Ontology highlight
ABSTRACT:
PROVIDER: PRJNA554271 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR9674830.fastq.gz | Fastqsanger.gz | |||
| SRR9674821.fastq.gz | Fastqsanger.gz | |||
| SRR9674831.fastq.gz | Fastqsanger.gz | |||
| SRR9674822.fastq.gz | Fastqsanger.gz | |||
| SRR9674823.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 11 |
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Project description:Diagnosis of infectious diseases by sequencing
| PRJDB7111 | ENA
Project description:<p>In the last decade, non-invasive prenatal diagnosis (NIPD) has emerged as an effective procedure for early detection of inherited diseases during pregnancy. This technique is based on using cell-free DNA (cfDNA) and fetal cfDNA (cffDNA) in maternal blood, and hence, has minimal risk for the mother and fetus compared with invasive techniques. NIPD is used today for identifying chromosomal abnormalities (in some instances) and for single-gene disorders (SGDs) of paternal origin. However, for SGDs of maternal origin, sensitivity poses a challenge that limits the testing to one genetic disorder at a time. Here we present a Bayesian method for the NIPD of monogenic diseases that is independent of the mode of inheritance and parental origin. Furthermore, we show that accounting for differences in the fragment length distribution of fetal- and maternal-derived cfDNA results in increased accuracy. Our model is the first to predict inherited insertions-deletions (indels). The method described can serve as a general framework for the NIPD of SGDs; this will facilitate easy integration of further improvements. One such improvement that is presented in the current study is a machine learning model that corrects errors based on patterns found in previously processed data. Overall, we show that next generation sequencing (NGS) can be used for the NIPD of a wide range of monogenic diseases, simultaneously. We believe that our study will lead to the achievement of a comprehensive NIPD for monogenic diseases.</p> <p>(Reprinted from Bayesian-based noninvasive prenatal diagnosis of single-gene disorders, with permission from Genome Research) </p>
| phs001659 | dbGaP
Project description:We report that blood cell-free DNA as a promising biomarker for the diagnosis of sepsis and for the prediction of 28-day mortality of ICU patients by integrating both human and microbial cfDNA components.
2022-07-01 | GSE179037 | GEO
Project description:Fragment ends of circulating microbial DNA as signatures for infectious diseases
| EGAS00001006321 | EGA
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9189 | biostudies-arrayexpress
Project description:Next-Generation-Sequencing (NGS) technologies have led to important improvement in the detection of new or unrecognized infective agents, related to infectious diseases. In this context, NGS high-throughput technology can be used to achieve a comprehensive and unbiased sequencing of the nucleic acids present in a clinical sample (i.e. tissues). Metagenomic shotgun sequencing has emerged as powerful high-throughput approaches to analyze and survey microbial composition in the field of infectious diseases. By directly sequencing millions of nucleic acid molecules in a sample and matching the sequences to those available in databases, pathogens of an infectious disease can be inferred. Despite the large amount of metagenomic shotgun data produced, there is a lack of a comprehensive and easy-use pipeline for data analysis that avoid annoying and complicated bioinformatics steps. Here we present HOME-BIO, a modular and exhaustive pipeline for analysis of biological entity estimation, specific designed for shotgun sequenced clinical samples. HOME-BIO analysis provides comprehensive taxonomy classification by querying different source database and carry out main steps in metagenomic investigation. HOME-BIO is a powerful tool in the hand of biologist without computational experience, which are focused on metagenomic analysis. Its easy-to-use intrinsic characteristic allows users to simply import raw sequenced reads file and obtain taxonomy profile of their samples.
