I posted my review verbatim, without any editing, and with the charge for the review laid out by the journal. Part of my goal was to provide some insight into why I was enthusiastic about Salmon, and why I reviewed it positively for publication.

Looking back on my review, I have a few thoughts - especially in light of Lior's hit piece and Rob et al's response.

First, it is always a pleasure reviewing software papers when you have used the tool for ages. My lab uses Salmon, trains people in running Salmon, and passes around blog posts and papers discussing Salmon results. I think we had been using Salmon for at least a year when I was asked to review the paper. So I was already pretty confident that Salmon performed well in general and I did not need to try to run it, evaluate it, etc.

Second, my review hit on a number of high points about Salmon: generally, that it was an important new tool of interest and that it was a significant improvement to the tried-and-tested Kallisto technique. More specifically, I felt that the GC bias correction was likely to be critical in the future (see esp the isoform switching observation!), and that the open-source license was an important aspect of the Salmon software. To my mind this meant that it warranted publication, a case I made succinctly but tried to make strongly.

Third, my review missed at least one very important aspect, which was the streaming nature of the Salmon implementation. The rebuttal covers this nicely...

Last, my review uses the term "pseudoalignment" and not "quasimapping." The distinction between these two terms is part of the brouhaha; but to my mind the basic idea of finding equivalence classes for reading mapping is pretty similar no matter what you call it, and it was clear (both from the citations to Kallisto and the discussion in the paper) that the core concept had been published as part of the Kallisto work. I don't think it matters what it's called - it's a good idea, I'm glad that there are multiple implementations that agree well with each other, and I think it was adequately, appropriately, and generously cited in the Salmon paper.

So, anyway, there are my thoughts. Yours welcome below!

(Before you comment, please do see the code of conduct for this blog - it's linked below. In particular, I place myself under no obligation to retain posted comments, and I will delete comments that are useless, or dishonest.)

--titus

Other articles

My Salmon review

Wed 16 August 2017
By C. Titus Brown

In science.

tags: salmon review

I was one of the reviewers of the Salmon paper by Patro et al., 2017, Salmon provides fast and bias-aware quantification of transcript expression. I was asked to review the paper on September 14, 2016, and submitted my review (or at least stopped getting reminders :) soon after October 20th.

The ...
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How to analyze, integrate, and model large volumes of biological data - some thoughts

Mon 15 May 2017
By C. Titus Brown

In science.

tags: ddd data integration

This blog post stems from notes I made for a 12 minute talk at the Oregon State Microbiome Initiative, which followed from some previous thinking about data integration on my part -- in particular, Physics ain't biology (and vice versa) and What to do with lots of (sequencing) data.

My ...
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A draft bit of text on open science communities

Fri 10 March 2017
By Anita De Waard and C. Titus Brown

In science.

tags: community TomorrowsUni

This is early draft text that Anita and I put together from a bunch of brainstorming done at the Imagining Tomorrow's University workshop. Comments welcome!

Communities are the fabric of open research, and serve as the basis for development and sharing of best practices, building effective open source tools ...
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Advancing metagenome classification and comparison by MinHash fingerprinting of IMG/M data sets.
Wed 01 March 2017
By Phillip T. Brooks, Jiarong Guo, Luiz Irber, C. Titus Brown

In science.

tags: sourmash minhash metagenomics proposal grant

This is our just-submitted proposal for the JGI-NERSC "Facilities Integrating Collaborations for User Science" call. Enjoy!
1. Brief description: (Limit 1 page)
Abstract: Sourmash is a command-line tool and Python library that calculates and compares MinHash signatures from sequence data. Sourmash "compare" and "gather" functionality enables comparison and characterization of signatures ...
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Request for Compute Infrastructure to Support the Data Intensive Biology Summer Institute for Sequence Analysis at UC Davis

Mon 20 February 2017
By Lisa Johnson Cohen

In science.

tags: xsede hpc dibsi

Note: we were just awarded this allocation on Jetstream for DIBSI. Huzzah!

Abstract:

Large datasets have become routine in biology. However, performing a computational analysis of a large dataset can be overwhelming, especially for novices. From June 18 to July 21, 2017 (30 days), the Lab for Data Intensive Biology ...
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My thoughts for "Imagining Tomorrow's University"

Wed 15 February 2017
By C. Titus Brown

In science.

tags: futureuni

So I've been invited to Imagining Tomorrow's University, and they have this series of questions they'd like me to answer.

(Note that you can follow the conversation at #TomorrowsUni on Twitter.)

Conveniently I already answered many of these questions in my "What is Open Science?" blog post ...
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Abstract: