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• Richter Syndrome RNA-seq dataset

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

  Dataset EGAD00001007922

• 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

• Sex chromosome aneuploidies give rise to changes in the circular RNA profile

  Purpose The landscape of circular RNAs (circRNAs), an important class of non-coding RNAs that regulate gene expression, has never been described in human disorders of sex chromosome aneuploidies. We profiled circRNAs in Turner syndrome females (45,X;TS) and Klinefelter syndrome males (47,XXY; KS) to investigate how circRNAs respond to a missing or an extra X chromosome. Methods Samples of blood, muscle and fat were collected from individuals with TS (n = 33) and KS (n = 22) and from male (n = 16) and female (n = 44) controls. CircRNAs were identified using a combination of circRNA identification pipelines (CIRI2, CIRCexplorer2 and circRNA_finder). Results Differential expression of circRNAs was observed throughout the genome in TS and KS, in all tissues. The host-genes from which several of these circRNAs were derived, were associated with known phenotypic traits. Furthermore, several differentially expressed circRNAs had the potential to capture micro RNAs that targeted protein-coding genes with altered expression in TS and KS. Conclusion Sex chromosome aneuploidies introduce pervasive changes in the circRNA transcriptome, demonstrating that the genomic changes in these syndromes are more complex than hitherto thought. CircRNAs may help explain some of the genomic and phenotypic traits observed in these syndromes.

  Study EGAS00001006404

• Characterization of Neoantigen-reactive T cells by Single-Cell Analysis

  Through CITE-seq and TCR-seq analysis of non-small cell lung cancer (NSCLC) tumor-infiltrating lymphocytes (TIL), we developed a neoantigen-reactive T-cell signature based on clonotype frequency and CD39 protein and CXCL13 mRNA expression. There are four datasets from four NSCLC cases. Each dataset includes (1) Transcriptome of tumor infiltrating lymphocytes (TIL), (2) Cell surface protein expression on TIL by Feature barcoding, (3) T-cell receptor analysis of TIL, and (4) Reference file for feature-barcoding antibodies.

  Study phs002792

• Integrated Exome and RNA Sequencing of Dedifferentiated Liposarcoma

  Multiomics analysis of rare cancers to identify genetic alterations related with pathogenesis and prognosis. To identification of genetics alterations of Dedifferentiated liposarcoma, DNAs and RNAs were extracted from dedifferentiated liposarcoma and paired non-cancer (normal) tissues. NGS libaraies were prepared by using Agilent SureSelect XT Human All Exon V5 + IncRNA kit for whole exome sequencing (WES) and TruSeq Stranded mRNA Prep kit or TruSeq RNA Access Library Prep kit (RNA seq). Sequencing was perfomred by Illumina HiSeq 2500.

  Study JGAS000177

• Analysis of genomic alterations in dedifferentiated liposarcoma

  Multiomics analysis of rare cancers to identify genetic alterations related with pathogenesis and prognosis. To identification of genetics alterations of Dedifferentiated liposarcoma, DNAs and RNAs were extracted from dedifferentiated liposarcoma and paired non-cancer (normal) tissues. NGS libaraies were prepared by using Agilent SureSelect XT Human All Exon V5 + IncRNA kit for whole exome sequencing (WES) and TruSeq Stranded mRNA Prep kit or TruSeq RNA Access Library Prep kit (RNA seq). Sequencing was perfomred by Illumina HiSeq 2500.

  Study JGAS000182

• RNA data for medulloblastoma samples (ICGC)

  RNA sequencing data for 170 medulloblastoma tumor samples

  Dataset EGAD00001003279

• 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