Wet-lab, dry-lab or moist-lab

Wet-lab: your traditional research lab with lots going on at the bench (often collaborating with dry-labs).

Dry-lab: A computational or mathematical lab focusing on analysis of other peoples data (sometimes collaborating with dry-labs).

Moist-lab: the new style of lab with both wet- and dry-staff, working together with some post-docs now being truly multi-functional developing methods in both environments.

What do you call a moist-lab worker?

Florian Markowetz is a junior group leader at the Cambridge Institute and gave an excellent seminar yesterday about his groups use of computational methods for understanding cancer evolution; and image processing for improved analysis of tissue sections. Florian is one of a relatively rare breed of computational lab heads and is hiring his own wet-lab staff. His seminar was the first place I heard the term "moist-lab".

 

The rise of the computational research assistant: over the last year or two I have noticed that many wet-lab PI's are hiring a different sort of Research Assistant into their labs: a computational RA. This it is not a surprise given the work those groups are doing, but is a recent change.

Most labs have at least one research assistant, officer, etc., who generally assists in the running of a lab, may often be responsible for maintaining lab stocks and things like cell culture. Research Assistants help labs run smoothly and are often the longer-term members of a group and/or institute. Until recently nearly all Research Assistants worked in the lab and had lab based skills.

But with the amount of data coming out of genomics technologies like microarrays and sequencing increasing so fast a group can quickly become overwhelmed with the volume of data. Simply keeping track of files can be tough.

Hence the rise of the computational RA and the emergence of moist-labs.

How many samples can you run on an Illumina Sequencer

Illumina now have a sequencer for almost every need: S, M, L & XL. There is a helpful table on their website that give instrument specs and an application-by-application estimate of sample numbers that can be sequenced in run:

Interestingly gene panel's don't appear on HiSeq 2500. We've used this for targeted sequencing to get phenomenal depth on large numbers of samples to look into heterogeneity in cancer. I'd expect anyone wanting to look deeply into populations would benefit in the same way.

There is also a comparison tool on their website to help you find the right sequencer for your lab:  helpful table on their website: interested in RNA-seq for DGE and ChIP-seq in cancer genomics? Here are the results:

One of our bases is missing: where's the G in NextSeq chemistry

Illumina surprised pretty much everyone with their latest SBS chemistry. I was at an Illumina meeting last week where it was discussed at some length, with many in the audience concerned about possible new error modes due to the drastic change compared to the four-colour SBS used in HiSeq and MiSeq.

I posted an explanation of how the two-colour chemistry works a couple of weeks ago and my initial thoughts remain the same: the chemistry is likely to be an important step forward and Illumina are unlikely to have released it without a lot of confidence in it. So do we need to be particularly concerned about the lack of G signal or the dual-flurophore approach used for A?

Help, my G is missing: argumentum ad ignorantiam, "absence of evidence is not evidence of absence" is the point of view most people seem to have come from. There is concern that a null signal is not the same as a nice bright green spot. But in discussing this with colleagues I was struck by the fact that twenty years ago the lack of signal was the basis for Sanger sequencing working at all. Take a look at the image below, you can read the sequence yourself:

 

GGTCCGCCACTTCCCGTTAGTC

 

Anyone who remembers, or actually performed, radioactive sequencing will know what I am talking about. All those lanes to interrogate, reading bases out to a mate while guided by a ruler down the autoradiograph. A genome felt like an impossibility. But the "missing" signal was not an issue, but rather the key to success. 75% of bases in each track had no signal, so what’s all the fuss over the missing G?

But what about comparisons to HiSeq SBS: We'll have to wait for academic groups to sequence larger sample numbers than Illumina have so far produced to get a real handle on how well the SBS chemistry's compare. For now most data is still going to come from four-colour SBS. But in the future who knows. Will two-colour SBS trickle down/across to other platforms? I'm certainly liking the simplification of hardware and looking forward to a more robust instrument. After all most of my groups Tweets are to say how long our queue is or that our HiSeq has broken.

I only ever did radioactive sequencing once during my third year at Uni, it was a two week long exercise, what with development of the autoradiograph, and I got a few hundred base pairs for my project. That was in 1995, nineteen years later and in two weeks an XTen system could generate 640 30x Human genomes.

A new tool for NGS run QC

We just published a paper describing the tool we use in my lab as the primary QC for all lanes of sequencing, we've used this tool on about 5000-6000 samples over th past 3-4 years.

Multi-genome alignment for quality control and contamination screening of next-generation sequencing data. Hadfield & Eldridge 2014

In designing the tool we aimed to produce something that gave us a fast, and computationally inexpensive, visual presentation of quality and yield. The tool is alignment-based and works on a 100,000 read sample of sequences and base quality scores extracted from a FASTQ file. Whilst we run MGA at the lane level it could be run on any number of FASTQ files e.g. every library in a multiplexed pool to determine the quality/contamination of each

I'm hoping the next step will be to release this as an App on BaseSpace.

How does MGA work: The MGA tool primarily displays yield, as counts of reads (clusters) and quality (error rate) with additional information to help identify lanes/libraries that may need additional troubleshooting. In figure B from the paper below we presented a HiSeq 2000 flowcell with four good lanes and four not-so good. Before I describe the results can you guess which lanes might have problems?

Figure B from Hadfield & Eldridge 2014

The figure is meant to represent a flowcell with 8 lanes, and will display a single lane for a MiSeq run, or 4 lanes on a NextSeq 500!

Lanes 1-4 generated between 165-200M reads each. The green bar represents the genome of interest and error rate, these lanes are almost entirely Human as expected with very little "contamination" from other genomes (as repressented by yellow) or unmapped sequences (as represented by white).

Lanes 5-8 generated only 90-140M reads. There's lots of unmapped sequence (white) and also lots of adapter contamination (as represented by purple). Additionally lane 8 is almost entirely unmapped with almost the same number of reads coming from contaminants as from the genome of interest.

How do you get MGA: The paper was only published a couple of days ago but you can read it in provisional format at Frontiers in Genetics. You can also grab the software from https://github.com/crukci-bioinformatics/MGA.

Who won the Core Genomics Christmas Competition?

Congratulations to Tatiana Borodina who has won the Core Genomics Christmas competition and a free MiSeq run courtesy of Illumina. Special mentions to runners up Tim Forshew (Cambridge Institute) and Charles Warden (City of Hope) who were very close to Tatiana. And also to Thomas Rio Frio (Institut Curie) who was the only person to get all 6 baubles right.

MinION is almost here...

Breaking news: AGBT Feb 14th: David Jaffe from the Broad Institute is presenting a talk titled: “Assembly of Bacterial Genomes Using Long Nanopore Reads”. My assumption is that this is ONT, it may not be but see you there anyway.

HiSeq NextSeq 500

Onto the next new instrument from Illumina, the NextSeq 500, I've given a brief overview but covered the new chemistry in an earlier post.

Illumina helpfully provide the NextSeq 500 User guide on their website. There is a lot of interesting reading in it and I’ve picked out a few of my favourite bits. The datasheet also describes “streamlined Illumina sample preparation kits”, I’ve not looked to see what changes have been made yet but Keith Robison over at Omics Omics has a post which describes the new NeoPrep system from Illumina. This is Illumina's incarnation of the Advanced Liquid Logic technology they purchased last year; expect 16 DNA or RNA library preps per run using TruSeq and/or Nextera assays.

NextSeq 500's new chemistry described

NextSeq 500 uses a two-colour chemistry rather than the original four-colours. This makes a massive difference to the complexity of producing reagents, the instrumentation and the computation; all are effectively reduced by a factor of two. So how does it work?

HiSeq X Ten: only Human Genomes?

Today I thought I'd give my first impressions on what HiSeq X Ten might mean, the dust has certainly not settled and yesterday there was lots of buzz about the new instruments from Illumina (see the bottom of this post for a round up of news). I’ve been reading the HiSeq X Ten datasheet and a couple of things jump out as significant changes: run speed and output per flowcell.

Update: I'd also point readers to this post by Shawn Baker (CSO at AllSeq)  where he points out that Illumina are using a four year lifespan to get the $1000 genomes. We managed to keep our GAIIs for about 4 years, and HiSeq was only 2 when 2500 was announced. Hopefully X Ten can go the distance?

Illumina's christmas presents

JF did not disappoint at JPM: Jay Flatley announced both the HiSeq X Ten and NextSeq 500, two more instruments to add to HiSeq and MiSeq. HiSeq X Ten comes as ten “ultra-high throughput” sequencing instruments that together can generate 18Tb in three days, with 6B clusters per run! NextSeq 500 could be billed “the HiSeq in a MiSeq” and will complete a 300 cycle run in 30 hours, available now for $250,000. Both systems, which make use of flowcell innovations and major changes in SBS chemistry discussed below were covered in quite some detail by GenomeWeb.