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• NIHR BioResource Rare Diseases WGS project - Leber Hereditary Optic Neuropathy (LHON) Rare Disease domain

  Short read whole genome sequencing (WGS) CRAM files for the NIHR BioResource Rare Diseases WGS project – Participants from the Leber Hereditary Optic Neuropathy (LHON) Rare Disease domain

  Dataset EGAD00001005122

• 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

• Illumina RNA-Seq paired of 10 different tumor samples from the Master program (H021)

  Fastq files of paired RNA-Seq of 10 different tumor samples, for which Nanopore and Illumina sequencing was compared. Illumina sequencing was carried out with HiSeq4000 or HiSeq X-Ten using the Illumina TruSeq stranded mRNA Kit.

  Dataset EGAD00001008971

• Whole transcriptome sequencing of 78 follicular lyphoma tumours

  This data set includes RNAseq from 77 follicular lymphoma tumours. All tumours were fresh frozen. Libraries were constructed by enriching for poly-A transcripts and sequenced as 75bp paired end reads on an Illumina HiSeq 2500 instrument.

  Dataset EGAD00001010894

• ChIP-seq bulk

  This dataset gather ChIP-seq data produced by immunoprecipitating CTCF factor in own laboratory in MM.1S cell line in EtOH and Dex conditions. It also gather ChIP-seq dataset produced by external laboratory (Active Motif) for H3K27ac mark and GR transcription factor in same cell line and conditions ( MM.1S ETOH/Dex)

  Dataset EGAD00001011136

• The preterm infant microbiome: biological, behavioral and health outcomes at 2 and 4 years of age

  This project follows a cohort of 78 Very Low Birth Weight (VLBW) previously enrolled infants in a R21 grant plus additional 25 infants through their Neonatal Intensive Care Unit (NICU) stay until they reach the age of 4 years. The data, gathered over 6 weeks of the NICU stay, includes multiple factors, such as prenatal and postnatal events and illnesses, received human milk amount, weekly means of cytokines, chemokines, growth factors, and secretory Immunoglobulin A in the milk, and weekly levels of fecal calprotectin. These factors could potentially alter the gut microbiome. Microbiome species and diversities will be measured in the laboratory of Dr. Jack Gilbert at Argonne National Laboratory using state of the science deep sequencing and amplification of microbial sRNA genes. The microbiome will again be measured in stool samples from those children at the ages of 2 and 4 years. Relationship between the prenatal and postnatal factors, human milk volume and immunobiology, fecal calprotectin levels, and the very early microbiome will be analyzed. The predictive power of the VLBW infant gut microbiome for determining later childhood microbiomes will be analyzed prospectively. The relationships between microbiomes across time and later growth, development and health will be determined. VLBW infants are at risk for both early and later health effects, and the role of the microbiome in these effects will be measured in this prospective study.

  Study phs001578

• Liquid biopsy-based minimal residual disease monitoring for early risk stratification and decision-making in advanced non-small cell lung cancer

  Circulating tumor DNA (ctDNA)-based minimal residual disease (MRD) monitoring shows promise for risk stratification and decision-making in cancer patients. However, factors like background noise from non-tumor DNA, clonal haematopoiesis, and non-shedding tumors may complicate manual interpretation and limit its clinical application. In this proof-of-concept study in advanced non-small cell lung cancer (NSCLC) patients treated with immune checkpoint inhibitors (ICIs), we developed an algorithm that automatically classifies serial cell-free DNA (cfDNA) samples, thereby enabling reliable and reproducible interpretation, and preventing time-consuming manual interpretation in approximately 75% of patients. Importantly, application of the algorithm allowed early risk stratification and decision-making, specifically identifying approximately 35% of patients with short-term clinical benefit and approximately 25% of patients who may potentially benefit from treatment escalation. Simultaneous serum tumor marker (STM) monitoring further improved risk stratification and decision-making in our study, enabling accurate identification of all patients with a clinical benefit of at least one year.

  Study EGAS50000001554

• Alpha synucleinopathy spectrum - single nucleus RNA seq of prefrontal cortex

  Single nucleus RNA seq dataset from prefrontal cortex of a total of N=46 individuals with alpha synucleinopathies and healthy controls. Tissue samples correspond to patients with Parkinson's disease (PD, N=20) monogenic PD caused by LRRK2 mutations (LRRK2-PD, N=7), multiple system atrophy (MSA, N=6) and neurologically healthy controls (N=13). RNA seq was carried out employing 10X Genomics Chromium. These samples were also sequenced using conventional bulk tissue RNA seq, and available within the same study as a separate dataset.

  Dataset EGAD50000000431

• Bulk RNA-sequencing datasets from Caco-2 cells under normal or inflamed conditions treated with 4HTBZ or vehicle.

  This dataset contains 4 bulk RNA sequencing files (.fastq.gz) and a metadata file (.csv) from Caco-2/TC7 intestinal epithelial cells under normal or inflamed conditions, followed by treatment with 4HTBZ or vehicle. The cDNA libraries were prepared with the QuantSeq 3′ mRNA-Seq Kit (Lexogen, Inc.) and sequenced on an Illumina HiSeq4000 system. The metadata file provides sample information (experimental condition and code identifier). Raw sequencing reads were quality-checked with FastQC, trimmed with Trimmomatic, and aligned to the human reference genome (GRCh38) using HISAT2.

  Dataset EGAD50000001759

• R compatible Seurat's objetc .rds files with count data and metadata from single cell RNA seq analysis to characterize the prostate cancer tumoral microenviroment of 31 fusion biopses.

  Pre-processed Seurat objects with cellular and functional annotation information from the scRNAseq study on PC fusion biopsy samples. The data consists of rds files composed of normalised counts matrices, normalised and scaled counts, functional enrichment counts at the cellular level and metadata with patient grouping and cellular annotation variables. There are 3 .rds files, one with the total cells (SCP_data_analysis), with the selection of cells annotated as cancerous (selected_cancer_analysis) and cancer-associated fibroblasts (selected_caf_analysis).

  Dataset EGAD50000001298