Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next generation sequencing for quantitative analysis of wild type and Y41F transcriptomes

ABSTRACT: Next Generation Sequencing (NGS) on total RNA of wild type (WT) and Y41F mutant. The goal of this study is to compare the transcriptome profile of Y41F mutant to WT cells.

ORGANISM(S): Schizosaccharomyces pombe

PROVIDER: GSE102125 | GEO | 2017/12/06

SECONDARY ACCESSION(S): PRJNA396743

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Bat3-/- BMDC Transcriptomes III

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived WT or Bat3 KO BMDC transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2022-01-11 | GSE169663 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Bat3-/- BMDC Transcriptomes I

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived WT or Bat3 KO BMDC transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2022-01-11 | GSE169530 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Cd226-/- BMDM Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare WT-BMDM vs. cd226-BMDM transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2024-08-10 | GSE181758 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and AXL-/- astrocytes Transcriptomes

Project description:Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare Wild Type astrocytes transcriptome profiling (RNA-seq) to AXL-/- astrocytes transcriptome profiling and to explore the mechanism by which AXL interferes with type I IFN signaling in WT astrocytes. We performed an RNA-Seq analysis of WT and AXL-/- U-251MG cells in the absence of ZIKV. Surprisingly, the intrinsic level of type I IFN signaling was lower in AXL-/- cells than in WT cells. This result was further confirmed by RT-qPCR

2017-11-06 | GSE106545 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Zfyve19-/- hepatic Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived hepatic transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2021-03-27 | GSE169737 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and SMAD4 Y95 Mutation Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of Y95 phosphorylation on SMAD4-mediated transcription in response to TGF-b signals. The goals of this study are to compare transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis Methods: mRNA profiles of HaCaT parental and SMAD4 KO cells stably expressing wild-type SMAD4 (WT), Y95E or Y95F mutant, and GFP (as control) under with or without TGF-b were generated by deep sequencing, using Illumina HiSeq X Ten. qRT–PCR validation was performed using TaqMan and SYBR Green assays Conclusions: hierarchical clustering of the global gene expression profiles of TGF-β treated cells revealed that wild-type-SMAD4- and Y95F-mutant-rescued SMAD4-null cells were highly similar to the parental HaCaT cells, whereas GFP- and Y95E-mutant-rescued cells formed a separate cluster

2018-10-22 | GSE121188 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Mettl5-/- brain Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived brain transcriptome. Methods: Brain mRNA profiles of 28-day-old wild-type (WT) and methyltransferase like 5 knockout (Mettl5−/−) mice were generated by using oligo(dT)-attached magnetic beads enrichemnt. The sequence reads that passed twice quality filters were analyzed at the transcript isoform level with Bowtie2 for quantitative gene analysis and with DEGseq for differentially expressed genes analysis. Results: 6 samples were tested by using the BGISEq-500 platform, and each sample produced 21.45 M data on average. The average ratio of samples to genomes (mm10) was over 96%; A total of 18,491 genes were detected.

2020-10-01 | GSE153138 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of IBP Transcriptomes

2021-09-08 | GSE183578 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of CHAA Transcriptomes

2021-04-27 | GSE173379 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Wild Type and Bat3-/- BMDC Transcriptomes II

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to compare NGS-derived retinal transcriptome profiling (RNA-seq) to microarray and quantitative reverse transcription polymerase chain reaction (qRT–PCR) methods and to evaluate protocols for optimal high-throughput data analysis

2022-01-11 | GSE169550 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data