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talk06-practices.tex
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talk06-practices.tex
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\documentclass[ignorenonframetext,]{beamer}
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% required for kable and kableExtra for R ----
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\title{R for bioinformatics, data wrangler practices}
\subtitle{HUST Bioinformatics course series}
\author{Wei-Hua Chen (CC BY-NC 4.0)}
\date{10 October, 2023}
\begin{document}
\frame{\titlepage}
\hypertarget{section-1-toc}{%
\section{section 1: TOC}\label{section-1-toc}}
\begin{frame}{前情提要}
\protect\hypertarget{ux524dux60c5ux63d0ux8981}{}
\begin{block}{pipe}
\protect\hypertarget{pipe}{}
\begin{itemize}
\tightlist
\item
\%\textgreater\%
\item
\%\$\%
\item
\%T\textgreater\%
\item
\%\textless\textgreater\%
\end{itemize}
\end{block}
\begin{block}{tidyr}
\protect\hypertarget{tidyr}{}
\begin{itemize}
\tightlist
\item
pivot\_longer()
\item
pivot\_wider()
\item
没有仔细讲的
\item
unite()
\item
separate()
\end{itemize}
\end{block}
\begin{block}{dplyr}
\protect\hypertarget{dplyr}{}
\begin{itemize}
\tightlist
\item
select()
\item
filter()
\item
mutate()
\item
summarise()
\item
arrange()
\item
group\_by() \ldots{}
\end{itemize}
\end{block}
\end{frame}
\begin{frame}{本次提要}
\protect\hypertarget{ux672cux6b21ux63d0ux8981}{}
\begin{enumerate}
\tightlist
\item
3个生信任务的R解决方案
\item
factors 的更多应用 (forcats)
\end{enumerate}
\end{frame}
\hypertarget{section-2-contents}{%
\section{section 2: contents}\label{section-2-contents}}
\begin{frame}{生信任务1 ： network analysis and visualisation (dplyr \&
some plot packages)}
\protect\hypertarget{ux751fux4fe1ux4efbux52a11-network-analysis-and-visualisation-dplyr-some-plot-packages}{}
protein-protein interaction data
\begin{block}{why PPI is important?}
\protect\hypertarget{why-ppi-is-important}{}
\begin{enumerate}
\tightlist
\item
most of the time, protein functions together with other proteins
(interactions)
\item
interacting partners tend to have similar functions (guilty by
association, can be used in gene annotation)
\end{enumerate}
\end{block}
\end{frame}
\begin{frame}{STRING database}
\protect\hypertarget{string-database}{}
\begin{enumerate}
\tightlist
\item
contains \textgreater2 billion interactions for 24.6 million proteins
in 5090 organisms (as of May 2021; ver 11.0b)
\item
contains:
\end{enumerate}
\begin{itemize}
\tightlist
\item
physical interaction
\item
genetic interactions
\item
gene co-occurrence (text-mining)
\item
transfers through orthologous relationships
\end{itemize}
\end{frame}
\begin{frame}{STRING is one of the most cited resources}
\protect\hypertarget{string-is-one-of-the-most-cited-resources}{}
\includegraphics[width=\textwidth,height=0.7\textheight]{images/talk06/STRING_google_scholar_citation_2021.png}
screenshot took in May 2021
more tools at Peer Bork's group:
\url{https://scholar.google.com/citations?hl=en\&user=M6Etr6oAAAAJ\&view_op=list_works\&sortby=pubdate}
\end{frame}
\begin{frame}{a typical STRING plot}
\protect\hypertarget{a-typical-string-plot}{}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.7\textheight]{images/talk06/string_normal_image.png}
\caption{interacting partners of SALL4}
\end{figure}
\end{frame}
\begin{frame}{note to previous plot}
\protect\hypertarget{note-to-previous-plot}{}
\textbf{note} this plot was generated using the following parameters:
