Manual
manual
manual
User Manual:
Open the PDF directly: View PDF .
Page Count: 6
Download | |
Open PDF In Browser | View PDF |
GSnet User Manual Maintainer: Jinhwan Kim hwanistic@unist.ac.kr 2018-07-12 1. 2 Ways to Start GSnet ① Run following codes on R console. >library(‘shiny’) >runGitHub(‘epn’, ‘jhk0530’) It is simple but may take a few minutes to download the data. To save the time, we recommend users to use second way. ② Download ZIP file and run app in R - Access to the GSnet GitHub page (https://github.com/jhk0530/epn) - Download the ZIP file by clicking ‘Clone or download’ and ‘Download ZIP’ button. - Unzip the downloaded file - Open R studio and set working directory to where the unzipped file exists. - Open the file ‘app.R’ and click ‘Run App’ button . Figure 1. Running GSnet using downloaded ZIP file Figure 2. Initial screen of GSnet * Note: GSnet can be run on both R display screen and web browser (by clicking ‘Open in Browser’ button in the R display screen). Running app on web browser is usually faster. 2. How to use ① Upload input data - Geneset: Gene-set analysis (GSA) result file. It is a tab-delimited text file composed of 3 columns including gene-set name, member genes and q-value. The header line is required. Gene-set members must be separated by space. Example file is available from ‘Downloads’ tab . Figure 3. Example of gene-set analysis result file - Geneset Cutoff: The significance cutoff for gene-sets to be included in the gene-set network. Default=0.25 - Gene score file (optional): Gene score file. It consists of gene name and gene pvalue columns (tab-delimited). The header line is required. Example file is available from ‘Downloads’ tab . Figure 4. Example of gene score file - Gene score Cutoff: The significance off for genes to be included in the gene network. Default=0.05. - After uploading data and setting parameters, click ‘RUN’ to generate gene-set and gene networks. ‘TRY DEMO’ will show the example network for gene sets significantly altered in Type 2 Diabetes Mellitus. ② Exploring the Gene-set Network In the result panel, the gene-set network graph is displayed, and the gene-set clusters are represented by different colors (fig. 5). Gene-sets included in multiple clusters are colored with dark gray. The detailed clustering result is represented as table in ‘Cluster info’ tab ( ), and users can save the result as text file by clicking ‘CLUSTERING_RESULT’ button below the result table. Figure 5. Result panel. Each number represents useful function introduced below. Functions 1. Graph control panel: Users can zoom in/out or move the graph by simple mouse control or using graph control panel ( in fig 5) in the top left of the result panel. 2. Gene-set search: To find a specific gene-set node, type a search word in Gene-set search box ( in fig 5), select target gene-set, and click ‘Search’ button. Then corresponding gene-set node will be located at the center of the result panel (fig. 6). Figure 6. Search for the position of a gene-set node 3. Layout option: Click ‘Layout Option’ button ( in fig 5) and choose circle or cola layout (fig. 7). Figure 7. Circle (left) and Cola (right) layout 4. Download Graph: Users can download a vector image file (.SVG) for current plot by clicking ‘Download Graph’ button ( in fig 5). 