--- title: "SubVis" author: "Scott Barlowe, Heather Coan, and Robert Youker" date: "`r Sys.Date()`" output: rmarkdown::html_vignette vignette: > %\VignetteIndexEntry{SubVis} %\VignetteEngine{knitr::rmarkdown} %\VignetteEncoding{UTF-8} --- [About](#abt) [Description](#descr) [Other Project Pages](#other) [Known Issues](#issues) [Included Data](#data) [Getting Started](#start) [Options Tab](#options) [VIZ Tab: Overview](#over) [VIZ Tab: Detail](#detail) [VIZ Tab: Search](#srch) [Error Messages](#error) [Notes](#note) [References](#ref) ### About: SubVis version 2.0.2 Scott Barlowe, Heather Coan, and Robert Youker Western Carolina University Uses: R (>= 3.3.0), JavaScript Licensing: GNU General Purpose License ### Description: Software tool for visual analysis of substitution matrix effects on pairwise protein sequence alignment. Utilizes Shiny for interface components, R for alignment processing, and JavaScript for visualization. ### Other Project Pages: 1. https://github.com/sabarlowe/SubVis ### Known Issues: None ### Included Data: Location: (extdata/Example_custom_matrix and extdata/Example_FASTA_files) 1. Four protein sequences in FASTA format (gpr12.fasta, gpr6.fasta) (Human.fasta, Xenla.fasta) (fNucl.fasta, pFalc.fasta) 2. A custom matrix developed by Rios et al. (gpcrtm.txt) A scaled and scaled adjusted matrix reported by Yu and Altschul (scaled_BLSM.txt, scaled_adj_BLSM.txt) The DISORDER matrix proposed by Radivojac et al. (disorder_mat.txt) 3. BLOSUM62 matrix used for varying penalties (BLS.txt) 4. Three custom master files (masterFile_gpcrtm.txt, masterFile_scaled_adj_bls.txt, and masterFile_disorder.txt) listing the file names of custom matrices and their associated gap and extension costs ### Getting Started: (Requires availability of a web browser): 1. Install R version >= 3.3.0 2. Install required R packages (and any dependencies): 'shiny' 'Biostrings' 3. Install and load SubVis package 4. Launch SubVis at the RStudio prompt with '> SubVis::startSubVis()' NOTE: ENTERING SEQUENCE TEXT (INSTEAD OF FILE UPLOAD) AND USING CUSTOM MATRICES REQUIRES READ/WRITE PERMISSIONS IN THE SUBVIS INSTALLATION DIRECTORY ### Main Tabs: Options, VIZ, and Help After launching, there are three tabs: Options, VIZ, and Help ### Options Tab: Loading Data, Matrices, and Parameters The Options tab includes the following features/requirements: 1. Protein sequences (one per file) must be in FASTA format. There are three sets of example FASTA files in the extdata/Example_FASTA_files folder. 2. Sequences can be loaded by either entering the text (including by copy/paste) or by file selection. In the case of text entry, text files with the FASTA sequences are created in the extdata/Example_FASTA_files directory located in the SubVis installation directory. These files can be saved for future use. NOTE: ENTERING SEQUENCE TEXT (INSTEAD OF FILE UPLOAD) REQUIRES READ/WRITE PERMISSIONS IN THE SUBVIS INSTALLATION DIRECTORY 3. An error message will be generated if a. Either textbox or file selection is empty b. Spaces (other than newlines) are in the sequences c. The header and sequences of both are identical d. The sequences are identical 4. BLOSUM and PAM matrices can be selected by checking the appropriate box. Gaps and extension costs can be changed with the associated text boxes. An error message will be generated if a. The gap entry is empty or is not a number b. The extension entry is empty or is not a number 5. Multiple custom matrices in the form of the predefined matrices can be loaded from text files. The basic form is First row --> Characters representing lookup table First col --> Transpose of first row starting at the second row A B C D E F . . . A B C D E F ... All other entries (intersection of amino acids) are substitution values Custom matrices are loaded by selecting a master file. This file lists the filenames of the custom matrices. Both files should be located in the extdata/Example_custom_matrix folder located in the SubVis installation directory. The format is: custom_matrix_name0 gap_cost0 extension_cost0 custom_matrix_name1 gap_cost1 extension_cost1 custom_matrix_name2 gap_cost2 extension_cost2 ...and so on... Spaces separate the custom matrix name, gap cost, and extension cost for each matrix. EACH LINE MUST END WITH A NEWLINE CHARACTER TO AVOID ERRORS/WARNINGS. THIS INCLUDES THE LAST LINE LISTING A CUSTOM MATRIX. THERE MUST BE A SINGLE BLANK LINE AFTER THE LAST ENTRY. In the display, the custom matrix is labeled "CM" followed by the number associated with its place in the order matrices are listed in the custom matrix master file (for example, CM0, CM1, etc.). An error message will be generated if a. The custom matrix radio button is set to "ON" and the file selection is empty b. The format of the custom matrix is not acceptable NOTE: USING CUSTOM MATRICES REQUIRES READ/WRITE PERMISSIONS IN THE SUBVIS INSTALLATION DIRECTORY 6. The score type can be selected with the drop-down menu 7. After all parameters are entered, clicking the "GO" button located under the "PERFORM ALIGNMENT" label will change the view to the Overview visualization Note: Each time a change in the Options tab is made, the "GO" button must be clicked ### VIZ Tab: Overview, Detail View, and Search View There are three options that can be selected with a drop-down menu: Overview, Detail view, and Search view ### Overview: Each row (except the last) represents a percent identity type. Within each row, the PID for the selected matrices are sorted. The last row is the sorted overall score. PID types include the following variances in denominator calculations as investigated by May and by Raghava and Barton: PID 1 - Denominator should be defined as aligned positions plus internal gap positions. PID 2 - Denominator should be defined as aligned positions. PID 3 - Denominator