Spending millions of $, Grail created a TCGA-like study to systematically answer the following:

What is the best cell-free DNA method to detect cancer from blood?

17 things we learned.🧵🩸 1. This study was composed of three phases, and today we will only discuss the first phase.

The goal of this phase is to answer which type of assay might give us the most insightful features to detect cancer - methylation, targeted-DNA-seq, or whole genome seq.

A lot of Machine Learning (ML) I learned during my Ph.D. was from youtube. I didn't have a guide to do this effectively and thus here it is:

A complete guide to studying ML from youtube: 13 best and most recent ML courses available on YouTube. 👩‍🏫🧵⤵️ We will start with "Stanford CS229: Machine Learning" by Andrew Ng to start and learn the following ML concepts:

Linear & Logistic Regression,
Naive Bayes, SVMs, Kernels
Decision Trees, Introduction to Neural Networks
Debugging ML Models.
youtube.com/playlist?list=…

I curated a list of 28 common issues one faces while using machine learning for biomedicine research and using different kinds of omics data. I also provided guides on how to best overcome them. 🍉🧵👇 I will cover these issues and how to address them using the following 8 studies.

We will start with the five pitfalls that arise when applying supervised ML models in genetics and genomics and how to best navigate through them.
nature.com/articles/s4157…

Using big data in healthcare. Here are 10 educational resources for anyone interested in building skills to analyze big data in healthcare.

Ranging from introductory to advanced, this includes courses, youtube channels, papers & online books.🧵🥑👇 We will start with a bioinfo course covering standard bioinfo to utilizing bulk/single-cell omics, big screens, precision oncology, & immunotherapy (Chp 19-26). @XShirleyLiu @joshuastarmer @tangming2005 @getz_lab @twang5

Recommend for folks using omics.
liulab-dfci.github.io/bioinfo-combio/

Our understanding of the immune system is quickly growing.

11 resources (videos and papers) covering the fundamentals and computational tools available to study the immune system. 🧵👇🔬🤒 Before we go on to learn the computational tools to quantify and measure the immune system, Let's start with a 15 mins visual overview of the fundamentals of the immune system.

Interested in aging and cancer. I did a year of literature survey on this.

Here is my list of 20 key open questions and challenges to better understand the interplay between aging and cancer. A thread 🧵👇 The presence of mutated clones in aging but otherwise healthy tissues has blurred the frontier between noncancer and cancer clones.

Why the clones that accumulate with age do not generate cancers?

Methods & data available to you are your thinking tools. While I learned the methods in my classes, I wish I knew various data available to me.

10 resources to learn almost all the big data resources available in cancer research. 🧵👇 First is my and @PengJiang20 collection of all the big data resources (data projects, data hosts, web analysis) in cancer research. (Review resulting from this: tinyurl.com/mrxpjaad) docs.google.com/spreadsheets/d…

Large-scale public data reuse to model immunotherapy response and resistance.
genomemedicine.biomedcentral.com/articles/10.11… Number of immune checkpoint blockade (ICB) clinical trials with patient tumor omics available for biomarker identification are increasing exponentially (Here's a list from this work).