\begin{itemize}
\tightlist
\item
use SALL4 in human as query
\item
show only the top ten connectivity partners
\item
only connectivity score \textgreater= 900 (or 0.9) were shown
\end{itemize}
\end{frame}
\begin{frame}{tasks of task 1}
\protect\hypertarget{tasks-of-task-1}{}
\begin{enumerate}
\tightlist
\item
get human PPI data
\item
limit the interactions to those with scores \textgreater= 900 (or 0.9)
\item
find SALL4 and its top ten interaction parteners
\item
visualize the PPI network
\item
calculate connectivities of sall4 and its top ten parteners in the
dataset
\end{enumerate}
\textbf{问题}
生物学意义何在？？
\end{frame}
\begin{frame}{download human ppi data from STRING}
\protect\hypertarget{download-human-ppi-data-from-string}{}
go to : \url{https://string-db.org/cgi/download.pl}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.5\textheight]{images/talk06/download_human_PPI_from_string.png}
\caption{Download human PPI data from STRING}
\end{figure}
\end{frame}
\begin{frame}[fragile]{load and load the human PPI data}
\protect\hypertarget{load-and-load-the-human-ppi-data}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{library}\NormalTok{(tidyverse);}
\end{Highlighting}
\end{Shaded}
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# read\_csv 也能处理压缩文件！！！ }
\NormalTok{ppi }\OtherTok{\textless{}{-}} \FunctionTok{read\_delim}\NormalTok{( }\AttributeTok{file =} \StringTok{"data/talk06/ppi900.txt.gz"}\NormalTok{, }\AttributeTok{col\_names =}\NormalTok{ T, }
\AttributeTok{delim =} \StringTok{"}\SpecialCharTok{\textbackslash{}t}\StringTok{"}\NormalTok{, }\AttributeTok{quote =} \StringTok{""}\NormalTok{ );}
\DocumentationTok{\#\# 查看一下数据 {-}{-}}
\NormalTok{ppi }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{filter}\NormalTok{( gene1 }\SpecialCharTok{==} \StringTok{"SALL4"}\NormalTok{ ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{do}\NormalTok{( }\FunctionTok{head}\NormalTok{(., }\AttributeTok{n =} \DecValTok{10}\NormalTok{ ) );}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 10 x 3
## gene1 gene2 score
## <chr> <chr> <dbl>
## 1 SALL4 POLR2E 900
## 2 SALL4 POLR2C 900
## 3 SALL4 POLR2I 900
## 4 SALL4 NANOG 992
## 5 SALL4 SALL1 923
## 6 SALL4 ZSCAN10 912
## 7 SALL4 LIN28A 957
## 8 SALL4 POU5F1 986
## 9 SALL4 SMAD2 906
## 10 SALL4 EPAS1 900
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{start to process the data}
\protect\hypertarget{start-to-process-the-data}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# get top 10 interacting partners of SALL4 by interaction score ... }
\NormalTok{toppart }\OtherTok{\textless{}{-}}\NormalTok{ ppi }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{filter}\NormalTok{( gene1 }\SpecialCharTok{==} \StringTok{"SALL4"}\NormalTok{ ) }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{arrange}\NormalTok{( }\FunctionTok{desc}\NormalTok{( score ) ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{slice}\NormalTok{( }\DecValTok{1}\SpecialCharTok{:}\DecValTok{10}\NormalTok{ );}
\DocumentationTok{\#\# get the interaction network consisting the top genes {-}{-}}
\NormalTok{genes }\OtherTok{\textless{}{-}} \FunctionTok{unique}\NormalTok{( }\FunctionTok{c}\NormalTok{( }\StringTok{"SALL4"}\NormalTok{, toppart}\SpecialCharTok{$}\NormalTok{gene2 ) );}
\NormalTok{netdata }\OtherTok{\textless{}{-}}\NormalTok{ ppi }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{filter}\NormalTok{( gene1 }\SpecialCharTok{\%in\%}\NormalTok{ genes }\SpecialCharTok{\&}\NormalTok{ gene2 }\SpecialCharTok{\%in\%}\NormalTok{ genes );}
\FunctionTok{nrow}\NormalTok{(netdata);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] 80
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{load the igraph package}
\protect\hypertarget{load-the-igraph-package}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# {-}{-} to make sure the installation will only run once ... }
\ControlFlowTok{if}\NormalTok{ (}\SpecialCharTok{!}\FunctionTok{require}\NormalTok{(}\StringTok{"igraph"}\NormalTok{))\{ }
\FunctionTok{chooseCRANmirror}\NormalTok{();}
\FunctionTok{install.packages}\NormalTok{(}\StringTok{"igraph"}\NormalTok{);}
\NormalTok{\} }
\FunctionTok{library}\NormalTok{( igraph );}
\end{Highlighting}
\end{Shaded}
\end{frame}
\begin{frame}[fragile]{visualise the network \ldots{}}
\protect\hypertarget{visualise-the-network}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{netnet }\OtherTok{\textless{}{-}} \FunctionTok{graph\_from\_data\_frame}\NormalTok{( netdata, }\AttributeTok{directed =} \ConstantTok{FALSE}\NormalTok{ );}
\FunctionTok{plot}\NormalTok{(netnet);}
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-6-1.pdf}
\end{frame}
\begin{frame}{图的问题}
\protect\hypertarget{ux56feux7684ux95eeux9898}{}
\begin{itemize}
\tightlist
\item
very ugly
\item
two lines (redundancy) between every two nodes
\end{itemize}
\end{frame}
\begin{frame}[fragile]{redundancy among data}
\protect\hypertarget{redundancy-among-data}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{netdata }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{filter}\NormalTok{( gene1 }\SpecialCharTok{\%in\%} \FunctionTok{c}\NormalTok{(}\StringTok{"SALL4"}\NormalTok{, }\StringTok{"NANOG"}\NormalTok{) }\SpecialCharTok{\&}\NormalTok{ gene2 }\SpecialCharTok{\%in\%} \FunctionTok{c}\NormalTok{(}\StringTok{"SALL4"}\NormalTok{, }\StringTok{"NANOG"}\NormalTok{) );}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 2 x 3
## gene1 gene2 score
## <chr> <chr> <dbl>
## 1 NANOG SALL4 992
## 2 SALL4 NANOG 992
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{how to remove redundancy?}
\protect\hypertarget{how-to-remove-redundancy}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# create a new column, sort the two gene names, and concatenate them ... }
\NormalTok{testdata }\OtherTok{\textless{}{-}}
\NormalTok{ netdata }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{filter}\NormalTok{( gene1 }\SpecialCharTok{\%in\%} \FunctionTok{c}\NormalTok{(}\StringTok{"SALL4"}\NormalTok{, }\StringTok{"NANOG"}\NormalTok{) }\SpecialCharTok{\&}\NormalTok{ gene2 }\SpecialCharTok{\%in\%} \FunctionTok{c}\NormalTok{(}\StringTok{"SALL4"}\NormalTok{, }\StringTok{"NANOG"}\NormalTok{) ) }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{mutate}\NormalTok{( }\AttributeTok{group =}
\FunctionTok{if\_else}\NormalTok{( gene1 }\SpecialCharTok{\textgreater{}}\NormalTok{ gene2, }
\FunctionTok{str\_c}\NormalTok{( gene1, gene2, }\AttributeTok{sep =} \StringTok{"{-}"}\NormalTok{ ), }
\FunctionTok{str\_c}\NormalTok{( gene2, gene1, }\AttributeTok{sep =} \StringTok{"{-}"}\NormalTok{ ) ) );}
\NormalTok{testdata;}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 2 x 4
## gene1 gene2 score group
## <chr> <chr> <dbl> <chr>
## 1 NANOG SALL4 992 SALL4-NANOG
## 2 SALL4 NANOG 992 SALL4-NANOG
\end{verbatim}
\FontNormal
\textbf{Note} \texttt{str\_c} is from the \texttt{stringr} package!!
