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accession-icon SRP001462
Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data.
  • organism-icon Homo sapiens
  • sample-icon 4 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Next-generation sequencing has become an important tool for genome-wide quantification of DNA and RNA. However, a major technical hurdle lies in the need to map short sequence reads back to their correct locations in a reference genome. Here we investigate the impact of SNP variation on the reliability of read-mapping in the context of detecting allele-specific expression (ASE).We generated sixteen million 35 bp reads from mRNA of each of two HapMap Yoruba individuals. When we mapped these reads to the human genome we found that, at heterozygous SNPs, there was a significant bias towards higher mapping rates of the allele in the reference sequence, compared to the alternative allele. Masking known SNP positions in the genome sequence eliminated the reference bias but, surprisingly, did not lead to more reliable results overall. We find that even after masking, $\sim$5-10\% of SNPs still have an inherent bias towards more effective mapping of one allele. Filtering out inherently biased SNPs removes 40\% of the top signals of ASE. The remaining SNPs showing ASE are enriched in genes previously known to harbor cis-regulatory variation or known to show uniparental imprinting. Our results have implications for a variety of applications involving detection of alternate alleles from short-read sequence data. Scripts, written in Perl and R, for simulating short reads, masking SNP variation in a reference genome, and analyzing the simulation output are available upon request from JFD. Overall design: RNA-Seq on two YRI Hapmap cell lines. Each individual sequenced on two lanes of the Illumina Genome Analyzer

Publication Title

Effect of read-mapping biases on detecting allele-specific expression from RNA-sequencing data.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP001540
Understaning mechanisms underlying human gene expression variation with RNA sequencing
  • organism-icon Homo sapiens
  • sample-icon 161 Downloadable Samples
  • Technology Badge IconIlluminaGenomeAnalyzerII

Description

Understanding the genetic mechanisms underlying natural variation in gene expression is a central goal of both medical and evolutionary genetics, and studies of expression quantitative trait loci (eQTLs) have become an important tool for achieving this goal. While all eQTL studies to date have assayed mRNA levels using expression microarrays, recent advances in RNA sequencing enable the analysis of transcript variation at unprecedented resolution. We sequenced RNA from 69 lymphoblastoid cell lines (LCLs) derived from unrelated Nigerian individuals that have been extensively genotyped by the International HapMap Project. Pooling data from all individuals, we generated a map of the transcriptional landscape of these cells, identifying extensive use of unannotated polyadenylation sites and over 100 novel putative protein-coding exons. Using the genotypes from the HapMap project, we identified over a thousand genes at which genetic variation influences overall expression levels or splicing. We demonstrate that eQTLs near genes generally act via a mechanism involving allele-specific expression, and that variation that influences the inclusion of an exon is enriched within or near the consensus splice sites. Our results illustrate the power of high-throughput sequencing for the joint analysis of variation in transcription, splicing, and allele-specific expression across individuals. Overall design: RNA-Seq in 69 lymphoblastoid cell lines from multiple Yoruban HapMap individuals in at least two replicate lanes per individual

Publication Title

Understanding mechanisms underlying human gene expression variation with RNA sequencing.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE29759
The Role of microRNAs in Neural Stem Cell-supported Endothelial Morphogenesis
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

MicroRNA microarrays and RNA expression arrays were used to identify functional signaling between neural stem cell progenitor cells (NSPC) and brain endothelial cells (EC) that are critical during embryonic development and tissue repair following brain injury.

Publication Title

The role of microRNAs in neural stem cell-supported endothelial morphogenesis.

Sample Metadata Fields

Specimen part, Disease, Treatment

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accession-icon GSE88966
Depot dependent effects of dexamethasone on gene expression in human omental and abdominal subcutaneous adipose tissues from obese women.
  • organism-icon Homo sapiens
  • sample-icon 26 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

We used microarrays to identify transcripts regulated by dexamethasone in omental (Om) and abdominal subcutaneous (Abdsc) adipose tissues of severely obese females obtained during elective surgeries.

Publication Title

Depot Dependent Effects of Dexamethasone on Gene Expression in Human Omental and Abdominal Subcutaneous Adipose Tissues from Obese Women.

Sample Metadata Fields

Specimen part, Disease stage, Treatment

View Samples
accession-icon GSE42997
The ISWI ATPase Snf2L is required for superovulation and regulates Fgl2 in differentiating mouse granulosa cells
  • organism-icon Mus musculus
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We investigate the role of Snf2l in ovaries by characterizing a mouse bearing an inactivating deletion on the ATPase domain of Snf2l (Ex6DEL). Snf2l mutant mice produce significantly fewer eggs than control mice when superovulated. Thus, gonadotropin stimulation leads to a significant deficit in secondary follicles and an increase in abnormal antral follicles. We profiled the expression of granulosa cells from Snf2l WT and Ex6DEL mice treated with pregnant mares' serum gonadotropin followed by human chorionic gonadotropin

Publication Title

The imitation switch ATPase Snf2l is required for superovulation and regulates Fgl2 in differentiating mouse granulosa cells.

Sample Metadata Fields

Specimen part

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accession-icon GSE35766
Identification of the cortical neurons that mediate antidepressant responses
  • organism-icon Mus musculus
  • sample-icon 30 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Identification of the cortical neurons that mediate antidepressant responses.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE20854
EGFR Isoforms and Gene Regulation in Human Endometrial Cancer Cells
  • organism-icon Homo sapiens
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Microarrays were used to analyze differential gene expression and to help determine the efficacy of Iressa (gefitinib), a tyrosine kinase inhibitor, on endometrial cancer cells.

Publication Title

EGFR isoforms and gene regulation in human endometrial cancer cells.

Sample Metadata Fields

Specimen part, Cell line

View Samples
accession-icon GSE18235
Effect of 10 Cigarette Smoke Condensates on Primary Human Airway Epithelial Cells
  • organism-icon Homo sapiens
  • sample-icon 21 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

Nine cigarette smoke condensates (CSCs) were produced under a standard ISO smoking machine regimen and one was produced by a more intense smoking machine regimen. These CSCs were used to treat primary normal human bronchial epithelial cells for 18 hours.

Publication Title

Effects of 10 cigarette smoke condensates on primary human airway epithelial cells by comparative gene and cytokine expression studies.

Sample Metadata Fields

Specimen part

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accession-icon GSE35758
Comparative analysis of S100a10 and Glt25d2 cortical pyramidal cells
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Molecular phenotyping of cell types and neural circuits underlying pathological neuropsychiatric conditions and their responses to therapy provides one avenue for the development of more specific and effective treatments. In this study, we identify a cell population in the cerebral cortex that shows robust and specific molecular adaptations following long-term SSRI treatment.

Publication Title

Identification of the cortical neurons that mediate antidepressant responses.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE35751
Comparative analysis of S100a10-expressing cortical pyramidal cells and whole cortex
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Molecular phenotyping of cell types and neural circuits underlying pathological neuropsychiatric conditions and their responses to therapy provides one avenue for the development of more specific and effective treatments. In this study, we identify a cell population in the cerebral cortex that shows robust and specific molecular adaptations following long-term SSRI treatment.

Publication Title

Identification of the cortical neurons that mediate antidepressant responses.

Sample Metadata Fields

Specimen part, Treatment

View Samples
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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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