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Hypoxic transcriptomic signature of A549 cells (Agilent microarrays)

ABSTRACT: Hypoxic transcriptomic signature of A549 cells (Agilent microarrays)

PROVIDER: PRJNA480893 | ENA |

REPOSITORIES: ENA

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Hypoxic transcriptomic signature of A549 cells (Agilent microarrays)

Project description:To assess the transcriptomic response of the LUAD cell line A549 to hypoxia, cells were exposed to 1% (Hx) or 21% O2 (Nx) during 24 hours. Two independent experiments were carried out.

2019-09-04 | GSE117041 | GEO

Hypoxic transcriptomic signature of A549 cells (RNA-Seq)

Project description:Hypoxic transcriptomic signature of A549 cells (RNA-Seq)

| PRJNA480905 | ENA

Hypoxic transcriptomic signature of A549 cells (RNA-Seq)

Project description:To assess the transcriptomic response of the LUAD cell line A549 to hypoxia, cells were exposed to 1% (Hx) or 21% O2 (Nx) during 24 hours. Two µg of total RNAs were depleted from ribosomal RNA with the Ribozero kit (epicenter), libraries were generated with the NEBNext Small RNA Library Prep Set for SOLiD and sequenced on SOLiD 5500XL (Life Technologies) with single-end 50bp reads. Reads were aligned to the human genome release hg19 with the LifeScope software v2.5.1 (Life Technologies) using whole transcriptome pipeline for RNA‐seq libraries with default parameters.

2019-09-04 | GSE117048 | GEO

caArray_EXP-576: TCGA (LUAD): Gene Expression Analysis of TCGA samples using Agilent Expression 244K microarrays (UNC)

Project description:Gene Expression Analysis of TCGA samples using Agilent Expression 244K microarrays.

2015-05-13 | GSE68787 | GEO

caArray_EXP-574: TCGA(Kirc): Gene Expression Analysis of TCGA samples using Agilent Expression 244K microarrays (UNC)

Project description:Gene Expression Analysis of TCGA samples using Agilent Expression 244K microarrays.

2015-05-13 | GSE68784 | GEO

Impact of NLUCAT1 deletion on A549 cells in normoxic and hypoxic conditions

Project description:Impact of NLUCAT1 deletion on A549 cells in normoxic and hypoxic conditions

| PRJNA480884 | ENA

Chromatin Protein PC4 Orchestrates B Cell Differentiation by Collaborating with IKAROS and IRF4 (Agilent microarrays)

Project description:Chromatin Protein PC4 Orchestrates B Cell Differentiation by Collaborating with IKAROS and IRF4 (Agilent microarrays)

| PRJNA608862 | ENA

Agilent striptease

Project description:new and stripped microarrays Keywords: reuse of Agilent custom 8.4 in situ microarrays

2005-08-20 | GSE2834 | GEO

Extended analysis of benchmark datasets for Agilent two-color microarrays.

Project description:BackgroundAs part of its broad and ambitious mission, the MicroArray Quality Control (MAQC) project reported the results of experiments using External RNA Controls (ERCs) on five microarray platforms. For most platforms, several different methods of data processing were considered. However, there was no similar consideration of different methods for processing the data from the Agilent two-color platform. While this omission is understandable given the scale of the project, it can create the false impression that there is consensus about the best way to process Agilent two-color data. It is also important to consider whether ERCs are representative of all the probes on a microarray.ResultsA comparison of different methods of processing Agilent two-color data shows substantial differences among methods for low-intensity genes. The sensitivity and specificity for detecting differentially expressed genes varies substantially for different methods. Analysis also reveals that the ERCs in the MAQC data only span the upper half of the intensity range, and therefore cannot be representative of all genes on the microarray.ConclusionAlthough ERCs demonstrate good agreement between observed and expected log-ratios on the Agilent two-color platform, such an analysis is incomplete. Simple loess normalization outperformed data processing with Agilent's Feature Extraction software for accurate identification of differentially expressed genes. Results from studies using ERCs should not be over-generalized when ERCs are not representative of all probes on a microarray.

| S-EPMC2174956 | biostudies-literature

The hypoxic landscape of melanoma

Project description:Micro-environment played an important role in the disease progression and overall survival. More recently, hypoxic signature were identified as one of the key signatures of innate anti-PD1 resistance, however, relatively little had been done to identify the key molecular signature of hypoxic response in melanoma and how these may correlated with other know signatures which correlate with poor prognosis. In this study we performed large scale study which integrate ChIP-seq of HIF (in one cell line) and RNA-seq (in three commonly used melanoma cell lines) to identify a common melanoma hypoxic signature. The finding were used to further integrated with our other genome wide which focus on MITF (the master regulator of the melanocyte lineage and a melanoma lineage oncogene, GSE77609) to elucidate the intricate interplay between MITF and HIF and how this interplay define a melanoma specific response to hypoxia.

2019-06-12 | GSE95280 | GEO

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