\end{frame}
\begin{frame}[fragile]{remove redundancy!}
\protect\hypertarget{remove-redundancy}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{testdata }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{group\_by}\NormalTok{( group ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{slice}\NormalTok{( }\DecValTok{1}\NormalTok{ );}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 1 x 4
## # Groups: group [1]
## gene1 gene2 score group
## <chr> <chr> <dbl> <chr>
## 1 NANOG SALL4 992 SALL4-NANOG
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{remove redundancy, cont.}
\protect\hypertarget{remove-redundancy-cont.}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{netdata.nr }\OtherTok{\textless{}{-}}
\NormalTok{ netdata }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{mutate}\NormalTok{( }\AttributeTok{group =}
\FunctionTok{if\_else}\NormalTok{( gene1 }\SpecialCharTok{\textgreater{}}\NormalTok{ gene2, }
\FunctionTok{str\_c}\NormalTok{( gene1, gene2, }\AttributeTok{sep =} \StringTok{"{-}"}\NormalTok{ ), }
\FunctionTok{str\_c}\NormalTok{( gene2, gene1, }\AttributeTok{sep =} \StringTok{"{-}"}\NormalTok{ ) ) ) }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{group\_by}\NormalTok{( group ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{slice}\NormalTok{( }\DecValTok{1}\NormalTok{ );}
\FunctionTok{nrow}\NormalTok{(netdata.nr);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] 40
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{plot the non-redundant data}
\protect\hypertarget{plot-the-non-redundant-data}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{netnet.nr }\OtherTok{\textless{}{-}} \FunctionTok{graph\_from\_data\_frame}\NormalTok{( netdata.nr, }\AttributeTok{directed =} \ConstantTok{FALSE}\NormalTok{ );}
\FunctionTok{plot}\NormalTok{(netnet.nr);}
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-11-1.pdf}
\end{frame}
\begin{frame}[fragile]{redundant 的数据可以用来计算 degree}
\protect\hypertarget{redundant-ux7684ux6570ux636eux53efux4ee5ux7528ux6765ux8ba1ux7b97-degree}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{net.stats }\OtherTok{\textless{}{-}}
\NormalTok{ netdata }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{group\_by}\NormalTok{( gene1 ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{summarise}\NormalTok{( }\AttributeTok{degree =} \FunctionTok{n}\NormalTok{() ) }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{arrange}\NormalTok{( }\FunctionTok{desc}\NormalTok{ (degree) );}
\NormalTok{net.stats;}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 11 x 2
## gene1 degree
## <chr> <int>
## 1 SALL4 10
## 2 SOX2 10
## 3 NANOG 9
## 4 POU5F1 9
## 5 KLF4 8
## 6 LIN28A 8
## 7 PRDM14 7
## 8 ZSCAN10 7
## 9 STAT3 5
## 10 SALL1 4
## 11 CTNNB1 3
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{继续美化 network}
\protect\hypertarget{ux7ee7ux7eedux7f8eux5316-network}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# node大小由degree决定}
\DocumentationTok{\#\# 查看网络中基因名存储的顺序}
\FunctionTok{V}\NormalTok{(netnet.nr)}\SpecialCharTok{$}\NormalTok{name; }
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] "KLF4" "LIN28A" "POU5F1" "PRDM14" "SALL1" "CTNNB1" "NANOG"
## [8] "SOX2" "STAT3" "ZSCAN10" "SALL4"
\end{verbatim}
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# 获取它们相对应的 degree ...}
\NormalTok{net.stats[}\FunctionTok{match}\NormalTok{( }\FunctionTok{V}\NormalTok{(netnet.nr)}\SpecialCharTok{$}\NormalTok{name , net.stats}\SpecialCharTok{$}\NormalTok{gene1 ), ];}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 11 x 2
## gene1 degree
## <chr> <int>
## 1 KLF4 8
## 2 LIN28A 8
## 3 POU5F1 9
## 4 PRDM14 7
## 5 SALL1 4
## 6 CTNNB1 3
## 7 NANOG 9
## 8 SOX2 10
## 9 STAT3 5
## 10 ZSCAN10 7
## 11 SALL4 10
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{继续美化 network, cont.}
\protect\hypertarget{ux7ee7ux7eedux7f8eux5316-network-cont.}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{vertex\_attr}\NormalTok{(netnet.nr, }\StringTok{"size"}\NormalTok{) }\OtherTok{\textless{}{-}}
\NormalTok{ net.stats}\SpecialCharTok{$}\NormalTok{degree[}\FunctionTok{match}\NormalTok{( }\FunctionTok{V}\NormalTok{(netnet.nr)}\SpecialCharTok{$}\NormalTok{name , net.stats}\SpecialCharTok{$}\NormalTok{gene1 ) ] }\SpecialCharTok{*} \DecValTok{2}\NormalTok{;}
\FunctionTok{plot}\NormalTok{( netnet.nr );}
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-14-1.pdf}
\end{frame}
\begin{frame}{更多美化}
\protect\hypertarget{ux66f4ux591aux7f8eux5316}{}
详见：
\begin{enumerate}
\tightlist
\item
igraph introduction
\item
a comprehensive network visualization tutorial in R
\end{enumerate}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.4\textheight]{images/talk06/igraph_example.png}
\caption{Example final outcomes}
\end{figure}
\end{frame}
\begin{frame}[fragile]{other network visualisation packages}
\protect\hypertarget{other-network-visualisation-packages}{}
\begin{enumerate}
\tightlist
\item
\texttt{ggnet}
\item
\texttt{interactive\ networkD3\ R\ package}
\item
\texttt{plotly.js}
\item
\texttt{D3}
\end{enumerate}
\end{frame}
\begin{frame}{生信任务2 : 宏基因基因数据展示的小应用 (forcats)}
\protect\hypertarget{ux751fux4fe1ux4efbux52a12-ux5b8fux57faux56e0ux57faux56e0ux6570ux636eux5c55ux793aux7684ux5c0fux5e94ux7528-forcats}{}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.6\textheight]{images/talk06/gmrepo_run_statistics.png}
\caption{肠道物种丰度示意图}
\end{figure}
Find more at the \href{https://gmrepo.humangut.info/home}{GMrepo
database}.
\end{frame}
\begin{frame}{什么是宏基因组？}
\protect\hypertarget{ux4ec0ux4e48ux662fux5b8fux57faux56e0ux7ec4}{}
Metagenomics is the study of genetic material recovered directly from
environmental samples.
\begin{block}{research contents}
\protect\hypertarget{research-contents}{}
\begin{itemize}
\tightlist
\item
mostly prokaryotes
\item
unicellular eukaryotes
\item
viruses
\end{itemize}
\end{block}
\begin{block}{techniques}
\protect\hypertarget{techniques}{}
\begin{itemize}
\tightlist
\item
16S (universially conserved gene in prokaryotes)
\item
whole genome sequencing (WGS or metagenomics)
\end{itemize}
\end{block}
\end{frame}
\begin{frame}{what can metagenomics do?}
\protect\hypertarget{what-can-metagenomics-do}{}
\begin{itemize}
\tightlist
\item
identify new species
\item
reveal species kinds and abundances
\item
relate species changes to human health and disease
\end{itemize}
\end{frame}
\begin{frame}[fragile]{biomes}
\protect\hypertarget{biomes}{}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.6\textheight]{images/talk06/ebi_metagenomics_biomes_aug4_2021.png}
\caption{Biomes}
\end{figure}
Screenshot taken from the \texttt{EBI\ MGnify\ database} on
\texttt{Aug\ 4,\ 2021};
\end{frame}
\begin{frame}{enviromental microbiome}
\protect\hypertarget{enviromental-microbiome}{}
