1.1 --- a/grant.txt Sat Apr 18 23:46:49 2009 -0700 1.2 +++ b/grant.txt Sun Apr 19 14:29:24 2009 -0700 1.3 @@ -263,14 +263,19 @@ 1.4 1.5 One class of feature selection scoring method are those which calculate some sort of "match" between each gene image and the target image. Those genes which match the best are good candidates for features. 1.6 1.7 -One of the simplest methods in this class is to use correlation as the match score. We calculated the correlation between each gene and each cortical area. Figure \ref{SScorr} shows the three genes most correlated with area SS. 1.8 - 1.9 -\begin{figure}\label{SScorr} 1.10 +One of the simplest methods in this class is to use correlation as the match score. We calculated the correlation between each gene and each cortical area. The top row of Figure \ref{SScorrLr} shows the three genes most correlated with area SS. 1.11 + 1.12 +\begin{figure}\label{SScorrLr} 1.13 \includegraphics[scale=.31]{singlegene_SS_corr_top_1_2365_jet.eps} 1.14 \includegraphics[scale=.31]{singlegene_SS_corr_top_2_242_jet.eps} 1.15 -\includegraphics[scale=.31]{singlegene_SS_corr_top_3_654_jet.eps} 1.16 - 1.17 -\caption{Genes (and predicted genes) Nfic, A930001M12Rik, C130038G02Rik are the most correlated with area SS (somatosensory cortex). Within each picture, the vertical axis roughly corresponds to anterior at the top and posterior at the bottom, and the horizontal axis roughly corresponds to medial at the left and lateral at the right. The red outline is the boundary of region MO. Pixels are colored according to correlation, with red meaning high correlation and blue meaning low.} 1.18 +\includegraphics[scale=.31]{singlegene_SS_corr_top_3_654_jet.eps}\\ 1.19 +\\ 1.20 +\includegraphics[scale=.31]{singlegene_SS_lr_top_1_654_jet.eps} 1.21 +\includegraphics[scale=.31]{singlegene_SS_lr_top_2_685_jet.eps} 1.22 +\includegraphics[scale=.31]{singlegene_SS_lr_top_3_724_jet.eps} 1.23 + 1.24 + 1.25 +\caption{Top row: Genes Nfic, A930001M12Rik, C130038G02Rik are the most correlated with area SS (somatosensory cortex). Bottom row: Genes C130038G02Rik, Cacna1i, Car10 are those with the best fit using logistic regression. Within each picture, the vertical axis roughly corresponds to anterior at the top and posterior at the bottom, and the horizontal axis roughly corresponds to medial at the left and lateral at the right. The red outline is the boundary of region MO. Pixels are colored according to correlation, with red meaning high correlation and blue meaning low.} 1.26 \end{figure} 1.27 1.28 1.29 @@ -284,7 +289,6 @@ 1.30 1.31 This finds pairs of genes which are most informative (at least at these discretization thresholds) relative to the question, "Is this surface pixel a member of the target area?". 1.32 1.33 -todo: fig 1.34 1.35 \vspace{0.3cm}**Gradient similarity** 1.36 We noticed that the previous two scoring methods, which are pointwise, often found genes whose pattern of expression did not look similar in shape to the target region. Fort his reason we designed a non-pointwise local scoring method to detect when a gene had a pattern of expression which looked like it had a boundary whose shape is similar to the shape of the target region. We call this scoring method "gradient similarity". 1.37 @@ -318,7 +322,7 @@ 1.38 1.39 \vspace{0.3cm}**Combinations of multiple genes are useful** 1.40 1.41 -Here we give an example of a cortical area which is not marked by any single gene, but which can be identified combinatorially. according to logistic regression, gene wwc1\footnote{"WW, C2 and coiled-coil domain containing 1"; EntrezGene ID 211652} is the best fit single gene for predicting whether or not a pixel on the cortical surface belongs to the motor area (area MO). The upper-left picture in Figure \ref{MOcombo} shows wwc1's spatial expression pattern over the cortex. The lower-right boundary of MO is represented reasonably well by this gene, however the gene overshoots the upper-left boundary. This flattened 2-D representation does not show it, but the area corresponding to the overshoot is the medial surface of the cortex. MO is only found on the lateral surface (todo). 