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Practical And Efficient Searching In Proteomics: A Cross Engine Comparison

Submited on: 25 Apr 2013 09:23:12 AM GMT
Published on: 01 Oct 2013 07:20:48 AM GMT

I recommend this paper to publish in webmed central plus. The manuscript is concise and well written. It require minor formating as per journal requirement. 

 

 
Posted by Anonymous reviewer on 06 Sep 2013 04:36:14 PM GMT

The manuscript entitled: “Practical and efficient searching in proteomics: A cross engine comparison” by Joao A. Paulo provides useful insights into the bioinformatics analysis of mass spec data using multiple search engines. The results obtained are justified based on the methods used. Also, it has been written well, with figures and tables being easy to follow. However, the study is not a groundbreaking discovery in proteomics or bioinformatics. But, it will surely be helpful to many researchers to follow the recommendations of this study in better analysis of mass spec data.

I found few issues that need to be addressed before it is considered for publication. There is no statistical analysis of the results obtained from the searches using the three engines. Most of the results are shown by Vein diagrams with absolute numbers and % values. No attempts have been made to determine if the number of peptides/proteins identified by different engines (Fig 1 and 2) is significantly different. A cumulative hypergeometric test of the number of peptides/proteins identified by between engines can reveal that information and hence I suggest the author to provide that in the figures.  Regarding Fig 3, the author needs to show if there is a significant difference in the number of additional peptides compared to the number of additional proteins being identified by different combined runs. I see from the line graphs that the number of additional proteins varies relatively more than that of the proteins after 2 or 3 combined runs. Hence, it is essential to know if the data between the two (peptides vs. proteins) are significantly different after 2/3 runs (which is the main result of this paper). With these modifications, I will strongly recommend publication of this work.

  

 
Posted by Dr. Susanta K Behura on 04 Sep 2013 03:59:37 PM GMT

This paper is an outstanding one because the authors put their  work inside this very specialized field and the results were robust because the data show that  using multiple search engines can expand the number of identified proteins  and validate protein identifications.

The paper also made the  analysis of more than one technical replicates and it  can substantially expand protein identifications.

By performing database searching with different engines and performing technical repeats, information could be extrated from a dataset. They also showed that this has not required addtional sample preparation and effectively utilizes research time and effort.

 

 

 
Posted by Prof. Valcinir Bedin on 31 Aug 2013 08:15:36 PM GMT

Overall the manuscript is well written and acceptable for publication with minor additions suggested below. 

1. Why the authors have chosen these particular search engines for comparision? 

2. please explain how the data was extracted from a collected data set by what insilico methods and how?

 

 
Posted by Dr. MNV Prasad Gajula on 27 Aug 2013 07:34:23 AM GMT

This is an interesting study that aimed to the overlap among the identifications as determined by each algorithm. Some points that are important to be raised are listed below:

 

  • I suggest the authors to add a statistical analysis topic in Method.
  • Discussion is well written, however, I suggest to mention the clinical implication of the new finding.
  • The study’s limitation is also worth to be cited.
  • The conclusion should be shorter and only briefly respond to the aim of the study.

 
Posted by Anonymous reviewer on 26 Aug 2013 04:31:24 PM GMT