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GSE61946

GSE GEO
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hESC-derived liver transcriptome analysis

Organism: Homo sapiens
Platform: GPL9052
Samples: 2
Experiment Types:
Expression profiling by high throughput sequencing
Submitted: Oct 01 2014
Last Updated: May 15 2019
Status: Public on Aug 07 2015
Contact: Maike,,Sander (UC San Diego)

Relations

SubSeries of: GSE61948 BioProject: https://www.ncbi.nlm.nih.gov/bioproject/PRJNA262733 SRA: https://www.ncbi.nlm.nih.gov/sra?term=SRP048557

Summary

To characterize the transcriptional programs that underlie pancreas differentiation and identity, we have generated genome-scale expression profiles by RNA-seq from human embryonic stem cell derived liver progenitors and human fetal pancreatic tissue (days 54-57 post conception). These samples were compared to those already published transcriptomes (Xie et al., 2013). Together, these samples were used to perform principles compotent analysis. Once this was performed, we were able to identify transcription factors that were important in the identity of each cell type.

Overall Design

To generate genome-scale expression profiles by RNA-seq from human embryonic stem cell derived liver progenitors, total RNA was isolated from human embryonic stem cell derived liver progenitors. Libraries were sequenced and mapped to the hg19 version of the human genome. Gene expression was determined using Sailfish. These samples were compared to those already published transcriptomes (Xie et al., 2013). Together, these samples were used to perform principles compotent analysis.

Analysis (9 steps)

View Data Processing
Processing steps for GSE61946
  1. Quality Control.
  2. Quality of sequencing data is analyzed using the software FastQC v0.10.1.
  3. The results are examined to determine if samples are of questionable quality on an array of metrics.
  4. Mapping.
  5. Alignment of sequencing data to reference genomes is performed with the software RNA-Star 2.3.0e.
  6. Parameters are set to default and reads are mapped to references along with splice junction databases.
  7. Gene Expression Quantification.
  8. To obtain gene expression values, several quantification methods are used (Sailfish 0.6.3, Cufflinks 2.2.0).
Showing first 8 steps.

Supplementary Files (1)

GSE61946_rpkm_table_liver_Ensemble_annotated.txt.gz Download
GEO Samples (2)

Dataset Citations (1)

A Gene Regulatory Network Cooperatively Controlled by Pdx1 and Sox9 Governs Lineage Allocation of Foregut Progenitor Cells.
PMID 26440894 · 2015 · Cell reports
Hung Ping Shih, Philip A Seymour, Nisha A Patel, Ruiyu Xie, Allen Wang, Patrick P Liu, Gene W Yeo, Mark A Magnuson, Maike Sander

SRA Experiments (2) and Runs (2)

Total: 3177 MB
SRX718112 SRP048557 RNA-Seq SINGLE
GSM1517600: hESC_derived_liverprogenitors_RNAseq replicate 1; Homo sapiens; RNA-Seq
Sample: SRS713929
BioProject: PRJNA262733
BioSample: SAMN03085518
Platform: ILLUMINA
Instrument: Illumina Genome Analyzer
Organism: Homo sapiens
Sample attributes
source_name: hESC-derived liver progenitors
cell line: CyT49
cell type: hESC-derived liver progenitors
Original files (1)
hESC-derived liver progenitors
Runs (1)
Run Spots Bases Size (MB) Files Link
SRR1593955 27781131 2778113100 1567.38 FGC0186_s_7_sequence.fastq.gz, SRR1593955 SRA
SRX718113 SRP048557 RNA-Seq SINGLE
GSM1517601: hESC_derived_liverprogenitors_RNAseq replicate 2; Homo sapiens; RNA-Seq
Sample: SRS713928
BioProject: PRJNA262733
BioSample: SAMN03085519
Platform: ILLUMINA
Instrument: Illumina Genome Analyzer
Organism: Homo sapiens
Sample attributes
source_name: hESC-derived liver progenitors
cell line: CyT49
cell type: hESC-derived liver progenitors
Original files (1)
hESC-derived liver progenitors
Runs (1)
Run Spots Bases Size (MB) Files Link
SRR1593956 27896714 2789671400 1609.88 FGC0186_s_8_sequence.fastq.gz, SRR1593956 SRA

Linked Publications (1)

Data Files (3)

Accession File Name Stored Type Output Type Mapping Assembly Size Download
FGC0186_s_7_sequence.fastq.gz RNA-Seq 1.5 GB link
FGC0186_s_8_sequence.fastq.gz RNA-Seq 1.6 GB link
SRR1593955 RNA-Seq 1.5 GB link