 |
 |
GEO help: Mouse over screen elements for information. |
|
| Status |
Public on Oct 01, 2020 |
| Title |
Next Generation Sequencing Facilitates Quantitative Analysis of Ctrl-Cas9 and TRIB3-Cas9 cells' Transcriptomes in lymphoma |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by high throughput sequencing
|
| Summary |
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.
|
| |
|
| Overall design |
Ctrl-Cas9 and TRIB3-Cas9 cells' mRNA profiles were generated by deep sequencing, in triplicate, using Illumina.
|
| |
|
| Contributor(s) |
Hu Z, Li K, Wang F |
| Citation(s) |
33298911 |
| |
| Submission date |
Jul 16, 2018 |
| Last update date |
Dec 22, 2020 |
| Contact name |
wang feng |
| E-mail(s) |
wangfeng123@imm.ac.cn
|
| Phone |
15624968856
|
| Organization name |
Chinese Academy of Medical Sciences & Peking Union Medical College,
|
| Street address |
nan wei road
|
| City |
bei jing |
| ZIP/Postal code |
associate professor |
| Country |
China |
| |
|
| Platforms (1) |
| GPL20301 |
Illumina HiSeq 4000 (Homo sapiens) |
|
| Samples (6)
|
|
| Relations |
| BioProject |
PRJNA481246 |
| SRA |
SRP153807 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE117128_RAW.tar |
16.2 Mb |
(http)(custom) |
TAR (of TXT) |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
|
|
|
|
 |
Less...
More...