Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Next Generation Sequencing Facilitates Quantitative Analysis of EL4+Ctrl and EL4+RGFP966 cells' Transcriptomes in T cells lymphoma

ABSTRACT: Next Generation Sequencing Facilitates Quantitative Analysis of EL4+Ctrl and EL4+RGFP966 cells' Transcriptomes in T cells lymphoma

PROVIDER: PRJNA1017862 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR26071833_1.fastq.gz	Fastqsanger.gz
	SRR26071833_2.fastq.gz	Fastqsanger.gz
	SRR26071834_1.fastq.gz	Fastqsanger.gz
	SRR26071834_2.fastq.gz	Fastqsanger.gz
	SRR26071835_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 12

Similar Datasets

Next Generation Sequencing Facilitates Quantitative Analysis of EL4+Ctrl and EL4+RGFP966 cells' Transcriptomes in T cells lymphoma

Project description:We here reported that HDAC3 inhibition induces the infiltration of NK cells in lymphoma and enhances their cytotoxicity by promoting the secretion of CXCL12 from lymphoma cells. RNA-seq analysis of EL4 cells treated with or without RGFP966 showed that chemokine signaling was significantly enriched in the HDAC3 inhibitor-treated group. And the expression of CXCL12 in mRNA and protein level were increased. ATF3 overexpression decreased the mRNA level of CXCL12 in lymphoma cells and reduced CXCL12 transcription can be reversed by HDAC3 inhibition in H9 cells. To sum up, targeting HDAC3 promoted the secretion of CXCL12 by inhibiting ATF3’s transcriptional activity.

2024-04-18 | GSE243346 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' Transcriptomes in lymphoma

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in Ctrl-Cas9 and TRIB3-Cas9 lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: Ctrl-Cas9 and TRIB3-Cas9 cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina GAIIx. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2020-10-01 | GSE117128 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' Transcriptomes in lymphoma

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' Transcriptomes in lymphoma

| PRJNA481246 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-siRNA and c-Myc-siRNA cells' Transcriptomes in lymphoma

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in Ctrl-siRNA and c-Myc-siRNA lymphoma cells by using NGS-derived lymphoma transcriptome profiling (RNA-seq). Methods: Ctrl-siRNA and c-Myc-siRNA cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of Ctrl-siRNA and c-Myc-siRNA cells' transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2020-10-02 | GSE126739 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-siRNA and c-Myc-siRNA cells' Transcriptomes in lymphoma

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-siRNA and c-Myc-siRNA cells' Transcriptomes in lymphoma

| PRJNA523180 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of WT and GSH or Ctrl and Cas9 mouse breast cancer cells Transcriptomes

Project description:Purpose: Next-generation sequencing (NGS) has revolutionized systems-based analysis of cellular pathways. The goals of this study are to analysis the differiational genes and pathways in WT and WT+GSH or Ctrl-Cas9 and Scarb2-Cas9 mouse breast cancer cells by using NGS-derived transcriptome profiling (RNA-seq). Methods: 4T1 cells treated with or without GSH (500 µM) and 4T1 stably expressing Ctrl-Cas9 or Scarb2-Cas9 were collected. These cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina HiSeq 4000. The sequence reads that passed quality filters were analyzed at the transcript isoform level with following methods: Alignment by using HISAT2 v2.1, IGV was used to to view the mapping result by the Heatmap, histogram, scatter plot or other stytle, FPKM was then calculated to estimate the expression level of genes in each sample, DEGseq v1.18.0 was used for differential gene expression analysis between two samples with non biological replicates and Function Enrichment Analysis including GO enrichment analysis and KEGG . Conclusions: Our study represents the first detailed analysis of WT and WT+GSH or Ctrl-Cas9 and Scarb2-Cas9 mouse breast cancer cells' transcriptomes, with biologic replicates, generated by RNA-seq technology. The optimized data analysis workflows reported here should provide a framework for comparative investigations of expression profiles. Our results show that NGS offers a comprehensive and more accurate quantitative and qualitative evaluation of mRNA content within a cell or tissue. We conclude that RNA-seq based transcriptome characterization would expedite genetic network analyses and permit the dissection of complex biologic functions.

2024-10-09 | GSE252087 | GEO

Next Generation Sequencing Facilitates Quantitative Analysis of WT and GSH or Ctrl and Cas9 mouse breast cancer cells Transcriptomes

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of WT and GSH or Ctrl and Cas9 mouse breast cancer cells Transcriptomes

| PRJNA1057739 | ENA

Sequencing data of lymphoma samples treated with chidamide and ctrl

Project description:Sequencing data of lymphoma samples treated with chidamide and ctrl Raw sequence reads

| PRJNA769397 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of ad-control and ad-ube3b cells' Transcriptomes in lymphoma

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of ad-control and ad-ube3b cells' Transcriptomes in lymphoma

| PRJNA523178 | ENA

Next Generation Sequencing Facilitates Quantitative Analysis of control and Pep2-CM4-treated cells' Transcriptomes in lymphoma

Project description:Next Generation Sequencing Facilitates Quantitative Analysis of control and Pep2-CM4-treated cells' Transcriptomes in lymphoma

| PRJNA523179 | ENA

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