Example Analysis of RNA degradation Diagram of Chip
Xiaobian to share with you the sample analysis of chip RNA degradation map, I believe most people still do not know much, so share this article for your reference, I hope you have a lot of harvest after reading this article, let's go to understand it together!
Chip RNA degradation map
RNA degradation is a very important factor affecting the quality of chip data. Generally, RNA degradation starts from the 5-terminal, so theoretically the fluorescence intensity of the 5-terminal probe should be lower than that of the 3-terminal probe.
The slope of the RNA degradation curve indicates this trend. The smaller the slope, the less degradation.
If the slope is too small, or even close to zero, special care should be taken, and all degradation may occur.
Based on affytrix chip CEL file, AffyRNAdeg function based on affy package can be obtained after AffyBatch is obtained to obtain RNA degradation situation (GSE66196)
RNAdeg=AffyRNAdeg(AffyBatch)> summaryAffyRNAdeg(RNAdeg) GSM1616746_Pool_1_Hilscher_26-07-2012.CEL.gz GSM1616747_Pool_1_Reif-Hilscher_8-2-2012.CEL.gzslope 4.30e+00 4.07e+00pvalue 3.61e-11 1.96e-11 GSM1616748_Pool_1wdh_Reif-Hilscher_9-2-2012.CEL.gz GSM1616749_Pool_2_Hilscher_26-07-2012.CEL.gzslope 4.03e+00 4.29e+00pvalue 1.93e-11 3.55e-11 GSM1616750_Pool_2_Reif-Hilscher_8-2-2012.CEL.gz GSM1616751_Pool_2wdh_Reif-Hilscher_9-2-2012.CEL.gzslope 3.98e+00 4.09e+00pvalue 8.56e-11 1.44e-11 GSM1616752_Pool_3_Hilscher_26-07-2012.CEL.gz GSM1616753_Pool_3_Reif-Hilscher_8-2-2012.CEL.gzslope 4.24e+00 3.94e+00pvalue 1.19e-11 1.26e-11 GSM1616754_Pool_3wdh_Reif-Hilscher_9-2-2012.CEL.gz GSM1616755_Pool_4_Hilscher_26-07-2012.CEL.gzslope 3.92e+00 4.43e+00pvalue 1.91e-11 1.82e-12 GSM1616756_Pool_4_Reif-Hilscher_8-2-2012.CEL.gz GSM1616757_Pool_4wdh_Reif-Hilscher_9-2-2012.CEL.gzslope 3.95e+00 3.94e+00pvalue
Drawing:
> SampleNames [1] "GSM1616746" "GSM1616747" "GSM1616748" "GSM1616749" "GSM1616750" "GSM1616751" "GSM1616752" "GSM1616753" "GSM1616754" "GSM1616755"[11] "GSM1616756" "GSM1616757"n.sample = length(AffyBatch$sample)cols = rainbow(n.sample)plotAffyRNAdeg(RNAdeg,cols= cols)legend("topleft",legend=SampleNames,col= cols,lty=1,box.lty=0,bg=NA)box()
Note: The parallel lines of each chip result indicate that the experimental processing is balanced and consistent. If there is a large difference between a certain chip and other chips, it is necessary to pay attention to whether there is any problem.
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