microarray data and clinical information of breast cancer patient cohort Search Results


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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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Broad Institute Inc breast cancer microarray dataset
A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and <t>bcar3</t> ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.
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Image Search Results


A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and bcar3 ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.

Journal: PLoS ONE

Article Title: Repeated Small Perturbation Approach Reveals Transcriptomic Steady States

doi: 10.1371/journal.pone.0029241

Figure Lengend Snippet: A and B ) Seven genes were chosen randomly from the set of genes with steady-state characteristics for this comparison. egfl5, cnn3, and bcar3 ( A ) exhibit immediate down-regulated responses, while pmaip1, jun, id2, and gadd45a ( B ) exhibit immediate up-regulated responses followed by relaxation. Solid and dash lines represent real-time PCR data and microarray data, respectively. The error bar of the microarray data indicates standard deviation estimated by the log linear model. The error bar of real-time PCR data is the standard deviation derived from three sets of CTs. C ) Scatter plot of real-time PCR results versus microarray data. The correlation coefficient, R is 0.93. The red line is a linear fit through all points. These results clearly demonstrate that even at the small fold change data points, these two sets of data agree very well. It also demonstrates the high reliability and resolution of our cDNA microarray system, which makes this kind of small perturbation study possible.

Article Snippet: The assay ID of corresponding probe sets and primers in the ABI's database are Hs00182488_m1, Hs00156565_m1, Hs00323519_m1, Hs00169255_m1, Hs00747379_m1, Hs01103582_s1, and Hs00382168_m1, respectively.

Techniques: Real-time Polymerase Chain Reaction, Microarray, Standard Deviation, Derivative Assay