected colon' by Sigurgeir Olafsson et al.

  Dataset EGAD00001006061

• Team

  The Team Mallory Freeberg Roderic Guigó Arcadi Navarro Helen Parkinson Jordi Rambla Ana T. Alonso Silvia Bahena Àlex Bedmar Kenneth Buckley Aldar Cabrelles Ángel Carreño Marcos Casado Giulia Cellerino Amy Curwin Teresa D'Altri Abeer Fadda Teresa Garcia Sara Gregorio Max Fischer Bela Juhasz Oriol Lopez-Doriga Mireia Marin Óscar Martínez Andrea Mero Akiris Moctezuma Aurora Moreno Liina Nagirnaja Francesc de Puig Santiago Rensonnet Gabriele Rinck Aravind Sankar Andres Silva Coline Thomas Sabela de la Torre Gemma Vicente The EGA Team at the CRG co-manages the European Genome and phenome Archive together with the EGA Team at the European Bioinformatics Institute. In addition to maintaining and distributing data, we enrich the contents of the EGA contributing with our knowledge about genomics and the relationship between genomes and phenomes. Previous Team Members Alexander Vikhorev Jeff Almeida-King Mario Alberich Sergi Aguilo Pablo Arce Minjie Ding Alfred Gil Leslie Glass Jag Kandasamy Vasudev Kumanduri llkka Lapalainen Audald Lloret i Villas Sira Martinez Anand Mohan Dietmar Orth Justin Paschall Saif Ur Rehman Gary Saunders Thomas Smith Ashutosh Shimpi Marc Sitges Dhvani Solanki Giselle Kerry Nino Spataro Dylan Spalding Matthieu Vizuete-Forster Cristina Yenyxe Gonzalez Garcia Paul Flicek Anna Foix Emilio Garcia Rios Jorge Izquierdo Roberto Ariosa Marta Ferri Peradalta Daniel Barrowdale Babita Singh Umuthan Uyan Aleix Canalda Dona Shaju Mauricio Moldes Carles Garcia Frédéric Haziza Alegria Aclan Lauren Fromont Alvis Brazma Marta Huertas Arnau Soler Gemma Milla Claudia Vasallo Aina Jené Csaba Halmagyi Raül Garcia Thomas Keane Mei Gascón

  Documentation about/team

• Somatic mutation rates scale with lifespan across mammals

  The rates and patterns of somatic mutation in normal tissues are largely unknown outside of humans. Comparative analyses can shed light on the diversity of mutagenesis across species and on long-standing hypotheses regarding the evolution of somatic mutation rates and their role in cancer and ageing. Here, we used whole-genome sequencing of 208 intestinal crypts from 56 individuals to study the landscape of somatic mutation across 16 mammalian species. We found somatic mutagenesis to be dominated by seemingly endogenous mutational processes in all species, including 5-methylcytosine deamination and oxidative damage. With some differences, mutational signatures in other species resembled those described in humans, although the relative contribution of each signature varied across species. Remarkably, the somatic mutation rate per year varied greatly across species and exhibited a strong inverse relationship with species lifespan, with no other life-history trait studied displaying a comparable association. Despite widely different life histories among the species surveyed, including ~30-fold variation in lifespan and ~40,000-fold variation in body mass, the somatic mutation burden at the end of lifespan varied only by a factor of ~3. These data unveil common mutational processes across mammals and suggest that somatic mutation rates are evolutionarily constrained and may be a determinant of lifespan.

  Dataset EGAD00001008032

• RNA sequencing of high hyperdiploid and ETV6/RUNX1-positive pediatric acute lymphoblastic leukemia

  We performed RNA-sequencing of high hyperdiploid and ETV6/RUNX1-positive ALL cases by using the Human Ribo-Zero rRNA Removal Kit to investigate the gene expression in high hyperdiploid ALL.

  Study EGAS00001003079

• Targeted DNA sequencing on 37 Merkel Cell Carcinomas from New Zealand with known Merkel cell polyomavirus status

  To determine the genomic landscape of NZ virus-negative MCCs (VN-MCC), assess genomic evolution in metastases, and catalogue the distribution of TP53 and RB1 variants from international studies.

  Study EGAS00001006873

• Raw sequencing data of PERMED-01 trial

  Targeted sequencing (t-NGS) of frozen advanced cancers tissue was established with three panels covering 395 to 560 candidate cancer genes. Sequencing was done using the 2x150-bp paired-end technology on the Illumina MiSeq and NextSeq500 platforms. The DNA libraries of all coding exons were done with the HaloPlex Target Enrichment System (Agilent, Santa Clara, CA, USA).

  Dataset EGAD00001006289

• Targeted amplicon sequencing on 218 samples from Stage 1 epithelial ovarian cancer biopises

  BAM files (aligned against the hg38 genome) from a targeted amplicon sequencing (139 genes) experiment (median depth 1000X) on 218 samples from Stage 1 epithelial ovarian cancer biopises. Samples labeled "bis" or "tris" with the same ID are relapses; "left" or "right" samples indicate, in the case of bilateral tumor, from which ovary the sample was taken.

  Dataset EGAD00001006873

• HuBMAP: High Resolution 3D Mapping of Cellular Heterogeneity Within Multiple Types of Mineralized Tissues

  The overall goal of the study was to generate 3D single cell maps of healthy human knee cartilage. Articular cartilage from the weightbearing and non-weightbearing regions of the femoral condyles in healthy knees from young donors (n=12) was analyzed by bulk RNA-sequencing (RNA-Seq), single nuclei RNA (snRNA-seq) and ATAC-sequencing and by spatial transcriptomic methods (GeoMx, MERFISH and Xenium). These multimodal data and additional single cell RNA-sequencing (scRNA-seq) data were integrated to generate a comprehensive molecular, genomic and function annotation of chondrocyte populations. Regulatory mechanisms were derived by linking motifs in expressed genes, transcription factors and chromatin organization.

  Study phs003721

• Copy-choice recombination during mitochondrial L-strand synthesis causes DNA deletions

  Mitochondrial DNA (mtDNA) deletions are associated with mitochondrial disease, and also accumulate during normal human ageing. The mechanisms underlying mtDNA deletions remain unknown although several models have been proposed. Here we use deep sequencing to characterize abundant mtDNA deletions in patients with mutations in POLG, the gene encoding mitochondrial DNA polymerase, and show that these have distinct directionality and repeat characteristics. Furthermore, we recreate the deletion formation process in vitro using only purified mitochondrial proteins and defined DNA templates. Based on our in vivo and in vitro findings, we conclude that mtDNA deletion formation involves copy-choice recombination during replication of the mtDNA light strand.

  Study EGAS00001003148

• Mapping_regulatory_variation_in_sensory_neurons_using_IPS_lines_from_the_HIPSCI_project

  Sensory neurons are nerve cells that are activated by sensory input such as heat, light and convey information to the brain. Although a key cell type in complex organisms, human sensory neurons are challenging to study because they are impossible to obtain from living donors. We have collaborated with the Neucentis Pharmaceutical Research Unit to differentiate sensory neuron like cells from human induced pluripotent stem cells derived as part of the Human Induced Pluripotent Stem Cells Initiative. We will sequence RNA from 100 IPS lines derived from healthy individuals and perform RNA-seq on the differentiated cells to identify noncoding variants that alter gene expression in human sensory neurons.

  Study EGAS00001001149

• RNA-seq of uncultured CD112high and CD112low long-term(LT) human hematopoietic stem cells (HSC) and cultured and lentiviral transduced (CTRL, INKA1-OE) LT- and short-term HSC from umbilical cord blood

  We performed RNA-sequencing to elucidate the biological pathways (1) altered by INKA1 overexpression in LT-HSC and ST-HSC that may contribute to the induced transient restraint in generating proliferative hematopoietic output in vivo and in vitro; and (2) that underlie the differential in vitro priming and regeneration phenotypes of CD112high and CD112low LT-HSC. Therefore, we prospectively isolated indicated subpopulations from 3 independent human umbilical cord blood pools and subjected them either to RNA-sequencing directly or following culture, lentiviral transduction and purification of the transduced cell fractions.

