‼️Why do we say that #methodsmatter?

Here’s a telling example.

Two very recent studies asked the exact same cancer #immunotherapy prediction question, on the exact same dataset.

They reached contradictory conclusions.

Why?

Slight changes in the #Bioinformatics methods used👇 https://twitter.com/NCIEytanRuppin/status/1610202233521438721

The changes are:
1.analyze data per cancer type vs. pan-cancer
2.use cutoff of 0.2 vs. 0.1 for calling a copy number alteration

The contradictory conclusions are:
1.aneuploidy score (AS) is not predictive of immunotherapy response
2.a new metric is predictive &amp; outperforms AS

Here’s links to the two studies, Spurr et al was published in November 2022 &amp; Cheng et al was posted on biorxiv in December 2022

https://www.nature.com/articles/s41588-022-01235-4

https://www.biorxiv.org/content/10.1101/2022.12.28.522101v1

This example is conceptually representative for some of the core principles that define #Bioinformatics #DataScience.

Minor changes in methods or statistical frameworks used can qualitatively change entire narratives.

Choice of thresholds is important

Reproducibility matters‼️

Why do we say that methods matter in Bioinformatics? An immunotherapy example