Slides online at: slides.com
/dhimmel
/launch
Wednesday October 11, 2017
6:00–9:00 pm, Milkboy Philly
cognition
+
carcinoma
putting machine learning in the hands of cancer biologists
Cognoma Motto 1
The Cancer Genome Atlas
$425,000,000 project funded by the U.S. Government
33 types of cancer
- esophageal carcinoma
- glioblastoma multiforme
- head & neck squamous cell carcinoma
- kidney chromophobe
- kidney clear cell carcinoma
- kidney papillary cell carcinoma
- acute myeloid leukemia
- brain lower grade glioma
- liver hepatocellular carcinoma
- lung adenocarcinoma
- lung squamous cell carcinoma
- mesothelioma
- ovarian serous cystadenocarcinoma
- pancreatic adenocarcinoma
- pheochromocytoma & paraganglioma
- prostate adenocarcinoma
- rectum adenocarcinoma
- sarcoma
- skin cutaneous melanoma
- stomach adenocarcinoma
- testicular germ cell tumor
- thyroid carcinoma
- thymoma
- uterine corpus endometrioid carcinoma
- uterine carcinosarcoma
- uveal melanoma
machine learning
Predicting cancer mutations from gene expression
Using public domain TCGA data
(from Xena Browser)
7,306 samples
20,468 genes with expression
RNA-Seq
21,960 genes with mutation.
Sequencing
covariates
elastic net logistic regression
Precision Oncology
"the science of ensuring that a patient's treatment is specifically designed and targeted for their unique form of cancer"
everyone learns something new
Cognoma Motto 2
Tonight makes 27!
Pull requests model for contribution
Contribution per user by GitHub repository
35+ contributors
Childhood Cancer Data Lab
- Cancer Data: Claire McLeod (@clairemcleod)
- Machine Learning: Patrick Miller (@patrick-miller), Ryan Velazquez (@rdvelazquez), Jesse Prestwood-Taylor (@jessept), Yichuan Liu (@yl565)
- Backend: Derek Goss (@dcgoss), Andrew Madonna (@awm33), Kurt Wheeler (@kurtwheeler)
- Frontend: Benjamin Dolly (@bdolly)
- Community: Karin Wolok (@KarinSpiderwoman)
- Wildcards: Daniel Himmelstein (@dhimmel), Gregory Way (@gwaygenomics), Casey Greene (@cgreene)