\begin{itemize}
\tightlist
\item
soil
\item
ocean
\end{itemize}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.5\textheight]{images/talk06/tara_oceans_boat.jpg}
\caption{The tara oceans expedition}
\end{figure}
\end{frame}
\begin{frame}{host associated microbiomes}
\protect\hypertarget{host-associated-microbiomes}{}
\begin{itemize}
\tightlist
\item
human body sites
\item
animals \& plants
\end{itemize}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.3\textheight]{images/talk06/iHMP.png}
\caption{NIH human microbiome project}
\end{figure}
\end{frame}
\begin{frame}{why human gut microbiota is important?}
\protect\hypertarget{why-human-gut-microbiota-is-important}{}
\begin{figure}
\centering
\includegraphics[width=\textwidth,height=0.6\textheight]{images/talk06/GutMicrobeInfographic.png}
\caption{human gut microbita}
\end{figure}
\end{frame}
\begin{frame}{tasks of human gut microbiota analysis}
\protect\hypertarget{tasks-of-human-gut-microbiota-analysis}{}
\begin{itemize}
\tightlist
\item
identify new species
\item
find good, bad and commensal microbes
\item
link microbial variations to human health
\item
mechanisms
\item
modulation, intervention and regulation
\end{itemize}
\end{frame}
\begin{frame}[fragile]{typical human gut microbiome data}
\protect\hypertarget{typical-human-gut-microbiome-data}{}
Species abundances
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{abu }\OtherTok{\textless{}{-}}
\FunctionTok{read\_delim}\NormalTok{(}
\AttributeTok{file =} \StringTok{"data/talk06/relative\_abundance\_for\_RUN\_ERR1072629\_taxonlevel\_species.txt"}\NormalTok{,}
\AttributeTok{delim =} \StringTok{"}\SpecialCharTok{\textbackslash{}t}\StringTok{"}\NormalTok{, }\AttributeTok{quote =} \StringTok{""}\NormalTok{, }\AttributeTok{comment =} \StringTok{"\#"}\NormalTok{);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## Rows: 122 Columns: 3
## -- Column specification --------------------------------------------------------
## Delimiter: "\t"
## chr (1): scientific_name
## dbl (2): ncbi_taxon_id, relative_abundance
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
\end{verbatim}
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{nrow}\NormalTok{(abu);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## [1] 122
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{Species abundances, cont.}
\protect\hypertarget{species-abundances-cont.}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{abu }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{arrange}\NormalTok{( }\FunctionTok{desc}\NormalTok{( relative\_abundance ) ) }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{do}\NormalTok{( }\FunctionTok{head}\NormalTok{(., }\AttributeTok{n =} \DecValTok{10}\NormalTok{) );}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 10 x 3
## ncbi_taxon_id relative_abundance scientific_name
## <dbl> <dbl> <chr>
## 1 821 24.3 Bacteroides vulgatus
## 2 -1 21.9 Unknown
## 3 328813 16.9 Alistipes onderdonkii
## 4 823 11.5 Parabacteroides distasonis
## 5 817 5.87 Bacteroides fragilis
## 6 818 3.41 Bacteroides thetaiotaomicron
## 7 239935 2.16 Akkermansia muciniphila
## 8 28116 2.05 Bacteroides ovatus
## 9 351091 1.97 Oscillibacter valericigenes
## 10 28118 1.41 Odoribacter splanchnicus
\end{verbatim}
\end{frame}
\begin{frame}{相对丰度作图要求}
\protect\hypertarget{ux76f8ux5bf9ux4e30ux5ea6ux4f5cux56feux8981ux6c42}{}