  Study EGAS00001004768

• Pan-tumor genomic biomarkers for personalization of PD-1 checkpoint blockade based immunotherapy

  Tumor mutation burden (TMB) and a T-cell-inflamed gene expression profile (GEP) independently predict clinical outcome in pembrolizumab-treated patients in 22 indications and stratify distinct targets of resistance biology.

  Study phs001572

• WTCCC3 case-control study for Primary Biliary Cirrhosis

  Genome-wide association scan was performed in 1,840 cases of primary biliary cirrhosis and 5,163 controls. Replication of new associations was tested in an independent set of 620 cases and 2,514 controls.

  Study EGAS00000000039

• Variant calling for UPST-SCCHN3 cohort

  Tumor versus Germline variant calling on UPST-SCCHN3 cohort

  Dataset EGAD50000002178

• NANOPORE_TALL_t_14_16_translocation

  Nanopore sequencing for patients with t(14;16) translocated T-ALL

  Dataset EGAD50000001785

• WXS_TALL_t_14_16_translocation

  Whole exome-sequencing for patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001783

• WGS_TALL_t_14_16_translocation

  WGS data for patients with t(14;16) translocated T-ALL.

  Dataset EGAD50000001782

• Targeting Heterochromatin Eliminates Malignant Stem Cells in Chronic Myelomonocytic Leukemia Through Reactivation of Retroelements and Innate Immune pathways

  RNA-sequencing, ATAC-sequencing, CUT&Tag-sequencing, data from CMML patient and aged-matched healthy donor CD34+ cells. RNA-sequencing data from patient CD34+ cells after treatment for 4 days with decitabine or UNC0638 inhibitors, alone or together, or left untreated

  Dataset EGAD50000000542

• Duplex sequencing of selected breast cancer patients

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primaty tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000769

• WES of breast cancer patients and controls

  Investigation of post-zygotic and germline variants using whole exome and ultra-deep duplex sequencing in paired uninvolved margin and primary tumor samples from 126 breast cancer patients with differing survival outcomes, with skin or blood samples as reference. Pairs of uninvolved margin and blood samples were also collected for 15 reduction mammoplasty patients without personal or familial history of cancer, serving as controls.

  Dataset EGAD50000000770

• 16SV4 ribosomal RNA gene sequencing data

  16SV4 ribosomal RNA gene sequencing data of GI samples and associated mixed community cultures collected from pediatric patients at risk for IBD.

  Dataset EGAD50000000485

• Sequencing data for oesophageal and related samples - OACs release 1 (RNA)

  Dataset EGAD00001002259

• Telomere attrition becomes an instrument for clonal selection in aging hematopoiesis and leukemogenesis

  Whole genome sequencing of 288 single-cell-derived blood colonies from 3 individuals with splicing factor-mutated clonal hematopoiesis.

  Dataset EGAD00001015640

• WGS data for medulloblastoma samples (MDT-AP)

  WGS data of medulloblastoma tumor/control pairs.

  Dataset EGAD00001003125

• GM18507 direct library preparation (DLP) single-cell genomes

  Microfluidic direct library preparation (DLP) single-cell whole-genome BAM files for near-diploid immortalized lymphoblastoid cell line GM18507.

  Dataset EGAD00001003148

• 184-hTERT-L2, SA501X3F, and SA501X4F bulk genomes

  Bulk whole-genome BAM files for 184-hTERT-L2, SA501X3F, and SA501X4F.

  Dataset EGAD00001003151

• Sequencing data for ICGC Oesophageal Adenocarcinoma tissue samples - barretts_1

  Samples from Ross Innes et. al 2015 - doi:10.1038/ng.3357

  Dataset EGAD00001001394

• Single cell ATAC sequencing

  Paired-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics single cell ATAC sequencing following manufacturer's protocol (CG000168 User Guide RevB) for chemistry version 1.0 and targeting 10000 nuclei per sample. Libraries were sequenced using Illumina HiSeq4000 using recommended cycling parameters.

  Dataset EGAD00001007675

• Single cell TCR sequencing

  Paired-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics single cell TCR sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina NovaSeq 6000 using recommended cycling parameters.