should be defined as the length of the shorter sequence. PID 4 - Denominator should be defined as the average of the two sequences. All PID colors are normalized together. The score colors are normalized separate from the PIDs. A legend in the bottom left shows the color scheme along with the minimum and maximum values for the PID and score. Interaction: Mouse move 1. When the mouse moves over a matrix type, the corresponding matrix in the other rows are identified. At the same time, detail information for the selected matrix (matrix type, percent identity, and score) are shown in the bottom right. When the mouse moves over the overall score, PID 4 for the selected matrix is shown. Interaction: Size 1. '+' enlarges the displayed items and '-' shrinks the displayed items ### Detail View: The overall score is located under the matrix type for each alignment pair along the left side. Amino acids are represented by a color-coded box. Interaction: Size 1. '+' enlarges the displayed items 2. '-' shrinks the displayed items Interaction: Mouse over an amino acid 1. A histogram displays the number of each amino acid in that column 2. The log-odds score (or any substitution value entered into a custom matrix) and the amino acid substitution are displayed under the score for each alignment 3. The amino acid, log-odds score (or any substitution value entered into a custom matrix), and the amino acid substitution are shown in the top right 4. The gap and extension costs for the selected amino acid (under the mouse) are shown in the top left Interaction: Classification 1. Amino acids can be classified according to [1] and whether an amino acid substitution is conserved (log-odds > 0) or not (log-odds < 0) Interaction: Amino Acid Representation 1. 'Alpha On/Off' - Shows amino acid abbreviation instead of boxes Interaction: Navigation 1. 'S' - Go to position 1 2. 'E' - Go to the end of the alignment with the maximum length 3. 'U' - Scroll up if all matrix types will not fit onto display space 4. 'D' - Scroll down if all matrix types will not fit onto display space 5. '<' - Go backward in the alignment 6. '>' - Go forward in the alignment 7. 'Pair' - Show both the pattern and subject for each matrix type 8. 'Patt' - Show only the pattern for each matrix type 9. 'Subj' - Show only the subject for each matrix type ### Search View: Interaction: POS (Requires clicking 'GO') 1. Go to a position by entering the column number in text box (Requires clicking 'Go') Interaction: Search (All require clicking 'Go') 1. 'NONE' - No search function on (default) 2. 'INDEL' - Shows the insertions and deletions in red 3. 'MATCH' - Shows the positions that match in both the pattern and subject 4. 'SEQ' - The amino acid to be searched for ### Error Messages: Error messages are generated in the following scenarios in the top left of the VIZ tab 1. 'ERROR: No Sequence Text': Generated if either sequence text box is empty 2. 'ERROR: No Sequence File': Generated if either sequence file selection is empty 3. 'ERROR: Identical Pattern and Subject': Generated if the two sequence inputs (header information and sequences) are identical 4. 'ERROR: Identical Sequences': Generated if the two sequence inputs (sequences only) are the same 5. 'ERROR: Non-Custom Gap': Bad gap value for the BLOSUM/PAM matrices provided (empty value or not a number) 6. 'ERROR: Non-Custom Ext': Bad extension value for the BLOSUM/PAM matrices provided (empty value or not a number) 7. 'ERROR: Bad Sequence or Matrix': Error in Biostring's pairwiseAlignment function. Could indicate, among other possibilities, a poorly constructed sequence not indicated by another error message or a poorly constructed custom matrix/custom matrix master file. 8. 'ERROR: No Custom Matrix Selected': Custom matrix turned on without selecting a custom matrix master file 9. 'ERROR: Custom Gap': Bad gap cost for the custom matrix read from the custom matrix file (not a number) 10. 'ERROR: Custom Ext': Bad extension cost for the custom matrix read from the custom matrix file (not a number) ### Notes: 1. Log-odds score (or any substitution value entered into a custom matrix) for pairs involving a gap are reported as undefined ### References: 1. Pages, H., Aboyoun, P., Gentleman, R., DebRoy, S.: Biostrings: String Objects Representing Biological Sequences, and Matching Algorithms. R package version 2.32.0 2. Pearson, W.R., Lipman, D.J.: Improved tools for biological sequence comparison. Proc. Natl. Acad. Sci. USA 85(8), 2444{2448 (1988) 3. Pommie, C., Levadoux, S., Sabatier, R., Lefranc, G., Lefranc, M.: Imgt standardized criteria for statistical analysis of immunoglobulin v-region amino acid properties. Journal of Molecular Recognition 17(1), (2004) 4. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2013). R Foundation for Statistical Computing. http://www.R-project.org/ 5. RStudio, Inc.: Shiny: Web Application Framework for R. (2014). R package version 0.10.1. http://CRAN.R-project.org/package=shiny 6. Rios, S., Fernandez, M.F., Caltabiano, G., Campillo, M., Pardo, L., Gonzalez, A.: Gpcrtm: An amino acid substitution matrix for the transmembrane region of class a g protein-coupled receptors. BMC Bioinformatics 16(206). (2015) 7. Yu, Y., Altschul, S.F.: The construction of amino acid substitution matrices for the comparison of proteins with non-standard compositions. Bioinformatics 21(7): 902-911. (2004) 8. Radivojac, P., Obradovic, Z., Brown, C.J., Dunker, A.K.: Improving sequence alignments for intrinsically disordered proteins. Pacific Symposium on Biocomputing 7:589-600. (2002) 9. May, A.: Percent sequence identity; the need to be explicit. Structure, 12(17). (2004) 10. Raghava, G. and Barton, G.: Quantification of the variation in percentage identity for protein sequence alignments. BMC Bioinformatics, 7(415). (2006)