Project description:Initial whole genome sequencing of plasma cell neoplasms in First Responders exposed to the World Trade Center attack of September 11, 2001
Project description:This dataset holds three runs of our new Atrandi-SPC based single-cell WGS protocol, one for each lysis protocol (R1-R3 in the study)
Project description:Chromosomal copy number variations (CNV) have been associated with various neurological and developmental disorders and chromosomal microarray (CMA) is a method of choice to diagnose Copy Number Gain/Loss syndromes. Recently, next-generation sequencing (NGS)-based low-coverage whole genome sequencing (LC-WGS) has been applied to detect Copy Number Gain/Loss syndromes. This dataset is intended to be used as a “Golden standard data set” for development of LC-WGS analysis method. It consists of patients (n=63) who have a mental delay and/or physical disability phenotype and normal (n=20) phenotype.
Project description:We performed shallow whole genome sequencing (WGS) on circulating free (cf)DNA extracted from plasma or cerebrospinal fluid (CSF), and shallow WGS on the tissue DNA extracted from the biopsy in order to evaluate the correlation between the two biomaterials. After library construction and sequencing (Hiseq3000 or Ion Proton), copy number variations were called with WisecondorX.
Project description:Whole genome sequencing (WGS) of tongue cancer samples and cell line was performed to identify the fusion gene translocation breakpoint. WGS raw data was aligned to human reference genome (GRCh38.p12) using BWA-MEM (v0.7.17). The BAM files generated were further analysed using SvABA (v1.1.3) tool to identify translocation breakpoints. The translocation breakpoints were annotated using custom scripts, using the reference GENCODE GTF (v30). The fusion breakpoints identified in the SvABA analysis were additionally confirmed using MANTA tool (v1.6.0).
Project description:The fallopian tube (FT) has been proposed as a potential site of origin for high-grade serous ovarian cancer (HGSOC), supporting investigation of genomic alterations across matched tissues. This dataset includes whole-genome sequencing (WGS) and DigiPico data from matched samples, including peripheral blood mononuclear cells (PBMCs), fallopian tube tissue, and tumor tissue from HGSOC patients. The data support analysis of germline and somatic variants, copy number alterations (CNAs), and neoantigen prediction across matched sample types. This submission contains the WGS data DigiPico data associated with this study.
Project description:Pancreatic cancer (PC) is a highly lethal malignancy, and its early diagnosis remains a clinical challenge. Extracellular vesicles (EVs) derived from patient plasma contain diverse RNA species that may serve as minimally invasive biomarkers. In this study, we performed RNA sequencing (RNA-seq) on EVs isolated from plasma samples of 85 individuals, including 65 patients with pancreatic cancer and 20 patients with benign pancreatic diseases. The benign group consisted of 10 intraductal papillary mucinous neoplasms (IPMN) and 10 chronic pancreatitis (CP) cases. Our aim was to identify differentially expressed RNA signatures in plasma-derived EVs that can distinguish pancreatic cancer from benign conditions. This dataset provides a valuable resource for biomarker discovery in liquid biopsy-based diagnosis of pancreatic cancer.
Project description:Multiple Myeloma is an incurable plasma cell malignancy with a poor survival rate that is usually treated with immunomodulatory drugs (iMiDs) and proteosome inhibitors (PIs). The malignant plasma cells quickly become resistant to these agents causing relapse and uncontrolled growth of resistant clones. From whole genome sequencing (WGS) and RNA sequencing (RNA-seq) studies, different high-risk translocation, copy number, mutational, and transcriptional markers have been identified. One of these markers, PHF19, epigenetically regulates cell cycle and other processes and has already been studied using RNA-seq. In this study a massive (325,025 cells and 49 patients) single cell multiomic dataset was generated with jointly quantified ATAC- and RNA-seq for each cell and matched genomic profiles for each patient. We identified an association between one plasma cell subtype with myeloma progression that we have called relapsed/refractory plasma cells (RRPCs). These cells are associated with 1q alterations, TP53 mutations, and higher expression of PHF19. We also identified downstream regulation of cell cycle inhibitors in these cells, possible regulation of the transcription factor (TF) PBX1 on 1q, and determined that PHF19 may be acting primarily through this subset of cells.
Project description:Low-pass whole genome sequencing (WGS) of one sample of human induced pluripotent stem cells (hiPSCs) derived from the CTL08A male cell line and three samples of CTL08A human embryonic germ cell-like cells (hEGCLCs) at passage 10 after hPGCLC-hEGCLC conversion.
Project description:Lack of a standard method for stratifying advanced-stage NSCLC patients receiving platinum combination therapy often results in a number of patients that do not derive benefit yet are still exposed to treatment toxicity. We hypothesized that miRNAs in pre-treatment serum and/or plasma could be used to differentiate non-small cell lung cancer (NSCLC) patients who would have disease progression to first-line carboplatin and gemcitabine chemotherapy at first response assessment. miRNA profiling of mature and precursor miRNAs was performed on total RNA isolated from the pre-treatment serum and plasma of 24 NSCLC patients. Single validated candidates or combinations thereof were selected based on specificity and sensitivity to segregate patients with disease progression at first radiologic response (PD) vs. those without progressed disease (nonPD). Two precursor miRNA were significantly over-expressed in serum (but not plasma) of PD patients: pre-miR-518b and pre-miR-598. Serum miRNAs may serve as a screening tool in predicting chemoresistance to platinum-based combination chemotherapy.