Ontology highlight
ABSTRACT:
PROVIDER: PRJNA579768 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Here we describe a custom FMDV microarray and a companion feature and template-assisted assembler software (FAT-assembler) capable of resolving virus genome sequence using a moderate number of conserved microarray features. The results demonstrate that this approach may be used to rapidly characterize naturally occurring FMDV as well as an engineered chimeric strain of FMDV. The FAT-assembler, while applied to resolving FMDV genomes, represents a new bioinformatics approach that should be broadly applicable to interpreting microarray genotyping data for other viruses or target organisms
2016-11-10 | GSE89283 | GEO
Project description:Estimating the relationships between individuals is one of the fundamental challenges in many fields. In particular, relationship estimation could provide valuable information for missing persons cases. The recently developed investigative genetic genealogy approach uses high-density single nucleotide polymorphisms (SNPs) to determine close and more distant relationships, in which hundreds of thousands to tens of millions of SNPs are generated either by microarray genotyping or whole-genome sequencing. The current studies usually assume the SNP profiles were generated with minimum errors. However, in the missing person cases, the DNA samples can be highly degraded, and the SNP profiles generated from these samples usually contain lots of errors. In this study, a robust machine learning approach was developed for estimating the relationships with high error SNP profiles. In this approach, a hierarchical classification strategy was employed first to classify the relationships by degree and then the relationship types within each degree separately. As for each classification, feature selection was implemented to gain better performance. Both simulated and real data sets with various genotyping error rates were utilized in evaluating this approach, and the accuracies of this approach were higher than individual measures; namely, this approach was more accurate and robust than the individual measures for SNP profiles with genotyping errors. In addition, the highest accuracy could be obtained by providing the same genotyping error rates in train and test sets, and thus estimating genotyping errors of the SNP profiles is critical to obtaining high accuracy of relationship estimation.
2022-07-27 | GSE209804 | GEO
Project description:Induced pluripotent stem cell (iPSC) derived organoid systems provide models to study human organ development. Single-cell transcriptome sequencing enables highly-resolved descriptions of cell state heterogeneity within these systems and computational methods can reconstruct developmental trajectories. However, new approaches are needed to directly measure lineage relationships in these systems. Here we establish an inducible dual channel lineage recorder, iTracer, that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze state and lineage relationships in iPSC-derived systems. This data set include the iTracer-perturb data of one cerebral organoid with simultaneous TSC2 perturbation and lineage recording.
2021-11-03 | E-MTAB-10971 | biostudies-arrayexpress
Project description:Induced pluripotent stem cell (iPSC) derived organoid systems provide models to study human organ development. Single-cell transcriptome sequencing enables highly-resolved descriptions of cell state heterogeneity within these systems and computational methods can reconstruct developmental trajectories. However, new approaches are needed to directly measure lineage relationships in these systems. Here we establish an inducible dual channel lineage recorder, iTracer, that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze state and lineage relationships in iPSC-derived systems. This data set include the iTracer data of 12 cerebral organoids.
2021-11-03 | E-MTAB-10974 | biostudies-arrayexpress
Project description:Viral siRNA generated from antiviral RNA silencing machinery was profiled using small RNA sequencing from Phalaenopsis orchid mixed infected with CymMV and ORSV
2020-01-01 | GSE94083 | GEO
Project description:Induced pluripotent stem cell (iPSC) derived organoid systems provide models to study human organ development. Single-cell transcriptome sequencing enables highly-resolved descriptions of cell state heterogeneity within these systems and computational methods can reconstruct developmental trajectories. However, new approaches are needed to directly measure lineage relationships in these systems. Here we establish an inducible dual channel lineage recorder, iTracer, that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze state and lineage relationships in iPSC-derived systems. This data set include the spatial iTracer data of three slices of one cerebral organoid measured by 10x Visium.
2021-11-03 | E-MTAB-10972 | biostudies-arrayexpress
Project description:Induced pluripotent stem cell (iPSC) derived organoid systems provide models to study human organ development. Single-cell transcriptome sequencing enables highly-resolved descriptions of cell state heterogeneity within these systems and computational methods can reconstruct developmental trajectories. However, new approaches are needed to directly measure lineage relationships in these systems. Here we establish an inducible dual channel lineage recorder, iTracer, that couples reporter barcodes, inducible CRISPR/Cas9 scarring, and single-cell transcriptomics to analyze state and lineage relationships in iPSC-derived systems. This data set include the iTracer data of two microdissected regions of one cerebral organoid.
2021-11-03 | E-MTAB-10973 | biostudies-arrayexpress
Project description:Resolving Deep Nodes in an Ancient Radiation of Neotropical Fishes in the Presence of Incomplete Lineage Sorting
| PRJNA470726 | ENA
Project description:We performed spatial transcriptome sequencing of orchid to provide spatial cell atlas of floral organogenesis.
2022-08-18 | GSE198128 | GEO