In the Table format, the dose-response data is represented as a long table where each row represent one observation in the dose-response matrix (Fig.1).
Fig.1 Input file in Table format.
The input table must contain the following columns (The column naming style used in the old SynergyFinder or DrugComb, i.e. ‘Alternative Column names’ are accepted):
| Required Columns |
Alternative Column names |
Description |
| block_id |
PairIndex, BlockId |
Identifier for the drug combination blocks. |
| drug1 |
Drug1, drug_row, DrugRow |
Name of the first tested drug. |
| drug2 |
Drug2, drug_col, DrugCol |
Name of the second tested drug. |
| conc1 |
Conc1, conc_row, ConcRow |
Concentration of first tested drug. |
| conc2 |
Conc2, conc_col, ConcCol |
Concentration of second tested drug. |
| response |
Response, inhibition, Inhibition |
Cell response to the drug treatment (%inhibition or %viability). |
| conc_unit |
ConcUnit |
Unit of concentration for drugs. This column could be replaced by multiple separated columns for each tested drugs (see table below), while different unit was used for measuring the concentrations. |
| Optional Columns |
Alternative Column names |
Description |
| conc_unit1 |
conc_r_unit |
Unit of concentration for the first drug. Used if the concentration units are not identical across the drugs tested in one block. |
| conc_unit2 |
conc_c_unit |
Unit of concentration for the second drug. Used if the concentration units are not identical across the drugs in test one block. |
| drug[n] |
|
Name of the n_th_ tested drug. For example, “drug3” for the third tested drug. Used for higher-order drug combination data point. |
| conc[n] |
|
Concentration of n_th_ tested drug. Used for higher-order drug combination data point. |
| conc_unit[n] |
|
Unit of concentration for n_th drug. Used if the concentration units are not identical across the drugs in test one block. |
| cell_line_name |
|
Name of the cell line. The cell line names will be used for “data annotation”. |
Note:
- The duplicated concentration combinations in one block (with the same “block_id”) will be treated as replicates.
- There is no restriction on the number of drug combinations for the input file. The data should however, contain at least three concentrations for each drug, so that sensible synergy scores can be calculated.
- SynergyFinder allows for missing values in the dose-response matrix. The missing value will be automatically imputed by mice R package.
In the Matrix format, the dose-response matrix is represented in a matrix with drug concentrations shown along the left (for Drug1) and top (for Drug2) edges of the matrix (Fig.2). The three rows below should precede each dose-response matrix:
- Drug1 name of the first drug
- Drug2 name of the second drug
- ConcUnit unit of concentration
Fig.2 An input file in Matrix format. Two dose-response matrices are provided as an example.
Note:
- Matrix format only works on 2 drug combination data. Please use table format for combinations with more than 3 drugs.
- The drug concentrations should be located at the top and left side of the matrix, where concentrations located at the left side correspond to Drug1 and concentrations located at the top correspond to the Drug2.
- There is no restriction on the number of drug combinations for the input file. The data should however, contain at least three concentrations for each drug, so that sensible synergy scores can be calculated.
- SynergyFinder allows for missing values in the dose-response matrix. The missing value will be automatically imputed by mice R package.
SynergyFinder accepts following file formats:
- EXCLE file with extension “.xlsx”
- comma-delimited CSV file, with extension “.csv”
- tab-delimited TXT file, with extension “.txt”
1.3 Example Data
SynergyFinderPlus provides 3 example data:
-
ONEILTable: It is an example data in table format for 2-drug combinations with 4 replicates. The is information extracted from a pan-cancer drug screening study [O’Neil et al. 2016]. It contains two representative drug combinations (MK-1775 & Niraparib and Paclitaxel & L-778123 free base) for which the %inhibition of a cell line OCUBM and NCIH2122 was assayed using a 5 by 5 dose matrix design with four replicates.
-
ONEILMatrix: It is an example data in matrix format for 2-drug combinations without replicates. The data resource is the sample as previous example data. The %inhibition value in the matrix are the average response value from 4 replicates.
-
NCATSTable: It is an example data in table format for 3-drug combinations without replicate. The information is extracted from a triple drug screening study on malaria [Ansbro et al. 2020]. It contains two representative drug combinations (Piperaquine & Pyronaridine Tetraphosphate & Darunavir Ethanolate and Piperaquine & Pyronaridine Tetraphosphate & Lopinavir) for which the %inhibition of malaria was assayed using a 10 by 10 by 12 dose matrix design with four replicates.
User can directly upload these data sets or download all of them in 3 different file formats (xlsx, csv, and txt) on the websites (see Fig3).
The files are also downloadable from here.
2 Upload File
The “Upload Data” tab is designed for user to upload file. Figure 3 shows the user interface.
Fig.3 User Interface of the "Upload Data" tab
- Choose the data format used in the uploaded file. Please check section “1.1 Data Format” for more details.
- Select the file to upload from your local directory. Please check section “1 Prepare Input Data” for more details. Alternatively you can select one of the example data tables from the dropdown list for analysis.
- Choose the phenotypic response metric of uploaded drug combinations. Available options in SynergyFinder are:
inhibition (% inhibition to cell growth or other signals. Normalized by negative control.)
viabillity (% cell viability after treatment. Normalized by negative control. In case of %viability response type, the provided %viability values will be converted to %inhibition by the formula: \(\%inhibition = 100 - \%viability\).)
Once a response type is selected, a new tab “Dose Response Map” will be shown in the left sidebar. User could click it to visualize dose-response map (see the next page of the user guide).
- A button to download the example data. The example data sets include 2 drug combination screening data, 3 drug combination screening data.
- A switch for data annotation. It will be shown once the data is successfully uploaded.By turning it on, the program will query the external databases the annotate the drugs and cell lines in the input data table.
- The overview for the input data in table format. It will be shown while the file is successfully uploaded and formatted.
3. Annotation
SynergyFinder provides three tables for annotation(Fig.4):
Fig.4 Annotation for drug and cell line
Drug Information: It contains the basic information for drugs tested in input data tables. It includes columns:
-
Drug Name: The name for drugs in the input data table.
-
InChIKey: They The IUPAC International Chemical Identifier for drugs. (Information from PubChem.[Kim et al., 2021])
-
Isomeric SMILES: The isomeric SMILES for drugs from input data table. (Information from PubChem.[Kim et al., 2021])
-
Molecular Formula: The molecular formula for the drugs. (Information from MICHA[Tanoli et al., 2021])
-
Max Phase: The maximum phase for clinical trial for the compounds (drugs) in input data table. (Information from MICHA[Tanoli et al., 2021])
- 0: Compound has not yet reached phase I clinical trials
- 1: Compound has reached phase I clinical trials
- 2: Compound has reached phase II clinical trials
- 3: Compound has reached phase III clinical trials
- 4: Compound has been approved in at least one country/area
-
Cross Reference: The drug identifiers used in other databases (PubChem, BindingDB, chEMBL, DrugBank, PharmGKB, Guide to Pharmacology, ChEBI, Selleck, ZINC). Clicking on the IDs directs user to corresponding drug pages on the external databases.
-
Disease Indication: The drug is used to treat these diseases. (Information from MICHA[Tanoli et al., 2021])
Drug Target Information: It contains the information for drug targets. It includes columns:
- Drug Name: The name for drugs in the input data table.
- InChIKey: They The IUPAC International Chemical Identifier for drugs. (Information from PubChem.[Kim et al., 2021])
- Primary Target Name: The name for the primary target of the drug. (Information from MICHA[Tanoli et al., 2021])
- Primary Target ID: The UniProt ID for the primary target of the drug. (Information from MICHA[Tanoli et al., 2021])
- Potent Target Name: The potent targets are defined as the targets displaying binding affinities <= 1,000 nM from the bioactivity databases, or targets recorded in the unary databases. The information comes from MICHA, which integrates the data from 6 databases: DTC, chEMBL, BindingDB, DrugBank, Guide to Pharmacology, DGIdb. (Information from MICHA[Tanoli et al., 2021])
Cell Line Information: It contains the information about the cell line from Cellosaurus database.[Bairoch, 2018] It shows only when the cell line names are included in the input data table. It includes columns:
- Cell Name: The cell line name extracted from input data table.
- Synonyms: The synonyms for cell line
- Cellosaurus Accession: The identifier for cell lines used in Cellosaurus
- Tissue: The tissue from which cell line is collected
- Disease Name: The disease from which cell line is collected
- Disease NCIt ID: The NCI Thesaurus (NCIt) for the disease
Reference
[Bairoch, 2018] Bairoch,A. (2018) The Cellosaurus, a Cell-Line Knowledge Resource. J Biomol Tech, 29, 25–38.
[Kim et al., 2021] Kim,S., Chen,J., Cheng,T., Gindulyte,A., He,J., He,S., Li,Q., Shoemaker,B.A., Thiessen,P.A., Yu,B., et al. (2021) PubChem in 2021: new data content and improved web interfaces. Nucleic Acids Research, 49, D1388–D1395.
[O’Neil et al. 2016] O’Neil, Jennifer, Yair Benita, Igor Feldman, Melissa Chenard, Brian Roberts, Yaping Liu, Jing Li, et al. 2016. “An Unbiased Oncology Compound Screen to Identify Novel Combination Strategies.” Molecular Cancer Therapeutics 15 (6): 1155–62.
[Tanoli et al., 2021] Tanoli,Z., Aldahdooh,J., Alam,F., Wang,Y., Seemab,U., Fratelli,M., Pavlis,P., Hajduch,M., Bietrix,F., Gribbon,P., et al. (2021) Minimal information for Chemosensitivity assays (MICHA): A next-generation pipeline to enable the FAIRification of drug screening experiments. bioRxiv, 10.1101/2020.12.03.409409.
