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• Complex-I stratification of Parkinson's disease in the prefrontal cortex - bulk RNA seq

  Dataset corresponding to the bulk RNA seq dataset from prefrontal cortex for a total of N=98 samples. Tissue samples correspond to patients with idiopathic Parkison's disease (PD) with varying levels of Complex-I activity (N=79) and neurologically healthy controls (N=19). RNA seq was carried out using ribosomal depletion. A subset of these samples was additionally sequenced using single nucleus RNA seq and is available in the same Study as an additional Dataset.

  Dataset EGAD50000000433

• Sequence Data from the phase 2 PrE0505 trial of Durvalumab with First Line Platinum-Pemetrexed for Unresectable Pleural Mesothelioma

  Dataset comprises of 84 bam files from exome sequencing data, including 40 tumor-normal pairs and 4 normal files. Each sample is numbered by the patient case ID such as 135, 156 and so on. The filenames are suffixed with "_tumor" and "_normal" to indicate tumor and normal bam files respectively.

  Dataset EGAD00001008016

• Tumor Profiler Project - OV cell-free DNA data

  The dataset contains amplicon sequencing data from 48 samples from 35 different patients with ovarian cancers. Cell free DNA was collected from plasma. Sequencing was performed on an Ion Torrent platform and the sequencing data is provided in bam format.

  Dataset EGAD50000001410

• Basal-to-Inflammatory Transition Contributes to Basal Cell Carcinoma Therapy Resistance via Crosstalk with a Pro-Inflammatory Stromal Niche

  Overcoming tumor evolution and inducible resistance states remain the main challenge to creating successful anti-tumor therapies. The body's cancer-associated inflammatory response is a double-edged sword having ill-defined pro- and anti-tumor properties. Our group previously identified a basal cell carcinoma (BCC) tumor-intrinsic resistance pathway called basal to squamous cell carcinoma transition (BST). However, tumor resistance driven through the complex dynamics of tumor interactions with the inflammatory response remains poorly studied. Here, employing a multipronged approach combining human tumor single-cell transcriptomics, single-cell chromatin accessibility (scATAC-Seq) study, CODEX multiplexed imaging, spatial transcriptomic along with functional validation, we have identified a surprising inflammation-associated SMOi therapy enriched tumor epithelial cell state we term basal-to-inflammatory transition (BIT). Marked by CHI3L1, TAGLN, ITGAV, and VCAM1, BIT arises in spatially distinct neighborhoods from BST in a subset of naive BCCs. While BST tumor epithelium occurs within the central cores of tumor nodules, BIT tumor epithelium arises in a specialized inflammatory environment defined by a tumor associated TREM1 myeloid signature. IL1 and OSM secreted by TREM1 myeloid cells activate the inflammatory NF-kB family of transcription factors within the BIT tumor epithelium. Strikingly, IL1 and OSM ligands are sufficient not only in inducing the BIT tumor state in vitro and in vivo in a synergistic fashion but also in lowering the sensitivity of human BCC explant tumors to SMOi treatment. This work provides critical insights into the BIT-resistant state as a novel targetable tumor state driven by a specialized inflammatory microenvironment.

  Study phs003437

• Multi-Ethnic Study of Atherosclerosis (Electrocardiogram Tracing Repository)

  The Multi-Ethnic Study of Atherosclerosis (MESA) is a study of the characteristics of subclinical cardiovascular disease (disease detected non-invasively before it has produced clinical signs and symptoms) and the risk factors that predict progression to clinically overt cardiovascular disease or progression of the subclinical disease. MESA researchers study a diverse, population-based sample of 6,814 asymptomatic men and women aged 45-84. Thirty-eight percent of the recruited participants are white, 28 percent African-American, 22 percent Hispanic, and 12 percent Asian, predominantly of Chinese descent. Electrocardiogram Tracing Repository includes ECG tracings performed during MESA Exam 1 conducted between 2000 and 2002 and during MESA Exam 5 conducted between 2010 and 2012.

  Study phs003703

• The life-saving benefit of dexamethasone in severe COVID-19 is linked to a reversal of monocyte dysregulation

  Assessment of dexamethasone response in human lung through scRNA-seq analysis of bronchoalveolar lavage (BAL) samples from patients with severe COVID-19.

  Study EGAS50000000203

• miRNA-sequencing of PBMCs from COVID-19 patients experiencing different degrees of the disease (mild and critical), and control patients

  micro RNA-sequencing of peripheral blood mononuclear cells collected from mild COVID-19 (n = 6), critical COVID-19 (n = 13) and control (n = 8) patients. Sequencing data is provided as FASTQ files.

  Dataset EGAD50000001406

• Genomic characterization of CNA-quiet oral cancer

  Low-coverage whole genome sequencing and targeted (30 gene panel) deep sequencing of oral cancer. Note that the targeted deep sequencing is not actually amplicon sequencing but hybrid capture sequencing, which was not available as on option.

  Dataset EGAD50000000790

• Genomic-Enabled Medicine for Recurrent Glioblastoma

  In this prospective study, we performed genome-wide tumor/normal exome sequencing and tumor RNA-sequencing for recurrent glioblastoma patients. A subset of patients had both enhancing tumor and non-enhancing tissue sequenced to investigate spatial heterogeneity of this disease. Together, this information builds our understanding of the genomic underpinnings of glioblastoma, and contributes toward the knowledge base for identifying and developing more effective treatments for patients with glioblastoma.

  Study phs001460

• Direct Comparative Analysis of 10X Genomics Chromium and Smart-seq2

  Single cell RNA sequencing (scRNA-seq) is widely used for profiling transcriptomes of individual cells. The droplet-based 10X Genomics Chromium (10X) approach and the plate-based Smart-seq2 full-length method are two frequently-used scRNA-seq platforms, yet there are only a few thorough and systematic comparisons of their advantages and limitations. Here, by directly comparing the scRNA-seq data by the two platforms from the same samples of CD45- cells, we systematically evaluated their features using a wide spectrum of analysis. Smart-seq2 detected more genes in a cell, especially low abundance transcripts as well as alternatively spliced transcripts, but captured higher proportion of mitochondrial genes. The composite of Smart-seq2 data also resembled bulk RNA-seq data better. For 10X-based data, we observed higher noise for mRNA in the low expression level. Despite the poly(A) enrichment, approximately 10-30% of all detected transcripts by both platforms were from non-coding genes, with lncRNA accounting for a higher proportion in 10X. 10X-based data displayed more severe dropout problem, especially for genes with lower expression levels. However, 10X-data can better detect rare cell types given its ability to cover a large number of cells. In addition, each platform detected different sets of differentially expressed genes between cell clusters, indicating the complementary nature of these technologies. Our comprehensive benchmark analysis offers the basis for selecting the optimal scRNA-seq strategy based on the objectives of each study.

  Dataset EGAD00001005448