Wanted to put out a brief thread on calculating tumor mutation burden because few papers explain how they do this, and I suspect most are not calculating it accurately. Mutation burden is typically expressed as mutations per megabase.
To calculate the numerator, first and foremost, you need a high quality set of mutation calls. Most studies meet this [bare minimum] standard, however, they fail to consider…
You must also define a cutoff for clonality. If you take the same sample and sequence it to 10X, 100X, 1000X, and 10000X coverage, you will find more mutations with more coverage b/c you pick up more subclonal mutations.
I typically count mutations that are predicted to be in greater than 50% of tumor cells. This is because we are ordinarily powered to detect mutations at this threshold in most samples we sequence. The biological questions being asked might factor into this decision, too.
To calculate the denominator, one must know how much sequencing footprint has sufficient coverage to call a mutation. Most labs just divide mutation count by the footprint of their baits – but can you really detect a mutation at 100% of sites?
In our lab, we ask: What threshold of coverage is needed to detect a mutation? Answer: depends on tumor cellularity and the variant caller. After determining an appropriate threshold, we use the Footprints software to count the number of basepairs that meet this requirement.
By the way, here is a video of how to run Footprints: . Described here: biorxiv.org/content/10.110…
To emphasize the importance of the denominator calculation, we recently downloaded tumor exomes from various studies. Our ability to detect mutations varied dramatically depending on overall coverage, variability in coverage, and tumor cellularity. Image
Overall, the considerations described above would permit more standardized and accurate measurements of tumor mutation burden (TMB) – a clinically actionable variable if measured correctly.

• • •

Missing some Tweet in this thread? You can try to force a refresh
 

Keep Current with Hunter Shain

Hunter Shain Profile picture

Stay in touch and get notified when new unrolls are available from this author!

Read all threads

This Thread may be Removed Anytime!

PDF

Twitter may remove this content at anytime! Save it as PDF for later use!

Try unrolling a thread yourself!

how to unroll video
  1. Follow @ThreadReaderApp to mention us!

  2. From a Twitter thread mention us with a keyword "unroll"
@threadreaderapp unroll

Practice here first or read more on our help page!

More from @ShainLab

3 Mar
I am thrilled to post our preprint, “The genomic landscapes of individual melanocytes from human skin” on BioRxiv. biorxiv.org/content/10.110…
Feedback is welcome. Here is a summary of what we found… (1/15)
Some background… @imartincorena, Philip Jones, and Peter Campbell deep sequenced “normal” skin, showing that keratinocytes are riddled with mutations. However, similar studies in melanocytes would require the ability to genotype individual cells. (2/15) Image
So we pioneered an experimental and bioinformatic workflow to call mutations in individual melanocytes with extreme sensitivity and specificity (just trust me or read the preprint because I can’t fit these details in 280 characters). (3/15)
Read 15 tweets

Did Thread Reader help you today?

Support us! We are indie developers!


This site is made by just two indie developers on a laptop doing marketing, support and development! Read more about the story.

Become a Premium Member ($3/month or $30/year) and get exclusive features!

Become Premium

Too expensive? Make a small donation by buying us coffee ($5) or help with server cost ($10)

Donate via Paypal Become our Patreon

Thank you for your support!

Follow Us on Twitter!