5. Clustering Options: The distance type, minimum seed size and maximum distance allowed between gene-sets can be set in ‘Clustering Options’ ( in fig 5). After setting these parameters, click ‘APPLY’ to change the gene-set network graph. We present detailed explanation for each parameter. Figure 8. Clustering Options and Distance Converter Distance type ✓ MM: Meet/Min distance (MM) is defined for two gene-sets A and B as: 𝑀𝑀(𝐴, 𝐵) = 1 − |𝐴 ∩ 𝐵| 𝑚𝑖𝑛(|𝐴|, |𝐵|) Where |A| is the size of A. ✓ pMM: PPI weighted Meet/Min (pMM) is defined as: 𝑝𝑀𝑀(𝐴) = 1 − [ |𝐴 ∩ 𝐵| 𝑤 ∑𝑦∈𝐴∩𝐵 𝑃(𝑥, 𝑦) + ∑𝑦∈𝐵−𝐴 𝑃(𝑥, 𝑦) 1 + ∑ ] min(|𝐴|, |𝐵|) min(|𝐴|, |𝐵|) ∙ max(𝑃) 𝑤|𝐴 ∩ 𝐵| + |𝐵 − 𝐴| 𝑥∈𝐴−𝐵 Where P is PPI score matrix, P(x,y) is PPI score of two genes x and y, and 𝑤= |𝐴| , 𝑖𝑓 |𝐴| ≤ |𝐵| |𝐴|+|𝐵| { |𝐵| , 𝑜𝑡ℎ𝑒𝑟𝑤𝑖𝑠𝑒 |𝐴|+|𝐵| And pMM(B) is symmetrically defined, Then, 𝑝𝑀𝑀(𝐴, 𝐵) = min(𝑝𝑀𝑀(𝐴), 𝑝𝑀𝑀(𝐵)) ✓ Kappa: 1-Cohen’s Kappa distance is defined as: 𝐾𝑎𝑝𝑝𝑎(𝐴, 𝐵) = 1 − 𝑂−𝐸 1−𝐸 Where 𝑂 = |𝐴∩𝐵|+|(𝐴∪𝐵)𝑐 | |𝑈| (U=list of total genes) is the observed rate of agreement of two gene-sets, and 𝐸 = |𝐴|∙|𝐵|+|𝐴𝑐 |∙|𝐵 𝑐 | |𝑈|2 is the expected rate of agreement of two gene-sets. The default distance is pMM with a cutoff (minimum seed distance) that corresponds to same percentile as MM=0.5. For example, if 0.5 ranks the top 1% among all the MM scores, the top 1% pMM score is set as default. Minimum seed size: The minimum cluster size allowed. Default = 3. Maximum Distance: Maximum distance between gene-sets to be connected. The default value is described above. Distance converter: For user convenience, we also provide distance converter. For example, to identify the Kappa distance matched to MM=0.5, select MM in ‘From’ box, type 0.5 below, select Kappa in ‘To’ box, and then click ‘Transform’ button. Then corresponding Kappa distance will be represented. 6. Gene Network GSnet provides gene network plot of each cluster based on STRING human PPI data. For example, if you want to see the gene network in cluster 4, do as follows: ① Click the ‘Gene Network’ button ( in fig 5). ② Choose the cluster number (‘4’ in this case) from ‘Gene Network in Cluster’ box. ③ Set the PPI cutoff (default=700) ④ Select edge type. We provide 8 edge types such as A. Combined PPI score (The stronger PPI, the thicker an edge is) B. Neighborhood C. Gene fusion D. Co-occurrence E. Co-expression F. Experiments G. Databases H. Text mining Detailed explanation for each PPI evidence type is described in STRING web page https://string-db.org/cgi/help.pl . ⑤ Click ‘Draw Gene Network’ button. Then it will show the network for genes in cluster 4 with selected edge types (fig 9). Figure 9. Gene network for a specific cluster Hub gene: To find top-ranked hub genes in selected cluster, just type degree rank in the box below (Find hub gene with DEGREE rank<=; default=3) and click ‘Search’. To see the gene-set network again, click ‘Reset’ button. 7. Hub If the user clicks the ‘Hub’ button ( in fig 5) and type a degree rank N in the box, the genes within N-degree rank for at least two clusters will be listed (fig. 10). We expect that such genes have multiple biological roles related to the phenotype . Figure 10. Hub genes observed in at least two clusters
Source Exif Data:
File Type : PDF File Type Extension : pdf MIME Type : application/pdf PDF Version : 1.7 Linearized : No Page Count : 6 Language : en-US Tagged PDF : Yes XMP Toolkit : 3.1-701 Creator : Microsoft Office User Creator Tool : Microsoft Word Create Date : 2018:07:12 12:48:02+00:00 Modify Date : 2018:07:12 12:48:02+00:00 Document ID : uuid:CA327204-2B6D-4253-8D09-A8C7291E5E9C Instance ID : uuid:CA327204-2B6D-4253-8D09-A8C7291E5E9C Author : Microsoft Office UserEXIF Metadata provided by EXIF.tools