  Dataset EGAD00001007674

• Single cell BCR sequencing

  Paired-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics single cell BCR sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina NovaSeq 6000 using recommended cycling parameters.

  Dataset EGAD00001007673

• 5' single cell RNA sequencing

  Pared-end fastq files of 22 AML and 2 normal bone marrow samples were generated using 10x Genomics 5' single cell RNA sequencing following manufacturer's protocol (CG000086 User Guide RevG) for chemistry version 1.0 and targeting 10000 cells per sample. Libraries were sequenced using Illumina HiSeq 4000 using recommended cycling parameters.

  Dataset EGAD00001007672

• CGH Array

  DNA samples were extracted from peripheral blood lymphocytes using commercially available kit (Puregene Core Kit A, Qiagen) according to manufacturer's protocol. Agilent SurePrint G3 Human CGH Microarray 180K platform was used for screening of copy number aberrations (CNAs) using array-CGH protocol recommended by manufacturer (Agilent Technologies), data mining and interpretation of array-CGH results was performed in same manner as in our previously published results.

  Dataset EGAD00001007743

• Dataset on keratinocytic gene expression pattern in Hidradenitis suppurativa

  Human skin samples were obtained from HS patients after informed consent (Ethical vote, University of Würzburg; No. 306/12). Lesional and perilesional were taken and epidermis and dermis separated. Isolated epidermal keratinocytes were further processed for RNA isolation. mRNA was extracted from five pairwise-matched lesional and perilesional epidermal HS pellets and RNA sequencing was performed.

  Dataset EGAD00001008005

• Paired RNA sequencing of 30 samples RRMM (multiple myeloma)

  Paired RNA sequencing of 30 samples RRMM using Illumina TruSeq stranded mRNA kit and either HiSeq2000 or HiSeq X Ten for sequencing.

  Dataset EGAD00001009680

• Genomic Characteristics of Myeloproliferative Neoplasms in Patients Exposed to Ionizing Radiation following the Chernobyl Nuclear Accident

  The study "Genomic Characteristics of Myeloproliferative Neoplasms in Patients Exposed to Ionizing Radiation following the Chernobyl Nuclear Accident" was designed as case-control study. We studied genomic characteristics of chronic Philadelphia chromosome-negative myeloproliferative neoplasm (MPNs) in Ukrainian patients who were previously exposed to Ionizing Radiation (IR) due to Chernobyl accident in comparison to unexposed MPN patients and controls (previously exposed to IR due to Chernobyl accident and unexposed people who were not diagnosed with any oncological condition at the moment of DNA sampling).

  Study phs001761

• Gene expression profiling by RNAseq of multiple cell types derived from patients with LSD1 mutations and healthy controls, and in isogenic cell lines with LSD1 mutation introduced by CRISPR-Cas9

  Cell lines (fibroblasts, reprogrammed from them hiPSCs and differentiated from hiPSCs endoderm, mesoderm and neuronal cells) derived from two male CPRF patients carrying distinct LSD1 mtuations and their healthy fathers as controls were subjected to gene expression analysis by bulk RNAseq to identify mis-regulated genes. Some cell lines were subject to treatment with HDAC inhibitor valproic acid (VPA) or DMSO as controls and also underwent RNAseq analysis. Two isogenic LSD1 mutant hiPSC lines with CRISPR-edited Family B LSD1 mutation were also used for RNAseq analysis (after endoderm differentiation, with or without VPA treatment).

  Study EGAS00001008240

• Inter and intra - tumor heterogeneity in Colorectal Cancer

  We used high depth massive parallel sequencing analyses to study 27 CRC (colorectal cancer) patients, with a total of 97 tumors (both primary and matched metastases) in addition to healthy control samples. We found inter-tumor concordance for coding mutations; in contrast, gene copy numbers were found to be highly discordant between primary tumors and metastases as validated by fluorescent in-situ hybridization. in a further step, we dissected a single tumor into 68 spatially defined samples and sequenced them separately. Here we identify evenly distributed coding mutations in APC and TP53 in all tumor areas, yet highly variable gene copy numbers in numerous genes.

