An estimate of industry-wide cost of NGS DNA sequencing can be found here: http://www.genome.gov/sequencingcosts/

For whole-genome sequencing, the cost stalled in the beginning of 2012. Because of lack of data for 2013, it cannot be known if the cost has kept falling. If NGS fails to deliver to break the 1K/genome cost barrier, I would bet that third-generation sequencing ("TGS") will succeed.

TGS can also scan an entire chromosome including long repeat sequences, which NGS cannot do today. This means that it will be possible to do research on genomic features that have been hidden before.

Rohan, there will never be enough human analysts. I think that IBM Watson provides the answer to this problem. Automating tasks to process all the information is not impossible with the technology that we have and are developing. (I am not advertising here on behalf of IBM though. You also have to double check that their estimates of cost efficiency and accuracy are correct because many companies have a tendency to polish such information in order to sell more and raise prices.)

I also wonder how data integrity will not be compromized now that computerization is leading to more storage of personal data. When DNA sequencing has become cheap, that will add another issue to solve.

I agree with Rohan,

While costs are very important, analytic challenges are even more daunting obstacles.

Some of the big challenges that remain

- Differentiating between true variation and technical sequencing errors

- Differentiating between benign variations (the vast majority) and disease-causing mutations (the vast minority)

- Interpreting the data linking variations to disease.

- Obtaining high quality clinical data (phenotypes) for large numbers of patients.

Major advances in these areas are needed. Such advances will make genome studies more valuable at any cost.