bioc-issue-bot
commented
6 years ago Dear @langholee ,
I could not find a DESCRIPTION file in the default branch of the GitHub repository at https://github.com/langholee/XINA . This repository should contain an R package.
I am closing this issue. Please try again with a new issue.
Hello,
I am Lang and want to submit XINA to Bioconductor. I checked XINA by using R CMD Check and Bioccheck and found no warnings and no errors. Of course, I know these are just minimum requirements. Please consider XINA to add to the Bioconductor repository. I attached the abstract part of XINA manuscript that I submitted to Journal of Proteome Research.
XINA ABSTRACT Quantitative proteomics experiments, using for instance isobaric tandem mass tagging approaches, are conducive to measuring changes in protein abundance over multiple time points in response to one or more conditions or stimulations. The aim is often to determine which proteins exhibit similar patterns within and across experimental conditions, since proteins with co-abundance patterns may have common molecular functions related to a given stimulation. In order to facilitate identification and analyses of co-abundance patterns within and across conditions, we previously developed a software inspired by the isobaric mass tagging method itself. Specifically, multiple datasets are tagged in silico and combined for subsequent subgrouping into multiple clusters within a single output depicting the variation across all conditions; converting a typical inter-dataset comparison into an intra-dataset comparison. An updated version of our software, XINA, not only extracts co-abundance profiles within and across experiments, but also incorporates protein-protein interaction databases and integrative resources such as KEGG to infer interactors and molecular functions, respectively, and produces user-friendly graphical outputs. In this report we compare the kinetics profiles of >5,600 unique proteins derived from three macrophage cell culture experiments and demonstrate through intuitive visualizations that XINA identifies key regulators of macrophage activation via their co-abundance patterns.
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