\begin{enumerate}
\tightlist
\item
按丰度从高到低排序
\item
只取前10个species (保留10行)
\item
将后面的丰度累加在一起，汇总为''Others''分类
\end{enumerate}
\end{frame}
\begin{frame}[fragile]{数据处理}
\protect\hypertarget{ux6570ux636eux5904ux7406}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{library}\NormalTok{( tidytidbits );}
\NormalTok{abu.dat }\OtherTok{\textless{}{-}}
\NormalTok{ abu }\SpecialCharTok{\%\textgreater{}\%} \FunctionTok{arrange}\NormalTok{( }\FunctionTok{desc}\NormalTok{( relative\_abundance ) ) }\SpecialCharTok{\%\textgreater{}\%}
\FunctionTok{lump\_rows}\NormalTok{( scientific\_name, relative\_abundance, }\AttributeTok{n =} \DecValTok{10}\NormalTok{, }\AttributeTok{other\_level =} \StringTok{"Others"}\NormalTok{ );}
\FunctionTok{head}\NormalTok{(abu.dat, }\AttributeTok{n =} \DecValTok{11}\NormalTok{);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 11 x 3
## ncbi_taxon_id relative_abundance scientific_name
## <dbl> <dbl> <chr>
## 1 821 24.3 Bacteroides vulgatus
## 2 -1 21.9 Unknown
## 3 328813 16.9 Alistipes onderdonkii
## 4 823 11.5 Parabacteroides distasonis
## 5 817 5.87 Bacteroides fragilis
## 6 818 3.41 Bacteroides thetaiotaomicron
## 7 239935 2.16 Akkermansia muciniphila
## 8 28116 2.05 Bacteroides ovatus
## 9 351091 1.97 Oscillibacter valericigenes
## 10 28118 1.41 Odoribacter splanchnicus
## 11 31199992 8.46 Others
\end{verbatim}
\end{frame}
\begin{frame}[fragile]{尝试作图}
\protect\hypertarget{ux5c1dux8bd5ux4f5cux56fe}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{ggplot}\NormalTok{(abu.dat, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{x =}\NormalTok{ scientific\_name, }\AttributeTok{y =}\NormalTok{ relative\_abundance, }\AttributeTok{fill =}\NormalTok{ scientific\_name ) ) }\SpecialCharTok{+}
\FunctionTok{geom\_bar}\NormalTok{( }\AttributeTok{stat =} \StringTok{"identity"}\NormalTok{ ) }\SpecialCharTok{+}
\FunctionTok{coord\_flip}\NormalTok{()}
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-18-1.pdf}
\end{frame}
\begin{frame}[fragile]{调整排列顺序}
\protect\hypertarget{ux8c03ux6574ux6392ux5217ux987aux5e8f}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# 用 forcat 包的 fct\_reorder 函数; 注意它3个参数的意义！！！}
\FunctionTok{ggplot}\NormalTok{(abu.dat, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{x =} \FunctionTok{fct\_reorder}\NormalTok{( scientific\_name, relative\_abundance, }\AttributeTok{.desc =}\NormalTok{ F), }
\AttributeTok{y =}\NormalTok{ relative\_abundance, }\AttributeTok{fill =}\NormalTok{ scientific\_name ) ) }\SpecialCharTok{+}
\FunctionTok{geom\_bar}\NormalTok{( }\AttributeTok{stat =} \StringTok{"identity"}\NormalTok{ ) }\SpecialCharTok{+}
\FunctionTok{coord\_flip}\NormalTok{() }\SpecialCharTok{+} \FunctionTok{xlab}\NormalTok{(}\StringTok{"Species"}\NormalTok{) }\SpecialCharTok{+} \FunctionTok{ylab}\NormalTok{( }\StringTok{"Relative abundance \%"}\NormalTok{ ) }
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-19-1.pdf}
\end{frame}
\begin{frame}[fragile]{把 \texttt{Others} 和 \texttt{Unknown} 放在最后}
\protect\hypertarget{ux628a-others-ux548c-unknown-ux653eux5728ux6700ux540e}{}
注意 \texttt{fct\_reorder}的用法：
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\DocumentationTok{\#\# }
\NormalTok{abu.dat}\SpecialCharTok{$}\NormalTok{scientific\_name }\OtherTok{\textless{}{-}}