1.42 +Here we give an example of a cortical area which is not marked by any single gene, but which can be identified combinatorially. according to logistic regression, gene wwc1\footnote{"WW, C2 and coiled-coil domain containing 1"; EntrezGene ID 211652} is the best fit single gene for predicting whether or not a pixel on the cortical surface belongs to the motor area (area MO). The upper-left picture in Figure \ref{MOcombo} shows wwc1's spatial expression pattern over the cortex. The lower-right boundary of MO is represented reasonably well by this gene, however the gene overshoots the upper-left boundary. This flattened 2-D representation does not show it, but the area corresponding to the overshoot is the medial surface of the cortex. MO is only found on the lateral surface. 1.43 1.44 Gene mtif2\footnote{"mitochondrial translational initiation factor 2"; EntrezGene ID 76784} is shown in figure the upper-right of Fig. \ref{MOcombo}. Mtif2 captures MO's upper-left boundary, but not its lower-right boundary. Mtif2 does not express very much on the medial surface. By adding together the values at each pixel in these two figures, we get the lower-left of Figure \ref{MOcombo}. This combination captures area MO much better than any single gene. 1.45 1.46 @@ -334,13 +338,17 @@ 1.47 1.48 1.49 1.50 -\vspace{0.3cm}**Areas which can be identified by single genes** 1.51 - 1.52 -todo 1.53 1.54 \vspace{0.3cm}**Underexpression of a gene can serve as a marker** 1.55 - 1.56 -todo 1.57 +Underexpression of a gene can sometimes serve as a marker. See, for example, Figure \ref{hole}. 1.58 + 1.59 + 1.60 +\begin{figure}\label{hole} 1.61 +\includegraphics[scale=.31]{holeExample_2682_SS_jet.eps} 1.62 +\caption{Gene Pitx2 is selectively underexpressed in area SS (somatosensory).} 1.63 +\end{figure} 1.64 + 1.65 + 1.66 1.67 === Specific to Aim 1 (and Aim 3) === 1.68 \vspace{0.3cm}**Forward stepwise logistic regression** 1.69 @@ -359,6 +367,27 @@ 1.70 1.71 todo 1.72 1.73 +\vspace{0.3cm}**Areas which can be identified by single genes** 1.74 + 1.75 +Using all of the methods we have tried to far, we have already found single genes which roughly identify some areas and groupings of areas. For each of these areas, an example of a gene which roughly identifies it is shown in Figure \ref{singleSoFar}. We have not yet cross-verified these genes in other atlases. 1.76 + 1.77 +In addition, there are a number of areas which are almost identified by single genes: COAa+NLOT (anterior part of cortical amygdalar area, nucleus of the lateral olfactory tract), ENT (entorhinal), ACAv (ventral anterior cingulate), VIS (visual), AUD (auditory). 1.78 + 1.79 + 1.80 +\begin{figure}\label{singleSoFar} 1.81 +\includegraphics[scale=.31]{singlegene_example_2682_Pitx2_SS_jet.eps} 1.82 +\includegraphics[scale=.31]{singlegene_example_371_Aldh1a2_SSs_jet.eps} 1.83 +\includegraphics[scale=.31]{singlegene_example_2759_Ppfibp1_PIR_jet.eps} 1.84 +\includegraphics[scale=.31]{singlegene_example_3310_Slco1a5_FRP_jet.eps} 1.85 +\includegraphics[scale=.31]{singlegene_example_3709_Tshz2_RSP_jet.eps} 1.86 +\includegraphics[scale=.31]{singlegene_example_3674_Trhr_COApm_jet.eps} 1.87 +\includegraphics[scale=.31]{singlegene_example_925_Col12a1_ACA+PL+ILA+DP+ORB+MO_jet.eps} 1.88 +\includegraphics[scale=.31]{singlegene_example_1334_Ets1_post_lat_vis_jet.eps} 1.89 + 1.90 +\caption{From left to right and top to bottom, single genes which roughly identify areas SS (somatosensory primary + supplemental), SSs (supplemental somatosensory), PIR (piriform), FRP (frontal pole), RSP (retrosplenial), COApm (Cortical amygdalar, posterior part, medial zone). Grouping some areas together, we have also found genes to identify the groups ACA+PL+ILA+DP+ORB+MO (anterior cingulate, prelimbic, infralimbic, dorsal peduncular, orbital, motor), posterior and lateral visual (VISpm, VISpl, VISI, VISp; posteromedial, posterolateral, lateral, and primary visual). The genes are $Pitx2$, $Aldh1a2$, $Ppfibp1$, $Slco1a5$, $Tshz2$, $Trhr$, $Col12a1$, $Ets1$.} 1.91 +\end{figure} 1.92 + 1.93 + 1.94 1.95 === Specific to Aim 2 (and Aim 3) === 1.96 1.97 @@ -481,3 +510,8 @@ 1.98 %%"genomic anatomy" is a name found in the titles of one of the cited papers which seems good; maybe "computational genomic anatomy" 1.99 1.100 %% todo: actually i'm pretty sure AGEA doesn't find ANY areas, but i said "most" and "often" to be cautious. 1.101 + 1.102 +%% todo: MO is only found on the lateral surface (todo). 1.103 +%% todo: predicted genes like Riken 1.104 + 1.105 +%% todo: should we disclose genes?