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Series GSE129240 Query DataSets for GSE129240
Status Public on Apr 03, 2019
Title Complete deconvolution of cellular mixtures based on linearity of transcriptional signatures
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary Difference in RNA content of different cell types introduces bias to gene expression deconvolution methods. If ERCC spike-ins are introduced into samples, predicted proportions of deconvolution methods can be corrected
 
Overall design Two cell types of distinctly different sizes and RNA per cell content: HEK cells and Jurkat cells were mixed in different proportions ensuring that each mixture contained total of one million cells. We sequenced RNA of the samples (including ERCC spike-in controls to 382 be able to control for the absolute RNA-concentration).
 
Contributor(s) Konstantin Z, Bambouskova M, Swain A, Artyomov MN
Citation(s) 31101809
Submission date Apr 02, 2019
Last update date May 29, 2019
Contact name Maxim Artyomov
E-mail(s) martyomov@wustl.edu
Organization name WASHINGTON UNIVERSITY IN ST LOUIS
Department Pathology & Immunology
Lab Artyomov lab
Street address 425 S Euclid Ave
City St. Louis
State/province Missouri
ZIP/Postal code 63110
Country USA
 
Platforms (1)
GPL16791 Illumina HiSeq 2500 (Homo sapiens)
Samples (14)
GSM3703348 Mixture 1: 100% HEK, 0% Jurkat
GSM3703349 Mixture 2: 100% HEK, 0% Jurkat
GSM3703350 Mixture 3: 80% HEK, 20% Jurkat
Relations
BioProject PRJNA530575
SRA SRP190212

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE129240_RAW.tar 21.2 Mb (http)(custom) TAR (of TXT)
GSE129240_rsem_expected_counts.tsv.gz 984.3 Kb (ftp)(http) TSV
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

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