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latex_and_sweave [2013/07/23 09:11] zuo |
latex_and_sweave [2013/07/23 09:13] (current) zuo |
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}; | }; | ||
\node[hyper](input)[rectangle,fill=none,above = 2.9cm of 3]{Input Reads}; | \node[hyper](input)[rectangle,fill=none,above = 2.9cm of 3]{Input Reads}; | ||
- | \node[read](read1)[above right=0.2cm and -1.8cm of 1]{ACCTAC...................}; | ||
- | \node[read](read1)[above right=0.2cm and 1.3cm of 1]{...................CTGAGT}; | ||
- | \node[read](read1)[above right=0.2cm and -1.5cm of 4]{GTTACA...................}; | ||
- | \node[read](read1)[above right=0.4cm and -1.8cm of 1]{...................TGATTC}; | ||
\node[read](read1)[above right=0.4cm and 1.2cm of 3]{...................CACTTT}; | \node[read](read1)[above right=0.4cm and 1.2cm of 3]{...................CACTTT}; | ||
\node[count](x1)[below=0.3cm of 1]{$X_1=2$}; | \node[count](x1)[below=0.3cm of 1]{$X_1=2$}; | ||
- | \node[count](x2)[below=0.3cm of 2]{$X_2=2$}; | ||
- | \node[count](x3)[below=0.3cm of 3]{$X_3=1$}; | ||
- | \node[count](x4)[below=0.3cm of 4]{$X_4=2$}; | ||
- | \node[count](x5)[below=0.3cm of 5]{$X_5=2$}; | ||
- | \node[rate](lambda1)[below=1cm of x1]{$\lambda^z_1$}; | ||
- | \node[rate](lambda2)[below=1cm of x2]{$\lambda^z_2$}; | ||
- | \node[rate](lambda3)[below=1cm of x3]{$\lambda^z_3$}; | ||
- | \node[rate](lambda4)[below=1cm of x4]{$\lambda^z_4$}; | ||
\node[rate](lambda5)[below=1cm of x5]{$\lambda^z_5$}; | \node[rate](lambda5)[below=1cm of x5]{$\lambda^z_5$}; | ||
\node[hyper](fun)[fill=red!80,below=2.5cm of x3]{$\mu_i=f(M_i,GC_i)$}; | \node[hyper](fun)[fill=red!80,below=2.5cm of x3]{$\mu_i=f(M_i,GC_i)$}; | ||
\node[rate](lambday1)[below=6cm of x1]{$\lambda^y_1$}; | \node[rate](lambday1)[below=6cm of x1]{$\lambda^y_1$}; | ||
- | \node[rate](lambday2)[below=6cm of x2]{$\lambda^y_2$}; | ||
- | \node[rate](lambday3)[below=6cm of x3]{$\lambda^y_3$}; | ||
- | \node[rate](lambday4)[below=6cm of x4]{$\lambda^y_4$}; | ||
- | \node[rate](lambday5)[below=6cm of x5]{$\lambda^y_5$}; | ||
\node[count](y1)[below=1cm of lambday1]{$Y_1=3$}; | \node[count](y1)[below=1cm of lambday1]{$Y_1=3$}; | ||
- | \node[count](y2)[below=1cm of lambday2]{$Y_2=5$}; | ||
- | \node[count](y3)[below=1cm of lambday3]{$Y_3=3$}; | ||
- | \node[count](y4)[below=1cm of lambday4]{$Y_4=2$}; | ||
- | \node[count](y5)[below=1cm of lambday5]{$Y_5=2$}; | ||
% \matrix[nodes={draw, ultra thick, fill=red!20}, row sep=0cm,column sep=0cm,ampersand replacement=\&] { | % \matrix[nodes={draw, ultra thick, fill=red!20}, row sep=0cm,column sep=0cm,ampersand replacement=\&] { | ||
\node[bin](bin1)[below=0.3cm of y1]{};\& \node[bin](bin2)[below=0.3cm of y2]{};\& \node[bin](bin3)[below=0.3cm of y3]{};\& \node[bin](bin4)[below=0.3cm of y4]{};\& \node[bin](bin5)[below=0.3cm of y5]{};\\ | \node[bin](bin1)[below=0.3cm of y1]{};\& \node[bin](bin2)[below=0.3cm of y2]{};\& \node[bin](bin3)[below=0.3cm of y3]{};\& \node[bin](bin4)[below=0.3cm of y4]{};\& \node[bin](bin5)[below=0.3cm of y5]{};\\ | ||
Line 162: | Line 142: | ||
\node[protein](protein1)[above right=-0.3cm and -1cm of bin2]{protein}; | \node[protein](protein1)[above right=-0.3cm and -1cm of bin2]{protein}; | ||
