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• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95622A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 509 samples; filetype=bam

  Dataset EGAD00001004746

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95624A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 604 samples; filetype=bam

  Dataset EGAD00001004747

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632B

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 626 samples; filetype=bam

  Dataset EGAD00001004748

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95632D

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 635 samples; filetype=bam

  Dataset EGAD00001004749

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95660A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 1522 samples; filetype=bam

  Dataset EGAD00001004750

• Whole genome sequencing of single cells identifies stochastic aneuploidies, genome replication, states, and clonal repertoires for library A95664A

  Transposase-based amplification-free single-cell genome direct library preparation in nanowell chips; 465 samples; filetype=bam

  Dataset EGAD00001004751

• 20210708_EGA_Melanoma_mk2 WGS 570 donors

  Illumina platform whole genome sequencing data for matched tumour-normal DNA samples from 570 melanoma patients

  Dataset EGAD00001008798

• The Genetics of Lung Cancer Susceptibility in Smokers

  Over 85% of all patients diagnosed with lung cancer report a history of tobacco use, though only 10% of tobacco smokers eventually develop lung cancer. Epidemiologic studies have shown that family members of patients with lung cancer have a higher risk of developing lung cancer than controls. In an effort to identify variants associated with tobacco induced lung cancer, we have sequenced germline DNA from affected and unaffected members of families with strong histories of tobacco related lung cancer.

  Study phs000728

• egpg-G-1

  Illumina Omni 2.5M SNPchip data (build37) of Ethiopian samples from the Pagani et al. 2015 AJHG paper (doi: http://dx.doi.org/10.1016/j. ajhg.2015.04.019)

  Dataset EGAD00010001221

• EGAD00010000632

  WTCCC2 People of the British Isles (POBI) samples using Illumina 1.2M array

  Dataset EGAD00010000632

• EGAD00010000634

  WTCCC2 People of the British Isles (POBI) samples using Affymetrix 6.0 array

  Dataset EGAD00010000634

• EGAD00010000730

  WTCCC2 Psychosis Endophenotype samples from UK, Germany, Holland, Spain and Australia using the Affymetrix 6.0 array

  Dataset EGAD00010000730

• EGAD00010000740

  Osteoarthritis cases genotyped on Illumina HumanOmniExpress from the arcOGEN Consortium (http://www.arcogen.org.uk/) with broader consent.

  Dataset EGAD00010000740

• EGAD00010000742

  Subset 1 of osteoarthritis cases genotyped on Illumina610k from the arcOGEN Consortium (http://www.arcogen.org.uk/) with broader consent.

  Dataset EGAD00010000742

• Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient

  Genome and transcriptome sequence data from a metastatic cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002976

• Genome and transcriptome sequence data from a breast cancer patient

  Genome and transcriptome sequence data from a breast cancer patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002972

• Genome and transcriptome sequence data from a rectal adenocarcinoma patient

  Genome and transcriptome sequence data from a rectal adenocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002973

• Genome and transcriptome sequence data from a cholangiocarcinoma patient

  Genome and transcriptome sequence data from a cholangiocarcinoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002991

• Genome and transcriptome sequence data from a leiomyosarcoma patient

  Genome and transcriptome sequence data from a leiomyosarcoma patient, generated as part of the BC Cancer Agency's Personalized OncoGenomics (POG) study

  Dataset EGAD00001002996

• RNA-sequencing of primary urothelial bladder cancer samples

  Paired-end RNA-sequencing of tumour tissue samples (n=85) from primary urothelial bladder cancer patients. Sequencing was performed using either HiSeq (n=27) or NextSeq (n=58) Illumina platforms. Of the 85 samples, 78 are Non-muscle invasive (NMIBC) and 7 are Muscle invasive (MIBC).

  Dataset EGAD00001007005

• RNA sequencing of 499 Greenlanders

  The data contain whole transcriptome sequencing of 499 Greenlanders.

  Dataset EGAD00001007717

• Solve-RD_RND_cohort-1_DF1+2_V1

  Solve-RD data submitted to the ERN-RND cohort for re-analysis (Data freeze 1+2) v1

  Dataset EGAD00001009769

• Dataset for Sarcoma RNA sequencing linked from study EGAS00001004813

  Sequencing data of 410 sarcoma tumor runs, which were uploaded to EGAS00001004813. The sequencing was always paired.

  Dataset EGAD00001010276

• Single cell transcriptomic landscape of pediatric B-cell acute lymphoblastic leukemia: dissection of transcriptional heterogeneity and B-cell developmental state

  Introduction: Genomic analyses of bulk ALL samples have improved our understanding of the genetic basis and risk stratification of B-ALL, but do not directly examine intratumor heterogeneity or enable inference of leukemia developmental state and cell of origin. Methods: We profiled 89 B-ALL samples by single-cell RNA-seq (scRNA-seq) (10X Genomics 5’v2) and compared them to a scRNA-seq reference map of normal human B-cell development. Results: Analysis of heterogeneity of inferred DNA copy number alterations at single cell level showed that aneuploid ALL with near haploidy and hyperdiploid harbor chromosomal losses or gains in all blasts, consistent with early, synchronous origin rather than sequential accumulation. Intra-sample heterogeneity was driven by five gene expression signatures: cell cycle, metabolism, differentiation, inflammation, refining leukemic subtyping. An atlas of B cell development was established to map B-ALL samples to specific developmental states. Hyperdiploid samples resembled pro-B cells, while MEF2D-r and TCF3::PBX1 showed high pre-B abundance. Patients with high early lymphoid abundance had poorer outcomes. Conclusions: Understanding variation in transcriptional programs and developmental states of B-ALL blasts by sc transcriptome refines existing clinical and genomic classifications and provides novel prognostic markers.

  Study EGAS00001007512

• DKFZ-HIPO Data Access Committee of Heidelberg Center for Personalized Oncology

  Dac EGAC00001000452