2021-07-26 | E-MTAB-9191 | biostudies-arrayexpress
Project description:The early detection of tissue and organ damage associated with autoimmune diseases (AID) has been identified as key to improve long-term survival, but non-invasive biomarkers are lacking. Elevated cell-free DNA (cfDNA) levels have been observed in AID and inflammatory bowel disease (IBD), prompting interest to use cfDNA as a potential non-invasive diagnostic and prognostic biomarker. Despite these known disease-related changes in concentration, it remains impossible to identify AID and IBD patients through cfDNA analysis alone. By using unsupervised clustering on large sets of shallow whole-genome sequencing (sWGS) cfDNA data, we uncover AID- and IBD-specific genome-wide patterns in plasma cfDNA in both the obstetric and general AID and IBD populations. Supervised learning of the genome-wide patterns allows AID prediction with 50% sensitivity at 95% specificity. Importantly, the method can identify pregnant women with AID during routine non-invasive prenatal screening. Since AID pregnancies have an increased risk of severe complications, early recognition or detection of new onset AID can redirect pregnancy management and limit potential adverse events. This method opens up new avenues for screening, diagnosis and monitoring of AID and IBD.
2022-09-14 | E-MTAB-11607 | biostudies-arrayexpress
Project description:Cell free DNA (cfDNA) in human plasma carries abundant information on physiological condition, especially in cancer patients such as esophageal cancer. Next-generation sequencing (NGS) as a rapidly developed technology could decode the information effectively. As a key step of NGS, using existing methods to construct cfDNA sequencing libraries is limited by several shortcomings. In this study, we developed a new NGS library construction method for highly degraded DNA, cfDNA as example, based on Single strand Adaptor Library Preparation (SALP). With the high ligation efficiency of single strand adaptor (SSA) which overhangs 3 random bases at 3' end of a double-strand DNA, the new method could construct the sequencing library with high sensitivity without using specific enzymes except T4 DNA ligase and Taq polymerase. With the special designed barcode T adaptor (BTA), multiple libraries constructed from different samples can be amplified in unbiased strategy and facility to compare. Using this method, this study successfully sequenced and compared totally 20 cfDNA samples derived from esophageal cancer patients and healthy people in whole genome scale. This study also compared the chromatin state between cancer patients and healthy people using cfDNA, identified the significant difference between different health condition. Our findings extend the application of cfDNA beyond the analysis with degraded DNA fragments itself, to the transcription regulation level, which also provide an important clue for biopsy of esophageal cancer and other diseases.
2019-04-12 | GSE116345 | GEO
Project description:Nucleosomes are the basic unit of packaging of eukaryotic chromatin, and nucleosome positioning can differ substantially between cell types. Here, we sequence 14.5 billion plasma-borne cell-free DNA (cfDNA) fragments (700-fold coverage) to generate genome-wide maps of in vivo nucleosome occupancy. We identify 13 million local maxima of nucleosome protection, spanning 2.53 gigabases (Gb) of the human genome, whose positions and spacings correlate with nuclear architecture, gene structure and gene expression. We further show that short cfDNA fragments - poorly recovered by standard protocols - directly footprint the in vivo occupancy of DNA-bound transcription factors such as CTCF. The sequence composition of cfDNA has previously been used to noninvasively monitor cancer, pregnancy and organ transplantation, but a key limitation of this paradigm is its dependence on genotypic differences to distinguish between contributing tissues. We show that nucleosome spacing in gene bodies and cis-regulatory elements, inferred from cfDNA in healthy individuals, correlates most strongly with transcriptional and epigenetic features of lymphoid and myeloid cells, consistent with hematopoietic cell death as the normal source of cfDNA. We build on this observation to show how in vivo nucleosome footprints can be used to infer the cell types that contribute to circulating cfDNA in pathological states such as cancer. Because it does not rely on genotypic differences, this strategy may enable the noninvasive cfDNA-based monitoring of a much broader set of clinical conditions than is currently possible. Sequencing of cfDNA libraries from healthy individuals, pooled healthy individuals and individuals with disease for the identification of nucleosomes and protection from other DNA binding proteins.
2015-11-04 | E-GEOD-71378 | biostudies-arrayexpress