Ontology highlight
ABSTRACT:
PROVIDER: PRJNA590866 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We evaluated whether targeted next-generation sequencing (NGS) using the Ion Torrent Personal Genome Sequencer of cfDNA could identify prognostic or predictive factors for overall survival (OS) or progression free survival (PFS) within a large cohort of patients with advanced lung adenocarcinoma enrolled in the GALAXY-1 trial.
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Project description:Mitogenomes generated using Galaxy
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Project description:Single-cell sequencing methodologies such as scRNA-seq and scATAC-seq have become widespread and effective tools to interrogate tissue composition. Increasingly, variant callers are being applied to these methodologies to resolve the genetic heterogeneity of a sample, especially in the case of detecting the clonal architecture of a tumor. Typically, traditional bulk DNA variant callers are applied to the pooled reads of a single-cell library to detect candidate mutations. Recently, multiple studies have applied such callers on reads from individual cells, with some citing the ability to detect rare variants with higher sensitivity. Many studies apply these two approaches to the Chromium (10x Genomics) scRNA-seq and scATAC-seq methodologies. However, Chromium-based libraries may offer additional challenges to variant calling compared to existing single-cell methodologies, raising questions for the validity of variants obtained from such a workflow. To determine the merits and challenges of various variant-calling approaches on Chromium scRNA-seq and scATAC-seq libraries, we use sample libraries with matched bulk whole-genome-sequencing to evaluate the performance of callers. We review caller performance, finding that bulk callers applied on pooled reads significantly outperform individual-cell approaches. We also evaluate variants unique to scRNA-seq and scATAC-seq methodologies, finding patterns of noise but also potential capture of RNA-editing events. Finally, we review the notion that variant calling at the single-cell level can detect rare somatic variants, providing empirical results that suggest resolving such variants is infeasible in single-cell Chromium libraries.
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Project description:Small RNA sequencing of 36 porcine embryo samples collected on Day 10 of pregnancy detected miRNA sequences mapping to known and predicted porcine miRNAs, and novel miRNAs highly conserved in human and cattle. A set of highly abundant miRNAs was identified as well as a large number of rarely expressed miRNAs. Due to the high number of generated sequence reads, it was possible to detect a large number of different miRNA isoforms (isomiRs). Potentially embryo-specific miRNAs were identified by comparing the data with small RNA-Seq data sets from porcine endometrium and a search in databases for miRNA tissue expression. The identification of 140 novel miRNAs in addition to 173 known porcine miRNAs (miRBase21) showed the benefit of our small RNA analysis pipeline. This benefit has a big impact for poorly annotated species such as the pig where it is possible to annotate many additional miRNAs based on the knowledge from related species. Furthermore, we integrated our pipeline into a Galaxy workflow using standard Galaxy tools which guaranties high reproducibility and flexibility for new/upcoming datasets/studies. Using ortholog species information increases the total number of annotated miRNAs while mapping to other non-coding RNAs decreased the chances of falsely annotated miRNAs. Galaxy workflows can be published, shared, downloaded, and optimized to adapt to other species or modify analysis parameters, such as tools specifically developed for a given research project/problem, so that a broad audience can use it.
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Project description:Most proteogenomic approaches for mapping single amino acid polymorphisms (SAPs) require construction of a sample-specific database containing protein variants predicted from the next-generation sequencing (NGS) data. We present a new strategy for direct SAP detection without relying on NGS data. Among the 348 putative SAP peptides identified in an industrial yeast strain, 85.6% of SAP sites were validated by genomic sequencing.
2018-04-18 | PXD003101 | Pride
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