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• Targeted MCC-seq

  The capture panel targets the functional methylome in human whole blood. Regions incorporated in the panel design included hypomethylated windows generated from merged WGBS data.

  Dataset EGAD50000000286

• 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

• Single-cell atlas of the human healthy airways

  Single cell atlas of human airways from 10 healthy volunteers by 10X Genomics 3’ RNA-seq profiling. 77,969 cells were collected by bronchoscopy at 35 distinct locations, from the nose to the 12th division of the airway tree, either by forceps (46,791 cells), or brush biopsies (31,178 cells).

  Dataset EGAD00001005714

• 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

• RNA-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  RNA-Seq dataset of Targeting the dark proteome to expand the lineage-retained antigen landscape in neuroblastoma

  Dataset EGAD00001016124

• Guardant ctDNA variant analysis

  This table describes each variant detected using Guardant 360 for each sample included in this analysis.

  Dataset EGAD50000001340

• WGS FASTQ files studied in Allogeneic induced pluripotent stem (iPS) cell-derived cartilage transplantation for articular cartilage damage in knee joints: a phase I, first-in-human study

  This data set contains 5 paired fastq files (WGS).

  Dataset EGAD50000001666

• SIA Subtyping Shallow Whole Genome Sequencing (sWGS)

  Associated with Molecular classification of small intestinal adenocarcinomas. Shallow Whole Genome Sequencing (sWGS) generated 214 .fastq files from 127 small intestine adenocarcinomas from 125 patients. DNA libraries for shallow whole genome sequencing were prepared using TruSeq Nano kits (Illumina).

  Dataset EGAD50000001760

• RNA-seq 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 18 paired fastq files (RNA-seq).

  Dataset EGAD50000000948

• Sample Sheet

  Sample sheet for aligning samples with patients.

  Dataset EGAD50000000484

• RNAseq following LDC67 or JQ1 treatment

  For RNA-Seq total RNA was isolated following LDC67 or JQ1 treatment. 3’RNAseq libraries were prepared with QUANT SEQ FWD 3´mRNA-Seq Kit (Lexogen, Austria), sequenced on an Illumina HiSeq 4000

  Dataset EGAD00001003464

• Meso RNA-seq data (SSA cell line study)

  RNA-seq data for mesothelioma cell lines after spliceostatin (SSA) or control (DMSO) treatment.

  Dataset EGAD00001001914

• Control iPSC lines with clinically annotated genetic variants for versatile multi-lineage differentiation Committee

  Four iPSC line data were sequenced by WGS. One of them has gene MYBPC3 modified.

  Dataset EGAD00001005066

• HV31 - MGI standard short-read sequencing

  MGI standard short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

  Dataset EGAD00001007044

• HV31 - MGI CoolMPS short-read sequencing

  MGI CoolMPS short-read sequencing data for individual HV31 generated using DNA from peripheral blood mononuclear cells, to a sequencing depth of ~57×.

  Dataset EGAD00001007048

• 14 scDNAseq samples

  14 samples were processed for single cell DNA sequencing

  Dataset EGAD00001007521

• Richter Syndrome RNA-seq dataset

  Raw FASTQ files for 77 RS + DLBCL + CLL samples. RNA-sequencing with single-end 50 nt reads.

  Dataset EGAD00001007922

• RaCHseq data

  Captured single-cell long-read data of a cohort of CLL patients receiving VEN treatment for resistance study

  Dataset EGAD00001008365

• FLTseq data

  Single-cell Long read data of a cohort of CLL patients receiving Venetoclax treatment for VEN resistance study.

  Dataset EGAD00001008367

• Fragment ends of circulating microbial DNA as signatures for infectious diseases

  Consists of 88 cases

  Dataset EGAD00001008958

• Clinical data

  Clinical data for IMpower150 (one patient per line): anonymized_patient_id, train_test_split, ctDNA_status, ARM1, OS_months, OS_event, PFS_months, PFS_event, TTEOS_rebaseline_BL, TTEPFS_rebaseline_BL, TTEOS_rebaseline_C2D1, TTEPFS_rebaseline_C2D1, TTEOS_rebaseline_C3D1, TTEPFS_rebaseline_C3D1, TTEOS_rebaseline_C4D1, TTEPFS_rebaseline_C4D1, TTEOS_rebaseline_C8D1, TTEPFS_rebaseline_C8D1, pdl1_high, number_metastatic_sites, baseline_ECOG, age, sex_female, history_of_tobacco_use, sld_baseline, sld_wk6, sld_percent_change_bl_to_wk6, sld_difference_bl_to_wk6, AGEGRP, tumor_assessment_week_6, tumor_assessment_week_12, tumor_assessment_week_18, tumor_assessment_week_24, PFS_days, days_between_randomization_c3

  Dataset EGAD00001009726

• Towards standardized whole exome sequencing (WES) for cancer patients: lessons from a multicentric pilot study

  ZPM WES Pilot consisting of 30 samples paired tumor/normal analyzed with WES at four different laboratories in Germany.

  Dataset EGAD00001011087

• High-grade serous ovarian cancer refined with single-cell RNA-sequencing

  We performed single-cell RNA-sequencing of 18,403 cells unbiasedly collected from 7 treatment-naive HGSOC tumours. For each phenotypic cluster of tumour or stromal cells, we identified specific transcriptomic markers. Next, we explored which phenotypic clusters correlate with overall survival based on expression of these transcriptomic markers in 1467 bulk RNA-seq tumours. By evaluating molecular subtype signatures in single cells, we assessed to what extent a phenotypic cluster of tumour or stromal cells contributes to each molecular subtype.

  Study EGAS00001004987

• Whole genome analysis of mutation hotspots in gastric cancer

  Tissue-specific driver mutations in non-coding genomic regions remain undefined for most cancer types. In this study, we unbiasedly analysed 212 gastric cancer whole genomes to identify recurrently mutated non-coding regions in gastric cancer. Applying comprehensive statistical approa- ches to accurately model background mutational processes, we observe significant enrich- ment of non-coding indels (insertions/deletions) in three gastric lineage-specific genes. We further identify 34 mutation hotspots, of which 11 overlap CTCF binding sites (CBSs).

  Study EGAS00001002872

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279