Transposed classical GEMME output for better legibility!

Dockerfile

 FROM ubuntu:20.04
 
 LABEL maintainer="Mustafa Tekpinar <tekpinar@buffalo.edu>"
-LABEL description="ESGEMME: Evolutionary and Structural Global Epistatic Model for Predicting Mutational Effects."
+LABEL description="ESGEMME: Evolutionary and Structural Global Epistatic Model for predicting Mutational Effects."
 
 WORKDIR /home/tekpinar/research/lcqb
 ENV JET2_PATH=/home/tekpinar/research/lcqb/JET2
@@ -13,6 +13,7 @@ COPY ./ESGEMME/pred.R ./ESGEMME/pred.R
 COPY ./ESGEMME/computePred.R ./ESGEMME/computePred.R
 COPY ./ESGEMME/default.conf ./ESGEMME/default.conf
 COPY ./ESGEMME/data/ ./ESGEMME/data/
+COPY ./ESGEMME/examples/ ./ESGEMME/examples/
 
 ###################################################################
 RUN apt-get update --fix-missing && \
@@ -25,6 +26,7 @@ apt-get install -y r-base r-base-core && \
 apt-get install -y muscle && \
 apt-get install -y dssp && \
 apt-get install -y default-jre && \
+apt-get install -y ncbi-blast+ && \
 apt-get install csh && \
 apt-get clean && rm -rf /var/lib/apt/lists/* /tmp/* /var/tmp/*
 ###################################################################
@@ -33,5 +35,12 @@ RUN ln -s /usr/bin/python3 /usr/bin/python
 RUN pip3 install --no-cache-dir prody matplotlib scipy pandas biotite
 RUN Rscript -e 'install.packages("seqinr", repos="http://cran.us.r-project.org", dependencies=TRUE)'
 
+# Build command
+# sudo docker build -t tekpinar/esgemme-docker:v1.3.0 .
 
+# Pull command on M1 Mac with macOS Monterey
+# docker pull tekpinar/esgemme-docker:v1.3.0
+
+# Run command on M1 Mac with macOS Monterey
+# docker run -i -t -v $(pwd) --platform linux/amd64 tekpinar/esgemme-docker:v1.3.0 /bin/bash
 

esgemme.py

@@ -1053,6 +1053,20 @@ def doit(inAli,mutFile,retMet,bFile,fFile,n,N, jetfile, pdbfile, normWeightMode,
             gemmeData = parseGEMMEoutput(prot+"_normPred_evolCombi.txt", verbose=False)
             plotGEMMEmatrix(gemmeData, prot+"_normPred_evolCombi.png", 1, None,\
                             colorMap='Oranges_r', offSet=0, pixelType='square')
+
+            #Convert standard combined output to a transposed format to increase
+            #legibility.
+            gemmeDF = pd.read_table(prot+"_normPred_evolCombi.txt", sep="\s+")
+            gemmeDFtrans = gemmeDF.T
+            print(gemmeDF)
+#            gemmeDF.columns = gemmeDF.columns.str.upper()
+            gemmeDFtrans.columns = gemmeDFtrans.columns.str.upper()
+#            with open('./filename.txt', 'w') as fo:
+#                fo.write(gemmeDFtrans.__repr__())
+            gemmeDFtrans.to_csv(prot+"_normPred_evolCombiTransposed.txt", sep='\t', float_format='%.2f', na_rep='NaN')
+            #sys.exit(-1)
+            
+            
         else:
             print("ERROR: "+prot+"_normPred_evolCombi.txt file does not exist!")
             print("       Can not generate "+prot+"_normPred_evolCombi.png file!")

pred.R

@@ -285,7 +285,11 @@ normalizePredWithNbSeqsZeroSelMult<-function(pred, trace, wt, listMut){
     myAA = tolower(let[[i]])
     n = length(myPos)
     predTMP = c()
-    for(k in 1:n){predTMP=c(predTMP,pred[myAA[k],myPos[k]])}
+    # print(myPos[1])
+    for(k in 1:n){
+      # print(k)
+      predTMP=c(predTMP,pred[myAA[k],myPos[k]])
+    }
     normPred[i] = sum(predTMP * trace[myPos])
   }
   return(normPred)