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• OSCC WES + WGS Boot et al. 2020

  Study EGAS00001004376

• Gut metagenome/FINRISK 2002 (Salosensaari et al. Nature Comms 2021)

  The main goal of the project is the study the associations between the gut metagenome and human health. The dataset contains data for n=7211 FINRISK 2002 participants who underwent fecal sampling. Demultiplexed shallow shotgun metagenomic sequences were quality filtered and adapter trimmed using Atropos (Didion et al., 2017), and human filtered using Bowtie2 (Langmead and Salzberg, 2012).

  Study EGAS00001005020

• Center for Common Disease Genomics [CCDG] - Cardiovascular: The Bangladesh Risk of Acute Vascular Events (BRAVE) Study

  The Bangladesh Risk of Acute Vascular Events (BRAVE) study is a hospital-based case-control study in Bangladesh which was established by the Cardiovascular Epidemiology Unit of Cambridge University in the UK in partnership with the key local cardiology and research centres to examine environmental, genetic, lifestyle and biochemical determinants of myocardial infarction (MI) among this South Asian population. By the end of 2016, this study has recruited ~8000 clinically confirmed first-ever MI cases (with a significant proportion being early-onset MI), and ~8000 healthy controls frequency-matched by age and sex. This site hosts data from ~500 whole genomes and ~1500 whole exomes (50% cases and 50% controls)

  Study phs001398

• Single Cell Analysis of Psoriasis Resolution following IL-23 Blockade

  Full-thickness skin biopsies were obtained from five individuals with severe psoriasis who were receiving risankizumab treatment. Skin biopsies were taken from lesional and non-lesional sites at baseline, and from lesional sites at day 3 and day 14 of therapy. All biopsies were taken from site-matched areas on the lower back/buttocks. Single-cell RNA sequencing was performed using a 10x Genomics platform. Myeloid and fibroblast populations showed the strongest change in gene expression after 3 days. An inflammatory, transient WNT5A+/IL24+ fibroblast state was identified, which was elevated in abundance in lesional skin versus non lesional skin, and decreased after 14 days of treatment. R1 and R2 FASTQs files are available.

  Study phs003351

• Whole genome sequencing data of pediatric B-other subtype acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases is acquired from ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) based on the RNA-seq profiles.

  Study EGAS50000001497

• RNA sequencing data of pediatric B-other acute lymphoblastic leukemia

  For a long time, approximately 70% of childhood B-ALL cases could be classified routinely, and the remaining 30% were classified into the “B-other” group lacking the known genetic features. However, more recently, new genomic tools have uncovered new subtypes among the B-other groups. Approximately 10% of B-ALL cases lack the recurrent genetic abnormalities, and are referred as "B-other". They are typically more heterogeneous than other subtypes of B-ALL, and their prognoses are more variable. In a more recent update of the B-ALL classification, 27 subtypes were identified (Arber et al., 2022). The identification of some of these subtypes is dependent on NGS methods, such as RNA sequencing, which are not routinely used in all clinical laboratories. For example, ETV6::RUNX1-like and DUX4-rearranged subtypes have been identified using RNA sequencing. For this study, subtype predictions for some of the cases were acquired by using the ALLIUM (Krali et al., NPJ Precis Oncol., 2023) and ALLCatchR (Beder et al., Blood, 2022) tools for the RNA sequencing data.

  Study EGAS50000001803

• Dopaminergic neuron differentiation of human embryonic stem cells

  2 replicates of dopaminergic neuron differentiation of human embryonic stem cells from timepoints day 17 and day 28, performed with 10X Genomics single cell RNA-seq. Part of the Ásgrimsdottir et al. (Arenas Lab).

  Study EGAS50000001099

• RNA seq of MPNST tumour samples

  RNA sequencing of 10 MPNST tumour samples as part of a larger study of MPNST. Article: Lyskjær et al, 2020, J Pathol, "H3K27me3 expression and methylation status in histological variants of malignant peripheral nerve sheath tumours".

  Study EGAS00001004528

• Healthy Never Smokers

  Bronchial brushing dataset from healthy never-smokers after exposure to diesel exhaust. Include 18 samples from 9 research participants who underwent bronchoscopy after controlled exposure to diesel exhaust. Main study design described in detail in Ryu et al 2022 AJRCCM (PMID: 35202552). This dataset was used in Hill et al Nature 2023.

  Dataset EGAD00001010024

• RNA-seq data of breast cancer HCI011 model from Ros et al (2020)

  RNA-seq data of the HCI011 and HCI011R models, GDC032 treated and control (total of 21 samples), from the paper: FOXM1 is a biomarker of resistance to PI3Kα inhibition in ER+ breast cancer that is detectable using metabolic imaging (Ros et al, 2020)

  Dataset EGAD00001006245