Review for "AGOUTI: improving genome assembly and annotation using transcriptome data"

Completed on 1 Jun 2016 by Mihaela Pertea.

License: http://creativecommons.org/licenses/by/4.0/

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Comments to author

Author response is in blue.

In this revised version of the manuscript the authors present a better explanation of their algoirthm and make a more thorough evaluation of their approach by including one real data set, and a larger simulated data set. On all data sets tested AGOUTI performs better than its competitor. I am still not convinced from the data presented here that AGOUTI will improve the assembly after a good DNA scaffolder was applied, but I have no doubt that some users will find it useful for their genome assembly tasks.

Level of interest

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An article of limited interest .

Quality of written English

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Acceptable.

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Authors' response to reviews: (https://static-content.springer.com/openpeerreview/art%3A10.1186%2Fs13742-016-0136-3/13742_2016_136_AuthorComment_V2.pdf)