  Study EGAS00001002150

• A110632A

  Whole genome sequencing for single cells for library A110632A 1151 cells; filetype=bam

  Dataset EGAD00001007094

• A110632B

  Whole genome sequencing for single cells for library A110632B 892 cells; filetype=bam

  Dataset EGAD00001007095

• A118833A

  Whole genome sequencing for single cells for library A118833A 919 cells; filetype=bam

  Dataset EGAD00001007096

• A118833B

  Whole genome sequencing for single cells for library A118833B 1147 cells; filetype=bam

  Dataset EGAD00001007097

• A118845B

  Whole genome sequencing for single cells for library A118845B 1209 cells; filetype=bam

  Dataset EGAD00001007098

• A118869A

  Whole genome sequencing for single cells for library A118869A 1165 cells; filetype=bam

  Dataset EGAD00001007099

• A118869B

  Whole genome sequencing for single cells for library A118869B 1124 cells; filetype=bam

  Dataset EGAD00001007100

• A95626A

  Whole genome sequencing for single cells for library A95626A 1040 cells; filetype=bam

  Dataset EGAD00001007103

• A95634B

  Whole genome sequencing for single cells for library A95634B 1335 cells; filetype=bam

  Dataset EGAD00001007105

• A95646A

  Whole genome sequencing for single cells for library A95646A 1071 cells; filetype=bam

  Dataset EGAD00001007106

• A95653B

  Whole genome sequencing for single cells for library A95653B 1342 cells; filetype=bam

  Dataset EGAD00001007107

• A95663B

  Whole genome sequencing for single cells for library A95663B 1364 cells; filetype=bam

  Dataset EGAD00001007108

• A95675A

  Whole genome sequencing for single cells for library A95675A 668 cells; filetype=bam

  Dataset EGAD00001007109

• A95731B

  Whole genome sequencing for single cells for library A95731B 1307 cells; filetype=bam

  Dataset EGAD00001007110

• A96115B

  Whole genome sequencing for single cells for library A96115B 1201 cells; filetype=bam

  Dataset EGAD00001007112

• A96118A

  Whole genome sequencing for single cells for library A96118A 1193 cells; filetype=bam

  Dataset EGAD00001007113

• A96130B

  Whole genome sequencing for single cells for library A96130B 1267 cells; filetype=bam

  Dataset EGAD00001007114

• A96178A

  Whole genome sequencing for single cells for library A96178A 788 cells; filetype=bam

  Dataset EGAD00001007115

• A96178B

  Whole genome sequencing for single cells for library A96178B 846 cells; filetype=bam

  Dataset EGAD00001007116

• A96181C

  Whole genome sequencing for single cells for library A96181C 1216 cells; filetype=bam

  Dataset EGAD00001007117

• A96225B

  Whole genome sequencing for single cells for library A96225B 959 cells; filetype=bam

  Dataset EGAD00001007119

• A96225C

  Whole genome sequencing for single cells for library A96225C 1034 cells; filetype=bam

  Dataset EGAD00001007120

• A96240A

  Whole genome sequencing for single cells for library A96240A 1493 cells; filetype=bam

  Dataset EGAD00001007121

• A98172A

  Whole genome sequencing for single cells for library A98172A 898 cells; filetype=bam

  Dataset EGAD00001007123

• A98256A

  Whole genome sequencing for single cells for library A98256A 1372 cells; filetype=bam

  Dataset EGAD00001007124

• A98256B

  Whole genome sequencing for single cells for library A98256B 1437 cells; filetype=bam

  Dataset EGAD00001007125

• A98257B

  Whole genome sequencing for single cells for library A98257B 1286 cells; filetype=bam

  Dataset EGAD00001007126

• A98258B

  Whole genome sequencing for single cells for library A98258B 1357 cells; filetype=bam

  Dataset EGAD00001007127

• A98274B

  Whole genome sequencing for single cells for library A98274B 1295 cells; filetype=bam

  Dataset EGAD00001007128

• A98282A

  Whole genome sequencing for single cells for library A98282A 1198 cells; filetype=bam

  Dataset EGAD00001007129

• A98283A

  Whole genome sequencing for single cells for library A98283A 1137 cells; filetype=bam

  Dataset EGAD00001007130

• A98285A

  Whole genome sequencing for single cells for library A98285A 1422 cells; filetype=bam

  Dataset EGAD00001007131

• A98295B

  Whole genome sequencing for single cells for library A98295B 1381 cells; filetype=bam

  Dataset EGAD00001007132

• A110673B

  Whole genome sequencing for single cells for library A110673B 1153 cells; filetype=bam

  Dataset EGAD00001007603

• A118830A

  Whole genome sequencing for single cells for library A118830A 912 cells; filetype=bam

  Dataset EGAD00001007604

• A118862A

  Whole genome sequencing for single cells for library A118862A 1070 cells; filetype=bam

  Dataset EGAD00001007605

• A118862B

  Whole genome sequencing for single cells for library A118862B 1152 cells; filetype=bam

  Dataset EGAD00001007606

• A95623B

  Whole genome sequencing for single cells for library A95623B 1363 cells; filetype=bam

  Dataset EGAD00001007608

• A95697B

  Whole genome sequencing for single cells for library A95697B 1233 cells; filetype=bam

  Dataset EGAD00001007610

• A95700A

  Whole genome sequencing for single cells for library A95700A 1172 cells; filetype=bam

  Dataset EGAD00001007611

• A95703A

  Whole genome sequencing for single cells for library A95703A 740 cells; filetype=bam

  Dataset EGAD00001007612

• A96233A

  Whole genome sequencing for single cells for library A96233A 637 cells; filetype=bam

  Dataset EGAD00001007622

• A95730A

  Whole genome sequencing for single cells for library A95730A 739 cells; filetype=bam

  Dataset EGAD00001007614

• A96114A

  Whole genome sequencing for single cells for library A96114A 798 cells; filetype=bam

  Dataset EGAD00001007615

• A96124B

  Whole genome sequencing for single cells for library A96124B 1241 cells; filetype=bam

  Dataset EGAD00001007616

• A96155C

  Whole genome sequencing for single cells for library A96155C 1316 cells; filetype=bam

  Dataset EGAD00001007617

• A96162A

  Whole genome sequencing for single cells for library A96162A 1505 cells; filetype=bam

  Dataset EGAD00001007618

• A96183B

  Whole genome sequencing for single cells for library A96183B 1191 cells; filetype=bam

  Dataset EGAD00001007619

• A96226B

  Whole genome sequencing for single cells for library A96226B 1274 cells; filetype=bam

  Dataset EGAD00001007621

• A98168A

  Whole genome sequencing for single cells for library A98168A 1294 cells; filetype=bam

  Dataset EGAD00001007624

• A98168B

  Whole genome sequencing for single cells for library A98168B 1290 cells; filetype=bam

  Dataset EGAD00001007625

• A98234A

  Whole genome sequencing for single cells for library A98234A 1240 cells; filetype=bam

  Dataset EGAD00001007626

• A98244A

  Whole genome sequencing for single cells for library A98244A 1271 cells; filetype=bam

  Dataset EGAD00001007628

• A98253A

  Whole genome sequencing for single cells for library A98253A 1250 cells; filetype=bam

  Dataset EGAD00001007629

• A98253B

  Whole genome sequencing for single cells for library A98253B 1388 cells; filetype=bam

  Dataset EGAD00001007630

• A98254A

  Whole genome sequencing for single cells for library A98254A 1490 cells; filetype=bam

  Dataset EGAD00001007631

• A98255B

  Whole genome sequencing for single cells for library A98255B 1394 cells; filetype=bam

  Dataset EGAD00001007632

• A98271A

  Whole genome sequencing for single cells for library A98271A 1190 cells; filetype=bam

  Dataset EGAD00001007633

• A98289A

  Whole genome sequencing for single cells for library A98289A 1066 cells; filetype=bam

  Dataset EGAD00001007634

• A98290B

  Whole genome sequencing for single cells for library A98290B 869 cells; filetype=bam

  Dataset EGAD00001007635

• A98305A

  Whole genome sequencing for single cells for library A98305A 986 cells; filetype=bam

  Dataset EGAD00001007637

• A108732A

  Whole genome sequencing for single cells for library A108732A 1139 cells; filetype=bam

  Dataset EGAD00001007592