cyttools Tutorial.Rmd

---
title: "cyttools Tutorial"
author: "Brian Capaldo"
date: "5/3/2017"
output: html_document
---

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## cyttools: Open source pipeline framework for cytometry data analysis

## Abstract

With the advent of mass cytometry and high parameter flow cytometry, cytometry data analysis, or cytomics, has entered the era of big data much like genomics did within the past decade. Learning from genomics is required to efficiently and effectively analyze the firehouse of data being made available. Desktop software is rapidly becoming overwhelmed by the glut of data and server based solutions are not accessible to every institution. Additionally, similar to genomics, cytomics, is constantly being inundated with new algorithms and analysis techniques that seek to answer similar questions, but with no standards as to how data is processed and results are returned, many of theses new techniques are slow to be implemented in ways for the majority of cytometrists to access and utilize. Towards this, we have developed cyttools, an open source pipeline framework for the analysis of cytomic data. cyttools seeks to provide a space for compiling all the analysis methods into one platform, easing use and implementation of the various tools, as well as incorporating new tools as they become available. cyttools is modeled after bedtools, a open source genomics toolkit developed to make interval analysis more accessible. Much like bedtools, cyttools utilizes a simple command line interface, however, cyttools uses the R and the Bioconductor project for the actual analysis, leveraging the vast wealth of cytomics tools currently available there. The importance of cyttools is that it will allow cytometrists without specialized training in computational biology to perform cutting edge analysis techniques by handling all necessary manipulations prior to the data being acted upon by the algorithm of choice, and stringing complicated, multistep analyses by creating a pipeline of cyttools commands.

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