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• Psoriatic arthritis WGS (2019-08-07)

  Whole genome sequencing of immune cells from patients diagnosed with psoriatic arthritis . This dataset contains all the data available for this study on 2019-08-07.

  Dataset EGAD00001005232

• ESGI - Whole Genome Sequencing of samples from the ORCADES cohort (X10) (2019-08-19)

  Deep whole genome sequencing of sampels from the Orkney Complex Disease Study (ORCADES), each with data on up to 300 quantitative traits and other risk factors associated with cardiovascular, metabolic and other complex diseases. The samples are sequenced using the Illumina HiSeq X Ten system. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005269

• Anaplastic Thyroid Cancer aligned whole exome sequence data

  Whole exome sequence data in fastq format was aligned to the GRCH38 reference genome. Aligned sequence was preprocessed with GATK for Indel Realignment and Base Quality Score Recalibration. Duplicates were marked with Picard Mark Duplicates. Aligned sequence is in bam format. Details of the alignment can be found in he bam header. Tumour samples were classified as Anaplastic Thyroid, Poorly-differentiated or well-differentiated cancers.

  Dataset EGAD00001005791

• Whole-exome sequences of ovarian clear cell carcinomas and paired normal DNA

  Whole-exome sequencing dataset for the Australian Ovarian Cancer Study (AOCS) and The Jikei University School of Medicine (JIKEI) ovarian clear cell carcinoma (OCCC) clinical outliers project, representing 10 donors. Consists of 20 fastq files: one normal and one tumour from each patient.

  Dataset EGAD00001006004

• A Single-Cell Atlas of the Multicellular Ecosystem of Primary and Metastatic Hepatocellular Carcinoma

  Single-cell transcriptomes for 10 hepatocellular carcinoma (HCC) patients from 21 sample of four relevant sites: primary tumor (T), portal vein tumor thrombus (P), metastatic lymph node (L) and non-tumor liver (N). Single cells were sequenced using Chromium Single Cell 3’ Library (10x Genomics).

  Dataset EGAD00001006190

• Single Cell RNA sequencing of Organoids from TSC2+/- patient IPSCs in H- and L-medium

  This dataset contains single cell RNA sequencing data from Organoids grown in high nutrient (H) and low nutrient (L) medium. Organoids were grown for 110 days. Organoids were grown from a patient IPS cell line with a heterozygous mutation in TSC2 (Patient 1 TSC2+/- iPSCs) and an isogenic control cell line (TSC2+/+).

  Dataset EGAD00001006332

• scTCR-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell T cell receptor clonotypes were produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006451

• scRNA-seq from brain metastasis micorenvironment and cerebrospinal fluid

  A total of 9 brain metastasis were sequenced. For 6/9 a matched cerebrospinal fluid sample, prior to surgery and in two cases after surgery (+1 month from surgery) and after treatment (+3 month) were collected. Single-cell gene expression was produced using the Chromium Single Cell 5’ Library and sequenced on an Illumina NovaSeq 6000.

  Dataset EGAD00001006452

• Finding structural variation and functional consequences from the primary leukemia cells (AML) at the single-cell level

  In this study, we aimed to identify somatic structural variation of acute myeloid leukemia (AML) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 32-year-old male donor.

  Dataset EGAD00001006782

• Finding structural variation and functional consequences from the primary leukemia cells (CLL) at the single-cell level

  In this study, we aimed to identify somatic structural variation of chronic lymphocytic leukemia (CLL) at the single-cell level and investigate its direct consequence on the nucleosome occupancy using scNOVA approach. For this purpose, we performed strand-specific single-cell sequencing of primary leukemia samples from 63-year-old female patient.

  Dataset EGAD00001006822