\FunctionTok{fct\_relevel}\NormalTok{( }\FunctionTok{fct\_reorder}\NormalTok{( abu.dat}\SpecialCharTok{$}\NormalTok{scientific\_name, abu.dat}\SpecialCharTok{$}\NormalTok{relative\_abundance, }\AttributeTok{.desc =}\NormalTok{ F), }
\StringTok{"Unknown"}\NormalTok{, }\StringTok{"Others"}\NormalTok{ );}
\FunctionTok{ggplot}\NormalTok{(abu.dat, }\FunctionTok{aes}\NormalTok{(}\AttributeTok{x =}\NormalTok{ scientific\_name,}
\AttributeTok{y =}\NormalTok{ relative\_abundance, }\AttributeTok{fill =}\NormalTok{ scientific\_name ) ) }\SpecialCharTok{+}
\FunctionTok{geom\_bar}\NormalTok{( }\AttributeTok{stat =} \StringTok{"identity"}\NormalTok{ ) }\SpecialCharTok{+}
\FunctionTok{coord\_flip}\NormalTok{() }\SpecialCharTok{+} \FunctionTok{xlab}\NormalTok{(}\StringTok{"Species"}\NormalTok{) }\SpecialCharTok{+} \FunctionTok{ylab}\NormalTok{( }\StringTok{"Relative abundance \%"}\NormalTok{ ) }
\end{Highlighting}
\end{Shaded}
\includegraphics{/Users/lucas/Library/Mobile Documents/com~apple~CloudDocs/~~aa学习/大二上/学习/R for Data Science/R-for-Data-Science/talk06-practices_files/figure-beamer/unnamed-chunk-20-1.pdf}
\end{frame}
\begin{frame}{更多 forcats 的应用 \ldots{}}
\protect\hypertarget{ux66f4ux591a-forcats-ux7684ux5e94ux7528}{}
see here:
\url{https://cran.r-project.org/web/packages/forcats/vignettes/forcats.html}
更多应用将会在 作图 （ggplot2） 时讲到。
\end{frame}
\begin{frame}[fragile]{生信任务3 : 整合基因表达、甲基化、突变数据
(dplyr::join)}
\protect\hypertarget{ux751fux4fe1ux4efbux52a13-ux6574ux5408ux57faux56e0ux8868ux8fbeux7532ux57faux5316ux7a81ux53d8ux6570ux636e-dplyrjoin}{}
在生信分析中，常需要将多个来源的数据整合在一个表格中，以方便后续分析。
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{meth }\OtherTok{\textless{}{-}} \FunctionTok{read\_delim}\NormalTok{( }\AttributeTok{file =} \StringTok{"data/talk06/methylation\_data.txt.gz"}\NormalTok{, }
\AttributeTok{delim =} \StringTok{"}\SpecialCharTok{\textbackslash{}t}\StringTok{"}\NormalTok{, }\AttributeTok{quote =} \StringTok{""}\NormalTok{, }\AttributeTok{col\_names =}\NormalTok{ T);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## Rows: 52232 Columns: 3
## -- Column specification --------------------------------------------------------
## Delimiter: "\t"
## chr (2): gene, site
## dbl (1): methylation_score
##
## i Use `spec()` to retrieve the full column specification for this data.
## i Specify the column types or set `show_col_types = FALSE` to quiet this message.
\end{verbatim}
\begin{Shaded}
\begin{Highlighting}[]
\FunctionTok{head}\NormalTok{(meth, }\AttributeTok{n =} \DecValTok{3}\NormalTok{);}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## # A tibble: 3 x 3
## gene site methylation_score
## <chr> <chr> <dbl>
## 1 A1BG 1stExon 0.799
## 2 A1BG 5UTR 0.799
## 3 A1BG Body 0.811
\end{verbatim}
\FontNormal
\textbf{问题} 什么是甲基化？？
\end{frame}
\begin{frame}[fragile]{表达数据}
\protect\hypertarget{ux8868ux8fbeux6570ux636e}{}
\FontSmall
\begin{Shaded}
\begin{Highlighting}[]
\NormalTok{expr }\OtherTok{\textless{}{-}} \FunctionTok{read\_delim}\NormalTok{( }\AttributeTok{file =} \StringTok{"data/talk06/expression\_data.txt.gz"}\NormalTok{,}
\AttributeTok{delim =} \StringTok{"}\SpecialCharTok{\textbackslash{}t}\StringTok{"}\NormalTok{, }\AttributeTok{quote =} \StringTok{""}\NormalTok{, }\AttributeTok{col\_names =}\NormalTok{ T );}
\end{Highlighting}
\end{Shaded}
\begin{verbatim}
## Rows: 46150 Columns: 2
## -- Column specification --------------------------------------------------------
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