|
Status |
Public on Jul 12, 2017 |
Title |
met_RHH1616 |
Sample type |
SRA |
|
|
Source name |
squamous cell carcinoma, metastatic tumor
|
Organism |
Homo sapiens |
Characteristics |
disease status: squamous cell carcinoma tissue: metastatic lymph node tumor sample type: single cell
|
Extracted molecule |
total RNA |
Extraction protocol |
RNA isolated from cells using the SMARTer Ultra Low RNA Kit for the Fluidigm C1 System (Clontech). Library construction: In accordance to protocol from Fluidigm describing the use of the C1 system to generate cDNA library for single cell RNA-seq. Briefly, cDNA was synthesized using SMARTer Ultra Low RNA Kit for the Fluidigm C1 System from Clontech; library was constructed using Nextera XT DNA Sample Preparation Kit and Nextera XT DNA Library Preparation Index Kits from Illumina.
|
|
|
Library strategy |
RNA-Seq |
Library source |
transcriptomic |
Library selection |
cDNA |
Instrument model |
Illumina HiSeq 4000 |
|
|
Description |
Metastatic cancer PolyA+ RNA Processed data file: expression.txt
|
Data processing |
BAM files produced using Tophat-2.1.0. FPKM obtained using Cuffdiff-2.2.1. The RefSeq genes are tracked for analysis. Genome_build: hg19 (GRCh37) Supplementary_files_format_and_content: expression.txt: The tab-delimited text file contains the log2(1+pQ normalized FPKM) expression matrix for all individual cells. For details about pQ normalization, see Sengupta, Debarka, et al. "Fast, scalable and accurate differential expression analysis for single cells." bioRxiv (2016): 049734.
|
|
|
Submission date |
Jul 14, 2016 |
Last update date |
May 15, 2019 |
Contact name |
Debarka Sengupta |
E-mail(s) |
debarka@gmail.com
|
Organization name |
Indraprastha Institute of Information Technology
|
Department |
Computational Biology and Computer Science
|
Street address |
IIIT Delhi, Okhla Phase 3
|
City |
Delhi |
State/province |
Delhi |
ZIP/Postal code |
110020 |
Country |
India |
|
|
Platform ID |
GPL20301 |
Series (1) |
GSE84323 |
Phenotype-driven precision oncology in patient-derived tumor models predict therapeutic response in squamous cell carcinoma |
|
Relations |
BioSample |
SAMN05391892 |
SRA |
SRX1949090 |