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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 scatter plot of data from three technical replicate hybridizations of a single sample. For all samples, the scatter plots revealed tight correlation between raw and normalized data replicates, which overall, points to high repeatability of technical replicate hybridizations.
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f0015: Representative scatter plot of data from three technical replicate hybridizations of a single sample. For all samples, the scatter plots revealed tight correlation between raw and normalized data replicates, which overall, points to high repeatability of technical replicate hybridizations.

Mentions: Next, we compared scatter plots of raw and normalized log2 data for each sample using the R function pairs. Only data with a P-value detected < 0.01 were included. A representative scatter plot is shown in Fig. 3. Scatter plots were viewed in conjunction with Pearson correlation tables. Correlation values were calculated from both raw and normalized log2 intensities for each technical repeat. Only probes with P-value detected < 0.01 were included in the calculation. Scatter plots confirmed high repeatability among technical replicates.


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 scatter plot of data from three technical replicate hybridizations of a single sample. For all samples, the scatter plots revealed tight correlation between raw and normalized data replicates, which overall, 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

f0015: Representative scatter plot of data from three technical replicate hybridizations of a single sample. For all samples, the scatter plots revealed tight correlation between raw and normalized data replicates, which overall, points to high repeatability of technical replicate hybridizations.
Mentions: Next, we compared scatter plots of raw and normalized log2 data for each sample using the R function pairs. Only data with a P-value detected < 0.01 were included. A representative scatter plot is shown in Fig. 3. Scatter plots were viewed in conjunction with Pearson correlation tables. Correlation values were calculated from both raw and normalized log2 intensities for each technical repeat. Only probes with P-value detected < 0.01 were included in the calculation. Scatter plots confirmed high repeatability among technical replicates.

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