GenesorteR: Feature Ranking in Clustered Single Cell Data
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA564101 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Marker genes identified in single cell experiments are expected to be highly specific to a certain cell type and highly expressed in that cell type. Detecting a gene by differential expression analysis does not necessarily satisfy those two conditions and is typically computationally expensive for large cell numbers. Here we present genesorteR, an R package that ranks features in single cell data in a manner consistent with the expected definition of marker genes in experimental biology research. We benchmark genesorteR using various data sets and show that it is distinctly more accurate in large single cell data sets compared to other methods. genesorteR is orders of magnitude faster than current implementations of differential expression analysis methods, can operate on data containing millions of cells and is applicable to both single cell RNA-Seq and single cell ATAC-Seq data. genesorteR is available at https://github.com/mahmoudibrahim/genesorteR.
2020-09-30 | GSE136950 | GEO
Project description:Detection of single feature polymorphisms comparing five barley genotypes. Gene expression under unstressed and drought stressed conditions. Tissue from five entire five day old seedlings from drought stress or unstressed growth conditions was used for RNA extraction. For Barke, Morex and Stepoe the two types of RNA were pooled. For Oregon Wolfe Barley Dominant and Recessive (OWBs), the two types of RNA were handled separately. Targets from three biological replicates of each genotype-treatment were generated and transcript levels were determined using Affymetrix Barley1 GeneChip arrays. Probe set, followed by single probe, comparisons between genotypes allows the identification of single feature polymorphisms in comparisons between genotypes. For the OWBs, comparisons between stressed and unstressed conditions defines stress-regulated genes. Keywords: repeat
2005-08-25 | GSE3170 | GEO
Project description:Detection of single feature polymorphisms comparing five barley genotypes. Gene expression under unstressed and drought stressed conditions. Tissue from five entire five day old seedlings from drought stress or unstressed growth conditions was used for RNA extraction. For Barke, Morex and Stepoe the two types of RNA were pooled. For Oregon Wolfe Barley Dominant and Recessive (OWBs), the two types of RNA were handled separately. Targets from three biological replicates of each genotype-treatment were generated and transcript levels were determined using Affymetrix Barley1 GeneChip arrays. Probe set, followed by single probe, comparisons between genotypes allows the identification of single feature polymorphisms in comparisons between genotypes. For the OWBs, comparisons between stressed and unstressed conditions defines stress-regulated genes. Experiment Overall Design: Three genotypes, three replicates each. Two additional genotypes, two sets of three replicates each.
2008-06-12 | E-GEOD-3170 | biostudies-arrayexpress
Project description:Quantitative single-cell transcriptome-based ranking of engineered AAVs in human retinal explants
| PRJNA821677 | ENA
Project description:Natural populations of the fruit fly, Drosophila melanogaster, segregate genetic variation that leads to cardiac disease phenotypes. Drosophila is well-known as a model for studying the mechanisms by which human disease genes cause pathology, including heart disease, but it is less well appreciated that they may also model the genetic architecture of disease, since flies presumably also have diseases that have a genetic basis. It is reasoned that most of these aberrant inbred line effects would be due to capture of rare variants of large effect as homozygotes, allowing the variants to be mapped rapidly using contemporary genomic approaches. In order to map the genetic variants in flies, we used single feature polymorphism (SFP) analysis to contrast the genome-wide genotype frequencies between pools of flies with aberrant and normal heart phenotype. SFP analysis is an indirect method for genome-wide genotyping that utilizes differential hybridization of genomic DNA to probes on a DNA chip that was initially designed for gene expression profiling, but can be used for species where genotyping chips are not available. DNA was prepared from three independent pools of 15 flies for each of the two types, as well as from the two parental lines. The samples were sheared and labeled with biotin, then hybridized to Affymetrix Drosophila expression microarray chips. Mismatch hybridization, namely a significant difference in the hybridization intensity between the parental lines, was detected from all perfect match (PM) probes, located in over 9,000 probes with an estimated False Discovery Rate of 11%.
2013-03-15 | E-GEOD-45123 | biostudies-arrayexpress
Project description:Unified Feature Association Networks through Integration of Transcriptomic and Proteomic Data
| PRJNA557355 | ENA
Project description:Natural populations of the fruit fly, Drosophila melanogaster, segregate genetic variation that leads to cardiac disease phenotypes. Drosophila is well-known as a model for studying the mechanisms by which human disease genes cause pathology, including heart disease, but it is less well appreciated that they may also model the genetic architecture of disease, since flies presumably also have diseases that have a genetic basis. It is reasoned that most of these aberrant inbred line effects would be due to capture of rare variants of large effect as homozygotes, allowing the variants to be mapped rapidly using contemporary genomic approaches. In order to map the genetic variants in flies, we used single feature polymorphism (SFP) analysis to contrast the genome-wide genotype frequencies between pools of flies with aberrant and normal heart phenotype. SFP analysis is an indirect method for genome-wide genotyping that utilizes differential hybridization of genomic DNA to probes on a DNA chip that was initially designed for gene expression profiling, but can be used for species where genotyping chips are not available.
2013-03-15 | GSE45123 | GEO
Project description:scAAVengr, a transcriptome-based pipeline for quantitative ranking of engineered AAVs with single-cell resolution
| PRJNA679024 | ENA
Project description: Not available
| S-EPMC5608217 | biostudies-literature
Project description: Not available
| S-EPMC7860202 | biostudies-literature