Price War Between Sequencers Continues

Elilene Zimmerman at CNNMoney writes:

Entrepreneurs and scientists are pursuing an even more dramatic medical breakthrough: The ability to sequence an entire human genome for around that same $100 price tag. That goal remains a few years away, but the obstacles are falling fast.

Sequencing is a way of "reading" DNA molecules -- two strands twisted together to form that famous double helix. The entire human genome contains roughly 3 billion molecular base pairs, which researchers study to find variations that might play a role in the development of diseases. Right now it typically costs $1,000 to $4,000 to map out an individual's genome. (Specialized sequencing -- for, say, a cancer patient -- often costs more.) 

A lot of great things can be achieved by embracing a "cheaper, better, faster" approach but it seems that too much attention is paid to the cost per genome sequenced.  The price tag is a neatly packaged quantitative measure that's easily quotable, but it doesn't convey the whole story.

What people actually using the "$1000 genome" data will tell you, from experience, is that cheaper genomes are not necessarily better. 

For instance, a lot of variables can be tweaked to reduce "price per genome" to yield market-beating prices but delivering sub-standard data quality (I don't mean that it's poor quality data, just data that doesn't meet the standards of what's current in research at the time).  For instance:

Right now [Ion Torrent] can sequence the exome -- the 1 percent of the genome we know how to interpret -- for $500. "In three months, we'll be able to do one entire human genome for $1,000," predicts Rothberg, whose first company, 454 Life Sciences, was the one that sequenced James Watson's genome.

A $500 exome sounds great, but how much data is delivered on each position within all the genes?  Probably enough to genotype normal DNA but if you're analyzing a cancer tumour I'd bet you want to spend more on data that gives a more detail perspective (for various reasons).  If that's the case, a $500 exome might not give you the depth of information really needed to interpret what's gone wrong within the tumour.

Moral of the story: Don't go by cost alone.  Sometimes the cheapest data ends up costing the most in terms of lost opportunities.