1. Filter

       i.      Cell Lines Selection Panel
       ii.     Domain Specific Filters

2. Genomic Features

       i.      Available Cell Lines
       ii.     Mutations
       iii.    Copy Number Variations
       iv.     Expression Profiles
       v.      Pathways

3. Drugs

       i.      Databases
       ii.     Line Graph
       iii.    Heatmap
       iv.     Value Table

4. Synthetic Lethality

       i.      Synthetic Lethal Interactions
       ii.     Synthetic Dosage Lethal Interactions

5. Search

       i.      Genes
       ii.     Drugs

1. Filter

        Top of each page contains a cell lines selection panel. Second panel is general filters specific to that page.
       i.      Cell Lines Selection Panel
Cell Lines Selection Panel
User can select all cell lines or its desired cell lines just by clicking on the cell line name. After complete selection of desired cell lines user have to press update button.


       ii.     Domain Specific Filters
Domain Specific Filters
These filters are different on each page specific to the data e.g. mutations can be filtered on the basis of mutation type, CNV can be filtered on the basis of Deletions or Amplification. Drugs display mode can be changed using these filters e.g. Line Graph, Heatmap or Value Tables.


2. Genomic Features

        Genomic Features is a dropdown menu of website. It further contains following information.
       i.      Available Cell Lines
Available Cell Lines
This section shows total number of available cell lines with necessary information. It includes total number of events related to this cell lines in each database and links to external databases. For example cell line "5637_URINARY_TRACT" has 131 mutations in CCLE, 3 mutations in GDSC, 117 CNV deletions, 85 CNV amplifications, gene expression is up-regulated in 1406 genes and down-regulated in 1141 genes. 24 drugs were tested on this cell line in CCLE and 99 drugs in GDSC. This cell line also have some information in other databases which may not be included in this database, links are available in respective column. Finally, the source of cell lines is shown in description.


       ii.     Mutations
Mutations
This section is about reported mutations of these cell lines. In filter panel one can select mutations of interest, e.g. Insertions or Deletions. The data available about mutations is Gene symbol, mutation types, protein change if applicable and position of mutation with reference and alternate alleles.


       iii.    Copy Number Variations
Copy Number Variations
This section have all copy number variation information, one can set cell line selection and filter panel according to research objectives. All analysis for CNV calculation was performed by broad for CCLE, "Segmentation of normalized log2 ratios (specifically, log2(CN/2)) was performed using the circular binary segmentation (CBS) algorithm". We considered values greater than 1 as amplifications and lower than 1 as deletions. Amplifications are shown in red color and deletions are shown in blue color.


       iv.     Expression Profiles
Expression Profiles
This section have all expression information, one can set cell line selection and filter panel according to research objectives. Expression values downloaded from CCLE are stored in database. All analysis for expression calculation was performed by broad for CCLE, "Gene-centric RMA-normalized mRNA expression data". As cell lines usually not contain normal tissue, so, up or down regulation is decided on the basis of remaining more than 1000 cell lines data of CCLE (Contains cell lines from all cancers). We considered up-regulation if its 15% more than average of all cell lines and down-regulation if it is 15% less than average of all cell lines. up-regulations are shown in red color and down-regulations are shown in blue color.


       v.      Pathways
Pathways
Pathway analysis is one of the most integral part of any genomic analysis, so, we included all pathways from KEGG. This database is capable of searching mutated genes in particular cell lines with respect of pathways. General table view displays pathway name and number of effected genes in particular cell line. For further details one can click on the name of the pathway which will show the list of genes effected and basic reason of inclusion.


3. Drugs

        Drugs is a dropdown menu of website, user can further select database of interest to check drug information in relevant database.
       i.      Databases

Currently, GDBC contains drug sensitivity data from 4 sources; i. CTRP, ii. GDBC, iii. CCLE, iv. In-house data (GDBC). Unfortunately, each group have their own experimental procedures and conditions, which limits from combining or comparing data among different databases.


       ii.     Line Graph
Line Graph
Line graph is a technique to display drug sensitivity data in different databases.


       iii.    Heatmap
Heatmap
Heatmap is a technique to display drug sensitivity data in different databases.


       iv.     Value Table
Value Table
Value Table is a technique to display drug sensitivity data (IC50 Values) in different databases.


4. Synthetic Lethality

        SL and SDL connections are taken from "Jerby-Arnon et al. (2014). Predicting Cancer-Specific Vulnerability via Data-Driven Detection of Synthetic Lethality. Cell 158, 1199-1209". We didn't used shRNA in our calculations, methods for calculation of values is mentioned below.

        Defining SL and SDL connections:
        Synthetic Lethality (SL): When gene 1 is inactive and gene 2 is essential for cell survival.
        Synthetic Dosage Lethality (SDL): When gene 1 is over-active and gene 2 is essential for cell survival.

        Calculation of SL connections
        Step 1 (Survival of Fitest):
        i.      Selecting genes less than -0.3 CNV
        ii.     Inactive group: Any cell lines that have SCNA < -0.3 and underexpressed OR It has deleterious mutation.
                  Made two groups in each pair based on gene A
                  - Active
                  - Inactive
                  To define "underexpressed", we used 10th bottom percentile across all CCLE samples (~1000 cell lines).
        iii.     Applied Shapiro test on data
                  - If P-Value < 0.05 used Wilcox Test
                  - If P-Value > 0.05 used T Test unless group has only 1 active cell line
                  For Shapiro Test: shapiro.test(data$Values)
                  For Wilcox Test or T Test: wilcox.test(data$Values ~ data$Status) or t.test(data$Values ~ data$Status)
        Step 2 (Co-expression Test)
        i.      Selecting gene pairs which have CNV data
        ii.     Applied one-way Spearman correlation test using R
                  - cor.test(data$Values, data$Status, method = "spearm", alternative = "g")
                  Extracted correlation and P-Values
        Step 3 (Combining P-Values)
        i.      Selecting common groups between Step 1 & 2
        ii.     Applied Fisher's test using R
                  combine.test(data$pValue, data$Size, method = "fisher")

        Calculation of SDL connections
        Step 1 (Survival of Fitest):
        i.      Selecting genes more than 0.3 CNV
        ii.     Over-active group: Any cell lines that have SCNA > 0.3 and overexpressed.
                  Made two groups in each pair based on gene A
                  - Over-active
                  - Normal
                  To define "overexpressed", we used expression > 90th percentile across all CCLE samples (~1000 cell lines).
        iii.     Applied Shapiro test on data
                  - If P-Value < 0.05 used Wilcox Test
                  - If P-Value > 0.05 used T Test unless group has only 1 active cell line
                  For Shapiro Test: shapiro.test(data$Values)
                  For Wilcox Test or T Test: wilcox.test(data$Values ~ data$Status) or t.test(data$Values ~ data$Status)
        Step 2 (Co-expression Test)
        i.      Selecting gene pairs which have CNV data
        ii.     Applied one-way Spearman correlation test using R
                  - cor.test(data$Values, data$Status, method = "spearm", alternative = "g")
                  Extracted correlation and P-Values
        Step 3 (Combining P-Values)
        i.      Selecting common groups between Step 1 & 2
        ii.     Applied Fisher's test using R
                  combine.test(data$pValue, data$Size, method = "fisher")
       i.      Synthetic Lethal Interactions
Synthetic Lethal Interactions
Synthetic Lethality (SL): When gene 1 is inactive and gene 2 is essential for cell survival. Detailed method for calculation is mentioned above


       ii.     Synthetic Dosage Lethal Interactions
Synthetic Dosage Lethal Interactions
Synthetic Dosage Lethality (SDL): When gene 1 is over-active and gene 2 is essential for cell survival.


5. Search

       i.      Genes
Search Gene
Search information of particular gene or list of genes. One need to enter the list of comma separated list of official gene symbols. It gives mutations, CNV and expression status of selected cell lines. If gene is target of any drug than drug is also mentioned in the table. Finally, last row shows all possible pathways in which searched genes are participating.


       ii.     Drugs
Search_Drugs
One can compare the sensitivity of different drugs tested against these cell lines. Enter the name of relevant drugs seperated by comma. Graphs are generated against IC50 values of searched drugs in selected cell lines. One can search in GDBC, CTRP, GDSC and CCLE using this option.