ADD appendix for the meta-analysis stuff
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@ -14,6 +14,7 @@
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\usepackage{graphicx}
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\usepackage{graphicx}
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\usepackage{subcaption}
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\usepackage{subcaption}
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\usepackage{nth}
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\usepackage{nth}
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\usepackage{hyperref} % must be before cleveref
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\usepackage[capitalize]{cleveref}
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\usepackage[capitalize]{cleveref}
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\usepackage[version=4]{mhchem}
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\usepackage[version=4]{mhchem}
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\usepackage{pgfgantt}
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\usepackage{pgfgantt}
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@ -160,6 +161,7 @@
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\newacronym{zfn}{ZFN}{zinc-finger nuclease}
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\newacronym{zfn}{ZFN}{zinc-finger nuclease}
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\newacronym{talen}{TALEN}{transcription activator-like effector nuclease}
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\newacronym{talen}{TALEN}{transcription activator-like effector nuclease}
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\newacronym{qbd}{QbD}{quality-by-design}
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\newacronym{qbd}{QbD}{quality-by-design}
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\newacronym{aws}{AWS}{amazon web services}
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
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% SI units for uber nerds
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% SI units for uber nerds
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@ -1583,18 +1585,6 @@ that were extrapolated from the standard curve were left unchanged.
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\subsection{data aggregation and meta-analysis}
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\subsection{data aggregation and meta-analysis}
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% TODO explain what the colors mean
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\begin{figure*}[ht!]
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\begingroup
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\includegraphics{../figures/metaanalysis.png}
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\endgroup
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\caption[Meta-analysis overview]
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{Overview of strategy used for meta-analysis}
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\label{fig:meta_overview}
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\end{figure*}
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In order to perform meta-analysis on all experimental data generate using the
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In order to perform meta-analysis on all experimental data generate using the
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\gls{dms} system, we developed a program to curate and aggregate the raw
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\gls{dms} system, we developed a program to curate and aggregate the raw
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datafiles into a \gls{sql} database (\cref{fig:meta_overview}).
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datafiles into a \gls{sql} database (\cref{fig:meta_overview}).
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@ -1612,10 +1602,10 @@ experimental parameters such as the number of bead or \gls{dms} added.
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To aggregate the data in a database, we wrote a program using Python, R, and
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To aggregate the data in a database, we wrote a program using Python, R, and
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Docker which retrieved the data from its source location and inserted the data
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Docker which retrieved the data from its source location and inserted the data
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in a Postgres database. This program included checks to ensure the integrity of
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in a Postgres database (specifically Aurora implementation hosted on \gls{aws}).
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source data (for example, flagging entries which had a reagent whose
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This program included checks to ensure the integrity of source data (for
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manufacturing date was after the date the experiment started, which signifies a
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example, flagging entries which had a reagent whose manufacturing date was after
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human input error).
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the date the experiment started, which signifies a human input error).
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\subsection{statistical analysis}\label{sec:statistics}
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\subsection{statistical analysis}\label{sec:statistics}
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@ -4341,10 +4331,32 @@ expansion technology given that even in healthy donors, we observed the
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\onecolumn
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\onecolumn
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\clearpage
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\clearpage
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% TODO some people put appendices here....not sure if I need to
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\appendix
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\chapter{meta analysis database code}\label{sec:appendix_meta}
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\chapter{References}
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The code used to aggregate all experimental data was written primarily in
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\renewcommand{\section}[2]{} % noop the original bib section header
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Python, with a subprocess running R in a Docker container to handle the flow
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cytometry data (\cref{fig:meta_overview}). The Postgres database itself was
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hosted using \gls{aws} using their proprietary Aurora implementation.
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% TODO explain what the colors mean
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\begin{figure*}[ht!]
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\begingroup
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\includegraphics{../figures/metaanalysis.png}
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\endgroup
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\caption[Meta-analysis overview]
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{Overview of strategy used for meta-analysis}
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\label{fig:meta_overview}
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\end{figure*}
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The code is available here: \url{https://github.gatech.edu/ndwarshuis3/mdma}.
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\chapter{reaction kinetics code}
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\chapter{references}
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\renewcommand{\chapter}[2]{} % noop the original bib section header
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\bibliography{references}
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\bibliography{references}
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