It is clear that miRNA are informative molecules for cancer diagnosis, and there is a desire for non-invasive tests. It is also clear that NGS is a real progress. However, the known advantages of miRNA NGS vs microarray are not important for my study, as I do not want to discover new miRNAs or isoforms. I want just to discriminate, with the highest possible accuracy, between cancer and normal, using advanced Artificial Intelligence (AI) methods. Prelimiary results suggest that microrna data are better than NGS. Moreover, microarray profiling is cheaper. Searching the literature, I found some papers corroborationg this idea: microarray is a better choice if you are interested in miRNA cuantification. What is your opinion? Thank you!
Hi,
According to studies, microarrays are highly sensitive and perform equivalent to NGS in terms of reproducibility and relative ratio .quantification,
But personally i would suggest using NGS if you have a large amount of data for quantification.
Hope it was helpful.
Thank you Nooman. Can you develop a little bit your suggestion? If microarray is good for quantification, and is also cheaper and gerates much smaller files, it is not very clear why to prffer NGS for large amount of data. This will just increase the costs and the size of the files, with all the related problems (e.g., transfering the files).
Thanks again!
In general the performance and suitable applications for NGS have been grossly oversold.
In functional biology and clinical orientated experiments the technical reproducibility of short-read seq is substantially lower than an array (for long RNAS). In addition, short-read seq misses about 50% of the tissue transcriptome (mainly lncRNAs - see our comments on this issue in this article (more coming later this year)Article A coding and non-coding transcriptomic perspective on the ge...
However, for miRNAs the situation is different. In general there is only 1 probe design per miRNA (for obvious reasons) and thus the specificity of the array can't approach the same levels as it can for longer RNAs. The technical reproducibility is likely to still be high though - just that you don't have the same level of assurance that the RNA species hybridising is actually what you think it is.
While many are rushing out lots of miRNA array data, I'm still comparing several platforms to evaluate specificity. In this sense, sequencing of small RNAs might be a good approach. If you are interested in pre- or pri- then an array with its more complete cDNA library formation step will still win through.
Thank you James! I will also follow the link you gave above. I am interested only in miRNA quantification for discrimnating between cancer and normal. I am aware about the background problem and the saturation problem of microarray. For the background correction there are well developed algorithms, and saturation seem to affect all samples in the same way, and so, it is not a big problem. Concerning miRNA NGS, I guess that the problems come from adaptors and the PCR amplification. Illumina recently announced a new technology, where adaptors ligation is not required anymore. But, even if both microarray and NGS could perform equally well, NGS comes with other problems like huge files, and, as far as I know, one cannot measure only a miRNA subset, as is possible in microarray. Considering that probably, only about 100 miRNAs are relevant in cancer diagnosis, NGS looks to complicated and costly, for the same (or lower discrimantion performance).
Hi
Technically in both cases u have to take few sizable number of miles and validate by qrtpcr.but microarray is better for relative count than Ngs as latter need to be assembled on reference database and based of coverage read length u will get rfpk values.but in microarray directly u will end up getting the relative log levels,just not novel mirs!
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