Choosing between microarray and RNA-seq for gene expression studies and more?

Nowadays, RNA-seq is not costly. You can compare the cost between these two. Further, RNA-seq is a faster and less laborious approach than microarray. As you mentioned, RNA-seq is the best option for gene expression profiling. 

I have the same opinion as you, but I want to be less or to a certain extent, not biased. Since the microarray technology still exists and not obsolete, I believe it is still relevant to many research.  I haven't used microarray but I have used RNA-seq. However, I saw a recent paper that microarray is better in gene expression analysis than RNA-seq, whereas RNA-seq is better in detecting alternative splicing, genotyping, etc. What are your thoughts?

Yes, it is. It has widely been used in drug discovery and diagnostics, however metagenomics is replacing with arrays for diagnostics. The advantages of RNA-Seq over microarray in transcriptome profiling were clearly explained in the abstract of the plos paper that you have sent its link. Microarray relys on a pre-designed complement sequence detection probe, hence it is no able to detect all differentially expressed genes. Moreover, RNA-Seq has several advantages over microarray in terms of cost, speed, accuracy and reproducibility. 

Although, RNA-Seq data accuracy depends upon several factors including quality of RNA and synthesized cDNA, and pipeline for data analysis which are crucial. 

As noted above RNA seq is dependent on high quality RNA and is becoming more cost effective.  It is a useful and sensitive tool for discovery.  However, it's value is critically linked to the data analysis, which can be costly and time consuming if performed thoroughly.  For example with alignment to multiple data bases. New microarrays from Affymetrix (now Thermo Fisher) that detect gene, exon and splice variant expression, along with lnc RNAs and that are designed using up to eight databases can be a useful and cost effective alternative to RNA-seq.  So I think there are two times when microarray may be recommended, 1) if the RNA integrity is compromised and 2) when your level of comfort using code for analysis of RNA-seq is not high.

Thanks for your opinion. Actually, I don't have any problem with your 2nd point. But with 1st point, it can be error-prone depending on the person who is handling it. How different is it if you use same RNA samples to microarray and RNA-seq? Do you mean, I can worry less about the integrity of my sample when I use microarray?

The RNA-seq blog contains information that can be valuable. Now I am thinking, how long will microarray technology stay with us until NGS completely takes over?

I am an NGS guy, my scientist's eyes were open in the advent of NGS technology, so I am really for it. I am expecting someone to comment here and make an argument for microarray so I won't be biased.

There are also several things I don't like about microarray, (1) flexibility, (2) throughput compared to NGS, (3) using a greater number of sample volume compared to NGS.

RNA-Seq is a powerful tool if you're trying to detect novel transcripts/splice forms, go on an unbiased "fishing trip" for genes/biomarkers, detect extremely rare transcripts, or look at changes in transcript abundance that occur over a very wide dynamic range. 

However, if you're interested in studying the expression of a known panel of transcripts and none of them are expressed at an extremely high or low level, a well-designed microarray will work just as well and cost less. Microarrays can be used for most of the same experiments as targeted PCR primer sets for RNA-Seq.

RNA-Seq is a better approach than microarray for all application. RNA-Seq is cost effective. it provides an opportunity for discovery of novel transcripts. RNA-seq has better dynamic range than microarray. Strand information can be resolved at better efficiency and accuracy. RNA-Seq is more quantitative than microarray.  People may be still using but for exploratory research RNA-Seq is better.

I'd agree with Jennifer Hardee, that statement describes accurately the current state of things. Still, after dealing with both microarray and RNA-Seq-based research over the period of 15 years, I'd recommend RNA-Seq going forward, to make the results of your today's experiments more insightful for years to come.

All the above are true. 

RNA-seq then. Thanks for your answers. In the beginning, I am already for RNA-seq. Just looking for someone who can woo me out of it. Oh well. Thanks!

I believe RNA seq is better if you have the platform to do it. Obviously, microarrays are good enough if you choose those with best characteristics.

I think you should adjust your answer as per the research question and availability of resources. And, of course, availability of expertise to analyse and interpret data. Both techniques are good and have equal publishability value. I, however, think that RNA-seq has a slight edge over microarrays in terms of rubustness of the results.