\node[read](read1)[below right=0.2cm and -0.7cm of bin1]{ACCGAC...................}; | \node[read](read1)[below right=0.2cm and -0.7cm of bin1]{ACCGAC...................}; | ||
- | \node[read](read1)[below right=0.2cm and 1.3cm of bin1]{...................CTCAGT}; | ||
- | \node[read](read1)[below right=0.2cm and -1cm of bin4]{GTTACA...................}; | ||
- | \node[read](read1)[below right=0.6cm and -0.9cm of bin1]{AGCACC...................}; | ||
- | \node[read](read1)[below right=0.4cm and -1.1cm of bin1]{...................TAGATC}; | ||
- | \node[read](read1)[below right=0.4cm and 0.7cm of bin1]{CGCCAG...................}; | ||
- | \node[read](read1)[below right=0.4cm and 0.8cm of bin3]{...................CCCCTT}; | ||
- | \node[hyper](chip)[below=0.6cm of bin3,fill=none,rectangle]{ChIP Reads}; | ||
\node[hyper](fig)[below=0.1cm of chip,fill=none,rectangle]{\scriptsize \textit{Fig. 2: The hierarchical Bayesian model for bin-level couts.}}; | \node[hyper](fig)[below=0.1cm of chip,fill=none,rectangle]{\scriptsize \textit{Fig. 2: The hierarchical Bayesian model for bin-level couts.}}; | ||
\path[every node/.style={font=\sffamily\small}] | \path[every node/.style={font=\sffamily\small}] | ||
(lambda1) edge (x1) | (lambda1) edge (x1) | ||
- | (lambda2) edge (x2) | ||
- | (lambda3) edge (x3) | ||
- | (lambda4) edge (x4) | ||
- | (lambda5) edge (x5) | ||
- | (fun) edge (lambda1) | ||
- | (fun) edge (lambda2) | ||
- | (fun) edge (lambda3) | ||
- | (fun) edge (lambda4) | ||
- | (fun) edge (lambda5) | ||
- | (fun) edge (lambday1) | ||
- | (fun) edge (lambday3) | ||
- | (fun) edge (lambday4) | ||
(fun) edge (lambday5) | (fun) edge (lambday5) | ||
- | (lambday1) edge (y1) | ||
- | (lambday2) edge (y2) | ||
- | (lambday3) edge (y3) | ||
- | (lambday4) edge (y4) | ||
(lambday5) edge (y5); | (lambday5) edge (y5); | ||
\node[rate](B1)[above left=0.5cm and -0.5cm of lambday1]{$B_1=0$}; | \node[rate](B1)[above left=0.5cm and -0.5cm of lambday1]{$B_1=0$}; | ||
- | \node[rate](B3)[above left=0.5cm and -0.50cm of lambday3]{$B_3=0$}; | ||
- | \node[rate](B4)[above left=0.5cm and -0.50cm of lambday4]{$B_4=0$}; | ||
\node[rate](B5)[above left=0.5cm and -0.50cm of lambday5]{$B_5=0$}; | \node[rate](B5)[above left=0.5cm and -0.50cm of lambday5]{$B_5=0$}; | ||
\path[every node/.style={font=\sffamily\small}] | \path[every node/.style={font=\sffamily\small}] | ||
(B1)edge(lambday1) | (B1)edge(lambday1) | ||
- | (B3)edge(lambday3) | ||
- | (B4)edge(lambday4) | ||
(B5)edge(lambday5); | (B5)edge(lambday5); | ||
- | |||
- | |||
- | \node [hyper](hyperx)[below=0.3cm of lambda3]{$\lambda^x_i\sim \Gamma(a,a/\mu_i)$}; | ||
- | \node [hyper](poisx)[below=0.3cm of x3]{$X_i\sim Pois(\lambda_iN_x)$}; | ||
- | \node [hyper](poisx)[above=0.3cm of y3]{$Y_i\sim Pois(\lambda^y_ie_0N_y)$}; | ||
- | \node[hyper](hyperb)[above right =0.5cm and 1.5cm of B1]{$\lambda^y_i | B_i=j \sim \Gamma(b^j,b^j/\mu^j)$}; | ||
- | \path[every node/.style={font=\sffamily\small}] | ||
- | (hyperb)edge(lambday2); | ||
- | \node[rate](B2)[above left=0.5cm and -0.50cm of lambday2]{$B_2=1$}; | ||
- | \path[every node/.style={font=\sffamily\small}] | ||
- | (B2) edge (lambday2) ; | ||
- | \node [hyper](hyperx)[below=0.3cm of fun]{$\lambda^y_i|B_j=0 \sim \Gamma(b,b/\mu_i)$}; | ||
\end{tikzpicture} | \end{tikzpicture} | ||
</code> | </code> |