11–20 of 41 posts
I am all for them trying though. I just don't think we are at a point where we can make a good diagnosis/conclusion yet.
This is border line academic imperialism. The founders seem to think that software engineering and data science applied to biological data will provide insight that traditional biology has not found. Unneccessary screening from a single dimension (genome) is only going to misguide patients into oppurtunistic drug companies and non-FDA approved remedies. We are still unsure of the nature/nuture problem. What if the en…
We don't know what we don't know. Yes, we know that certain genes can contribute towards cancer. However, that doesn't mean you will develop it. You could have a torrent of SNPs underneath BRCA1 but never develop breast cancer.
The last comment I'll make (not to be a naysayer) but it's naive to approach the solution as if it's black and white. Biology is super messy. The data is often not clean. Sequencers do get it wrong (albeit not often) and the bioinformatics is not a perfect science. People looking at the field from the outside should approach it with healthy caution.
It's somewhat the equivalent of saying that, in theory it's easy to launch a rocket into orbit. You have a concentration of reaction mass, you ignite it, it propels you to space. In reality, it's obviously infinitely more complex, much like genetics.
"Color has developed a next-generation sequencing based test for hereditary cancer. This test analyzes 30 genes associated with increased risk to develop breast, ovarian, colorectal, melanoma, pancreatic, prostate, stomach, and uterine cancers... The assay has a high degree of analytical validity for the detection of single nucleotide variants, small insertions and deletions (indels), and larger deletions and duplications (copy number variants, or CNVs)."
So not micro-arrays like 23andMe that test for SNPs ($99?), but not full genome sequencing either (~$1,000?); but specific sequencing for the sites of these genomic regions of those 30 genes.
Wet Lab sequencing method: "Specifically, it includes target enrichment by Agilent’s SureSelect method (v1.7) and sequencing by Illumina’s NextSeq 500 (paired-end 150bp, High Output kit)"; Unanswered question, are they doing the sequencing in-house or using a facility somewhere else?
Computational method: "The bioinformatics pipeline was built using well-established algorithms such as BWA-MEM, SAMtools, Picard and GATK. CNVs are detected using dedicated internally developed algorithms for read depth analysis and split-read alignment detection."
So basically perform the standard genome assembly, alignment with human reference genome of your partial assembly, and then identify what variant of these 30 genes the patient sample has; plus a special sauce for counting the number of specific bp repeats, due to in-del events, this is not something I am not too familiar, but presumably the number of a specific k-mer repeats you have in these genes of interest might correlate to a specific type of cancer? (would love to hear someone who is an expert in this field their opinion).
"These [30] genes are APC, ATM, BAP1, BARD1, BMPR1A, BRCA1,BRCA2, BRIP1, CDH1, CDK4, CDKN2A (p14ARF and p16INK4a), CHEK2, EPCAM, GREM1, MITF, MLH1, MSH2, MSH6, MUTYH, NBN, PALB2, PMS2, POLD1, POLE, PTEN, RAD51C, RAD51D, SMAD4, STK11, and TP53". (You can follow up by searching them here, e.g., http://www.genecards.org/cgi-bin/carddisp.pl?gene=BRCA2&keyw...).
Also interesting to note, since it's clinical, each of their test has to be verified by a certified "genetics counselor" and also meet lots of clinical standards.
There are already companies that do this... Today they are called innovators, tomorrow they'll be called money-grubbing, unethical, anti-FDA maniacs for do the same thing.
This is border line academic imperialism. The founders seem to think that software engineering and data science applied to biological data will provide insight that traditional biology has not found. Unneccessary screening from a single dimension (genome) is only going to misguide patients into oppurtunistic drug companies and non-FDA approved remedies. We are still unsure of the nature/nuture problem. What if the en…
Elad started his career with a PhD in cancer biology prior to starting the mobile team at Google, so I don't think "academic imperialism" is an accurate descriptor. I think you'll see more people with these hybrid skills over time. They take years to develop, though. If we want advancement in medicine, can we really do it without deep collaboration between biology and computer science? If so, isn't Color Genomics a m…
There's an entire field for that already, it's called bioinformatics.
Here's their white-paper on their testing methodology: https://s3.amazonaws.com/color-static-prod/pdfs/validationWh... "Color has developed a next-generation sequencing based test for hereditary cancer. This test analyzes 30 genes associated with increased risk to develop breast, ovarian, colorectal, melanoma, pancreatic, prostate, stomach, and uterine cancers... The assay has a high degree of analytical validity for…
This is border line academic imperialism. The founders seem to think that software engineering and data science applied to biological data will provide insight that traditional biology has not found. Unneccessary screening from a single dimension (genome) is only going to misguide patients into oppurtunistic drug companies and non-FDA approved remedies. We are still unsure of the nature/nuture problem. What if the en…
Sure, they are concentrating on one of the many aspects of human biology but as long as their findings are mere recommendations to get tested more often etc based on the potential genetic predisposition I don't see anything wrong with that.
As far as the article is concerned - I'd be very cautious going into the "share your dna report with your employer" (or anyone else for that matter) territory for a variety of reasons.
This is border line academic imperialism. The founders seem to think that software engineering and data science applied to biological data will provide insight that traditional biology has not found. Unneccessary screening from a single dimension (genome) is only going to misguide patients into oppurtunistic drug companies and non-FDA approved remedies. We are still unsure of the nature/nuture problem. What if the en…
Here's their white-paper on their testing methodology: https://s3.amazonaws.com/color-static-prod/pdfs/validationWh... "Color has developed a next-generation sequencing based test for hereditary cancer. This test analyzes 30 genes associated with increased risk to develop breast, ovarian, colorectal, melanoma, pancreatic, prostate, stomach, and uterine cancers... The assay has a high degree of analytical validity for…
Whole genome is not controlled enough to meet clinical standards.