[anamax]

> That's why we write papers. Plain English can be more coherent than a pile of code.

"Plain english" doesn't analyze data - software does.

If the software is a mess, how likely is it that the "plain English" description is correct? How do you know? Why should anyone believe that the description is correct?

Code is truth.

[etal]

Right, which is why the novel parts should get more attention and undergo code review, which is the goal of the Bioinformatics Testing Consortium.

To be clear, I'm all for open science and even open notebooks where it's a good fit for the project. I just don't think a pile of single-use scripts is a sufficient replacement for a clear English description of the analysis workflow and the reasons for each step. If I can't understand how an analysis was done from the article itself and the documentation for any associated software, I would not trust the article. Including more code, particularly the code further down the Pareto curve of relevance to the final article, does not make the article more correct -- most journal articles are wrong or flawed in some way, even if the code works as advertized.