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Transcriptional profiling of differentially expressed long non-coding RNAs in breast cancer.

Wang L, Shen X, Xie B, Ma Z, Chen X, Cao F - Genom Data (2015)

Bottom Line: However, little is known about their mechanistic role in breast cancer pathogenesis, especially in triple-negative breast carcinomas (TNBC) that have particular poor outcomes.The basic analysis as contained in the manuscript published in Oncotarget with the PMID 26078338.These data can be used to further elucidate the mechanisms of breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Taizhou Hospital, Wenzhou Medical University, Taizhou, Zhejiang, China.

ABSTRACT
Long non-coding RNAs (lncRNAs) are subclass of noncoding RNAs that have been recently shown to play critical roles in cancer biology. However, little is known about their mechanistic role in breast cancer pathogenesis, especially in triple-negative breast carcinomas (TNBC) that have particular poor outcomes. This study was specifically designed to identify the signatures relevant lncRNAs in breast cancer and characterize lncRNAs that modulate the phenotype. Here we provide detailed methods and analysis of microarray data, which is deposited in the Gene Expression Omnibus (GEO) with the accession number GSE64790. The basic analysis as contained in the manuscript published in Oncotarget with the PMID 26078338. These data can be used to further elucidate the mechanisms of breast cancer.

No MeSH data available.


Related in: MedlinePlus

Representative box plot of raw data from three technical replicate hybridizations of a single sample. For all samples, the box plots revealed median-centered raw data distributions, which were further refined during normalization. Overall, this points to high repeatability of technical replicate hybridizations.
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f0010: Representative box plot of raw data from three technical replicate hybridizations of a single sample. For all samples, the box plots revealed median-centered raw data distributions, which were further refined during normalization. Overall, this points to high repeatability of technical replicate hybridizations.

Mentions: Since three technical replicate hybridizations were performed and later averaged, care was taken to ensure high repeatability between technical replicates. First, raw and normalized log2 data for each sample were plotted using the R function boxplot. Control and flagged probes were not included. A representative box plot is shown in Fig. 2. While this analysis is designed to identify hybridizations that have intensity distributions different from those of their technical replicates, we did not find any instances of this. This analysis also ensures that the normalization has correctly centered the distributions of each replicate microarray.


Transcriptional profiling of differentially expressed long non-coding RNAs in breast cancer.

Wang L, Shen X, Xie B, Ma Z, Chen X, Cao F - Genom Data (2015)

Representative box plot of raw data from three technical replicate hybridizations of a single sample. For all samples, the box plots revealed median-centered raw data distributions, which were further refined during normalization. Overall, this points to high repeatability of technical replicate hybridizations.
© Copyright Policy - CC BY-NC-ND
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4664755&req=5

f0010: Representative box plot of raw data from three technical replicate hybridizations of a single sample. For all samples, the box plots revealed median-centered raw data distributions, which were further refined during normalization. Overall, this points to high repeatability of technical replicate hybridizations.
Mentions: Since three technical replicate hybridizations were performed and later averaged, care was taken to ensure high repeatability between technical replicates. First, raw and normalized log2 data for each sample were plotted using the R function boxplot. Control and flagged probes were not included. A representative box plot is shown in Fig. 2. While this analysis is designed to identify hybridizations that have intensity distributions different from those of their technical replicates, we did not find any instances of this. This analysis also ensures that the normalization has correctly centered the distributions of each replicate microarray.

Bottom Line: However, little is known about their mechanistic role in breast cancer pathogenesis, especially in triple-negative breast carcinomas (TNBC) that have particular poor outcomes.The basic analysis as contained in the manuscript published in Oncotarget with the PMID 26078338.These data can be used to further elucidate the mechanisms of breast cancer.

View Article: PubMed Central - PubMed

Affiliation: Department of Pediatrics, Taizhou Hospital, Wenzhou Medical University, Taizhou, Zhejiang, China.

ABSTRACT
Long non-coding RNAs (lncRNAs) are subclass of noncoding RNAs that have been recently shown to play critical roles in cancer biology. However, little is known about their mechanistic role in breast cancer pathogenesis, especially in triple-negative breast carcinomas (TNBC) that have particular poor outcomes. This study was specifically designed to identify the signatures relevant lncRNAs in breast cancer and characterize lncRNAs that modulate the phenotype. Here we provide detailed methods and analysis of microarray data, which is deposited in the Gene Expression Omnibus (GEO) with the accession number GSE64790. The basic analysis as contained in the manuscript published in Oncotarget with the PMID 26078338. These data can be used to further elucidate the mechanisms of breast cancer.

No MeSH data available.


Related in: MedlinePlus