Round-up May 23rd – July 11th


I’ve been away for a while, so a higher level catch-up below.


The FDA has introduced two new sets of guideline docs for NGS testing

1) how test developers could demonstrate the analytical validity of NGS tests for germline diseases

2) guidance on how they might establish the clinical validity of genetic variants gauged by such tests using public databases recognized by the agency

The reaction has not, in general, been positive, e.g.. ‘”They don’t know what they’re saying,” she said, adding that test developers already have good guidelines from CAP and NYSDOH. “What does the FDA think it’s going to add to this?” posited Bale, who is a founding member of the American College of Medical Genetics and Genomics, and an author on NGS standards issued by the group in 2013. “From a technical aspect, they are way in over their heads.”‘

The FDA are trying to distant these guidelines from their proposal to regulate Laboratory Developed Tests, but they’re not convincing many.

The French have launched a national $780m genomes project (cf $215 for the US’s Precision Medicine Initiative), “The first objective is to make France a leader among the countries already laying the groundwork for genomic medicine. Second, is to prepare for the integration of genomic medicine into the normal course of patient care in the country, which means sequencing about 235,000 genomes per year by 2020. And the third goal is to establish a national genomic medicine industry to serve as a source of innovation and economic growth.”

The NIH has a new data system for sharing of genomic data, including clinical data, and focused on cancer data:


“CMS Preliminary pricing plan would reduce payments for several molecular tests“:

InsideDNA will launch in the Fall a Google cloud service that allows users to plug and play various different bioinformatics tools, for e.g. variant calling, but also discovery tools:

Genos, a consumer genomics company arising out of the ashes of Complete Genomics, will give consumers a VCF of their exome, and put them in touch with genetic counsellors if requested. They will make their money by allowing researchers to ask users if they can pay to access their genetic data.

Illumina is looking to make big bucks of software, including variant interpretation:

IBM have partnered with the DVA, with Watson to recommend treatment options based on genetic analysis of veteran’s tumors:

Counsyl move into Oncology with a new business unit:

IDbyDNA, out of Mark Yandell’s lab, is still in stealth mode, but it is based on an exclusive license to the Taxonomer software, details of which were recently published. Taxonomer is a metagenomics tool to identify which pathogens are present.

Hortonworks, who focus on open and connected data platforms, is leading a Big Data/Spark/Hadoop open data consortium, involving Baylor, Mayo, and others:


The LawSeq project has been launched, which will look at: liability, quality of data and variant interpretation, privacy, and frameworks for research-clinical translation.

A study of consumer attitudes to WGS found a lot of heterogeneity, including that 38% of people would not pay for anything for actionable variants, 7% would pay more than $400, and that 3% would pay more than $1000.

Genomics helps enable precision medicine, but its also relevant in public health. The CDC has launched this new database on the relevance of genomics to public health, which will be updated at least weekly:

Scientists behind the “Human Genome Project – Write” published on some of their pilot project goals, and the overall vision:

Mount Sinai reports on using WES and RNA-Seq for tumor-normal analysis

A GenomeWeb write-up from some of the results presented at ASCO includes the report that Foundation’s panel test can be used to assess overall Tumor Mutational Burden. Some studies suggest that high TMB can give better response to therapy.

Craig Venter reports on deep sequencing of 10,000 genomes. One nugget: each genome contributes about ~8,500 novel variants.

A score based on several SNPs helps predict the age at which you start reading, which in turn predicts some socioeconomic outcomes: The score only helps predict ~2% of the variance, but will surely be an early example of whats to come…

A pilot study of 20 sick babies at CHEO identified genetic causes in 40% of them using the TruSightOne panel.

A three year Uganda based study will look for genetic markers that dictate TB and HIV progression in children across three countries: