Ross and Shah Submission

bioinformaticsProject/BioCompProject.sh

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+#Shell Script for Biocomputing Bash Project Fall 2021
+
+#Usage: bash BioCompProject.sh
+#the code will ask users for the path's of where each folder is located. However to make it 
+#easier on users, we suggest organizing the project's files based on the structure below:
+##### /bioinformaticsProject : /muscle, /ref_sequences, /BioCompProject.sh, /proteomes, 
+#     /hmmer/bin/: hmmbuild hmmsearch 
+
+
+# The following code is getting the path of McRa gene, HSP70 gene and Proteomes from the user.
+printf  "Hi, I hope you are doing great.\nCould you please give me the path of McRA_Genes?\n"
+printf  "Example: ref_sequences directory is in Biocomp-Project, which is current working directory, enter './ref_sequences'\n"
+printf  "If any path is your current path, please enter only a '.'\n"
+
+read Path1
+printf "Awesome, and also share the path of HSP70 genes?\n"
+read Path2
+printf "Great! Now kindly enter the path where proteomes are stored\n"
+read Path3
+printf "Thank you. Almost there...I promise. Please tell us the path where your Muscle program is stored.\n"
+read Path4
+printf "Finally, could you list the path for your hmmbuild and hmmsearch?\n"
+read Path5
+
+printf "The paths you have entered are: "
+echo $Path1 $Path2 $Path3 $Path4 $Path5
+
+#following commands concatenates all the McrA gene files and all of the HSP70 gene files
+#results in one file for McrA genes and anothe for HSP70 genes
+cat $Path1/mcrAgene*.fasta  > $Path1/mcrAlist.fasta
+cat $Path2/hsp70gene*.fasta > $Path2/hsp70list.fasta
+
+#next set of commands runs the Muscle program to create alignment files 
+#for both types of reference sequences. Then a profile is built for each to perform a search
+
+$Path4/muscle -in $Path1/mcrAlist.fasta -out $Path1/mcrAlignment.fasta
+
+$Path4/muscle -in $Path2/hsp70list.fasta -out $Path2/hsp70Alignment.fasta
+
+$Path5/hmmbuild $Path1/mcrAbuild.fasta $Path1/mcrAlignment.fasta 
+
+$Path5/hmmbuild $Path2/hsp70build.fasta $Path2/hsp70Alignment.fasta
+
+#removes any file with this naming convention 
+rm genehitlist.csv
+
+#print a header row for your CSV file
+echo -e 'Proteome\tMcrA Hits\tHSP70 Hits'  >> genehitlist.csv
+
+#begin for loop to generate a search image that will be then referenced to all 50 proteomes
+#to find any proteome that has the most McrA and HSP70 hits/matches
+for i in {01..50}
+
+do 
+
+$Path5/hmmsearch --tblout mcrAsearch.fasta $Path1/mcrAbuild.fasta $Path3/proteome_$i*
+
+mcrAhit=$(cat mcrAsearch.fasta | grep -v "^#" | wc -l)
+
+$Path5/hmmsearch --tblout hsp70search.fasta $Path2/hsp70build.fasta $Path3/proteome_$i* 
+
+hsp70hit=$(cat hsp70search.fasta | grep -v "^#" | wc -l)
+
+echo -e Proteome_$i'\t'$mcrAhit'\t\t'$hsp70hit >> genehitlist.csv 
+
+done	
+
+
+# The following pipeline  travereses genehitlist.csv to find the best 5 candidates that are  
+#methanogens with pH resistance qualities. First, we check to see if there are any McrA hits, and
+#discard any that return with 0 hits. Following this we sort the reminaing proteomes based on their 
+#the number of hsp70 gene hits/matches. Finally, this list is stored in a new .txt file and is displayed for the user to see
+
+cat genehitlist.csv |awk -F '\t' '$2>0'|sort -k 3 -nr | head -n 5 | cut -f 1 > UltimateHitList.txt 
+
+echo "This is the ultimate list of Proteomes to use for your experiment...Good luck!"
+cat UltimateHitList.txt
+

bioinformaticsProject/UltimateHitList.txt

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+Proteome_50
+Proteome_45
+Proteome_42
+Proteome_03
+Proteome_24

bioinformaticsProject/genehitlist.csv

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+Proteome	McrA Hits	HSP70 Hits
+Proteome_01	0		4
+Proteome_02	0		2
+Proteome_03	1		3
+Proteome_04	0		4
+Proteome_05	1		2
+Proteome_06	0		0
+Proteome_07	1		2
+Proteome_08	0		5
+Proteome_09	0		1
+Proteome_10	0		3
+Proteome_11	0		6
+Proteome_12	0		6
+Proteome_13	0		3
+Proteome_14	0		2
+Proteome_15	1		1
+Proteome_16	1		1
+Proteome_17	0		4
+Proteome_18	0		8
+Proteome_19	2		1
+Proteome_20	0		3
+Proteome_21	0		5
+Proteome_22	0		9
+Proteome_23	2		2
+Proteome_24	1		2
+Proteome_25	0		5
+Proteome_26	0		1
+Proteome_27	0		1
+Proteome_28	0		1
+Proteome_29	1		0
+Proteome_30	0		1
+Proteome_31	0		7
+Proteome_32	0		4
+Proteome_33	0		0
+Proteome_34	0		2
+Proteome_35	0		1
+Proteome_36	0		3
+Proteome_37	0		1
+Proteome_38	1		1
+Proteome_39	1		1
+Proteome_40	0		2
+Proteome_41	0		1
+Proteome_42	1		3
+Proteome_43	0		3
+Proteome_44	1		1
+Proteome_45	1		3
+Proteome_46	0		2
+Proteome_47	0		1
+Proteome_48	1		1
+Proteome_49	0		3
+Proteome_50	1		3