Friday, October 13, 2017

iGenomX Riptide Kits Promise a Sea of Data

A theme for me in my six years on Starbase has been addressing the challenge of cost-effectively sequencing many small genomes.  While sequence generation bulk prices have plummeted, all-in library construction cost has tended to stubbornly resist dramatic change.  Large genome projects don't face quite such a pinch, but if you want to sequence thousands of bacteria, viruses or molecular biology constructs, paying many-fold more for getting a sequence into the box than you're paying to move it through the box ends up being a roadblock. Illumina's Nextera approach dropped prices a bit, but not really a sea change.  Various published protocols drop  costs further via reagent dilution, but these can suffer from variable library yield and an increased dependence on precise input DNA quantitation and balancing.  Even then, the supplied barcoding reagents for Nextera handle at most 384 samples, and that is only a relatively recent expansion from 96. I previously profiled seqWell's plexWell kits, which like Nextera use a transposase scheme but with modifications to enhance tolerance to input sample concentration variation.  plexWell also enables very high numbers of libraries, which better mates projects with large numbers of small genomes to sequencers with enormous data generation capabilities.  Now comes another entrant in the mass Illumina library generation space: iGenomX, which has reformatted their chemistry from a microdroplet mode intended for linked read generation to a 96-well plate format requiring no unusual hardware.

Wednesday, October 04, 2017

PacBio's Frankenpatent on Error Correction

Well, here we go again.  Pacific Biosciences launched yet another patent lawsuit towards Oxford Nanopore at the end of September, and already the hounds are baying for me to look at the patents -- which I've foolishly established a reputation of doing. I will remind readers that, to use a construction that exasperates my son, I have no memory of these topics being covered during the time I was in law school. (said construction also works for divinity school, seminary, yeshiva, dental school, military academy, etc). 

Sunday, October 01, 2017

Dispatches from CDC AMD Day 2017

I had the singular honor and pleasure of speaking this past Monday at the Center for Disease Control and Prevention's Advanced Molecular Detection(AMD) program's annual confab in Atlanta.  Just visiting the CDC campus was already a bit magical -- along with the Kennedy Space Center and Cold Spring Harbor it's one of mythical places of human exploration to me.  But to actually stand at the podium? Wow!

I've collected below a bunch of separate mental threads, many of which probably should be expanded out to a full post in the future.

Sunday, September 24, 2017

Why Is LISP So Rare in Bioinformatics?

LISP is one of the oldest computer languages and perhaps one of the most influential of the early ones.  Some of the other well-known Eisenhower era languages -- Fortran, COBOL and ALGOL, have certainly left their mark, but LISP and derivatives such as Scheme or Common LISP certainly carries more cachet among "serious" programmers.  COBOL has always been a bit of an easy joke and Fortran tends to mark you as old-school; use of APL (once a language of mine) would mark you as dangerously reactionary.  ALGOL begat Pascal and Modula II and clearly had impact on the C syntax family of languages (including bioinformatics mainstays Python, Perl and Java) As I'll detail below, learning LISP has embarrassingly ended up stuck seemingly permanently on my future plans queue.  But that's also because life never forced the issue:  while LISP has certainly been used in bioinformatics (as covered in a review from 2016 ) , its mindshare in the community would seem to be very minimal.

Monday, September 18, 2017

Teaching Biology Evidence: Old or New?

I've been toying over a week with writing something based on an interesting Twitter discussion started by Dr. Laura Williams (@MicroWavesSci) of Providence College pondering the best way to approach teaching molecular genetics (really, science in general) at the undergraduate level.  In particular, Professor Williams wondered about the dangers of branding various key experiments with the names of the experimenters, such as Hershey-Chase or Meselson-Stahl.  The risk she points out is that this can devolve into an exercise in memorizing names and dates without assimilating concepts, or conversely that some students will find the names more of a hindrance than a help.  I'm going to play a bit with this, but I do emphasize that for her this is reality and for me it is a hobby (or perhaps a retirement fantasy, if I should ever actually retire).  Or in other words, for the academic this is her industry but for this industrial scientist it is academic.

Tuesday, August 29, 2017

The Curse of Spammotation Lives!

High throughput sequencing of genomes is over twenty years old, which demanded the development of automated pipelines for annotating this data.  I've worked on such pipelines since the early 1990s, implementing them as a student and at two different corporate stops.  Indeed, we were reviewing results from my pipeline versus some of the other ones out there to see what can be done better.  And unfortunately, I've found infuriating problems with RefSeq entries annotated with NCBI's bacterial genome annotation pipeline.  Now I'm usually one to sing the praises of NCBI -- they are a key resource for biological research and they make available multiple spectacular public services freely to the entire world.  But I'm afraid this time I need to vent.

Tuesday, August 15, 2017

DNA vs. the Machine

Last week's news contained a story sure to raise eyebrows.  A group of computer security researchers from the University of Washington claimed to have demonstrated that they could hijack a computer via sequencing a carefully-constructed DNA fragment.  Visions of NextSeqs rampaging through the streets immediately sprung to mind.  The paper is interesting and has some useful warnings for the bioinformatics community, but certainly the news coverage has been strong on hype and alarmism.