This page covers usage of this web application. For general information about MuSyC and frequently asked questions, see the About page.

Input data format

Users' data is uploaded in comma-separated value (CSV) format, using the Unicode UTF-8 encoding (the default across most software). The required columns and their contents are shown in the table below. Combinations are grouped based on drug1, drug2, and sample columns. Thus, multiple combinations can be uploaded in the same file and will be processed separately. The drug1.units and drug2.units are arbitrary but must be consistent within each combination.

Column Name Data Type Description yyyy-mm-dd Experiment date
drug1.conc Float Drug 1 concentration
drug2.conc Float Drug 2 concentration
effect Float Effect value (e.g., % viability, DIP rate)
sample String Sample name (e.g., name of cell line)
drug1 String Drug 1 name
drug2 String Drug 2 name
drug1.units String Drug 1 units (e.g., nM)
drug2.units String Drug 2 units (e.g., nM)
effect.95ci Float (optional) 95% confidence interval for effect value

Create an account

Go to Create an account. Please enter your email address and a choice of password. Your email address will be verified by sending an email with a clickable link. Click on this link, and you will then be able to log in to the site with your credentials.

Create a dataset

After logging in, click the Create dataset button. Fill out the form with each of the required fields:

After completing the form, click the "Create dataset" button on this page. The file will be uploaded and fitting tasks created for each drug combination. Depending on the dataset size and demand, this process make take a few seconds to several minutes. Do not navigate away from the page while the upload is in progress.

The Dataset Page

After a dataset upload is complete, you will see the dataset page. You can also return to the dataset page at any time by logging in and by clicking the dataset's name on the home page.

Each combination experiment is sent to a queue for processing. The processing step runs the MuSyC algorithm to fit the dose-response surface, and returns the relevant fitting parameters. For small datasets, this process typically only takes a few minutes, but this will vary depending on dataset size and server demand.

When the upload is complete, the web browser will redirect to a page showing the dataset name and a list of the combination experiments in a table. A progress bar indicates whether there are still fitting tasks queued, in progress, or completed. At the bottom of the page, there is a link to download the dataset's fitting parameters as a CSV file.

Each drug combination in the table shows the fitting algorithm's status (e.g., queued, started, success, failed). For successful tasks, clicking on the word "SUCCESS" will show the parameters for that combination, along with an interactive dose-response surface plot, which can be zoomed, panned, rotated etc. in the web browser. For tasks marked as "FAILED", clicking on that word will show more details about the error (e.g., if there was a data validation issue that the user should correct). There is also a link at the bottom of the task result page to download that single combination's parameters as a CSV file.

Parameter CSV file

The following table gives a description of each of the fields in the parameter CSV files.
sampleSample name
drug1_nameName of compound 1 (d1)
drug2_nameName of compound 2 (d2)
exptName of experiment
batchName of the batch (if applicable)
task_statusDid the task succeed?
converge_mc_nllsDid the Monte Carlo sampling converge? (1=True)
betaThe % increase of in the effect of the combination over the most efficacious single agent (based on fitted Emax). Beta = (min(E1,E2)-E3)/(E0-min(E1,E2))
beta_ciThe 95% confidence interval for beta based on Monte Carlo sampling
beta_obsThe observed % increase of in the effect of the combination over the most efficacious single agent (based value of fit at max tested conc.). Beta_obs = (min(E1_obs,E2_obs)-E3_obs)/(E0-min(E1_obs,E2_obs))
beta_obs_ciThe 95% confidence interval for beta_obs based on Monte Carlo sampling
log_alpha12Log of synergistic potency (drug1’s affect on potency of drug2). Values < 0 are antagonistically potent. Values >0 are synergistically potent. Alpha1 is quantifies the shift in the EC50 of drug 2 at saturating conc of d1.
log_alpha12_ciUncertainty in log_alpha1
log_alpha21Log of synergistic potency (drug2’s affect on potency of drug1). Values < 0 are antagonistically potent. Values >0 are synergistically potent. Alpha2 is quantifies the shift in the EC50 of drug 1 at saturating conc of d2.
log_alpha21_ciUncertainty in log_alpha2
R2R-squared of fit
log_like_mc_nllsLog likelihood of the parameter set
E0Fitted basal effect when [d1]=[d2]=0
E0_ciThe 95% confidence interval for E0
E1Fitted effect for [d1]->inf and [d2]=0
E1_ciThe 95% confidence interval E1
E2Value of fit at max tested conc. d1 and [d2]=0
E2_ciThe 95% confidence interval E1_obs
E3Fitted effect for [d2]->inf and [d1]=0
E3_ciThe 95% confidence interval E2
E1_obsValue of fit at max tested conc. d2 and [d1]=0
E1_obs_ciThe 95% confidence interval E2_obs
E2_obsFitted effect for [d1]->inf and [d1]->inf
E2_obs_ciThe 95% confidence interval E3
E3_obsValue of fit at max tested conc. d1 and d2
E3_obs_ciThe 95% confidence interval E3_obs
log_C1Log of the EC50 for drug 1
log_C1_ciUncertainty in log_C1
log_C2Log of the EC50 for drug 2
log_C2_ciUncertainty in log_C2
log_h1Log of the hill slope d1
log_h1_ci95% confidence interval of log_h1
log_h2log of hill slope d2
log_h2_ci95% confidence interval of log_h2
h1Hill slope d1
h2Hill slope d2
C1EC50 drug1
C2EC50 drug2
time_totalTime to fit
drug1_unitsDrug 1 units
drug2_unitsDrug 2 units
metric_namename of metric of drug effect
fit_betaWas Emax fixed such that beta=0? 1=Yes; 0=No
boundary_samplingWas boundary sampling fit used
max_conc_d1maximum tested concentration of drug 1
max_conc_d2maximum tested concentration of drug 2
min_conc_d1minimum tested concentration of drug 1
min_conc_d2minimum tested concentration of drug 2
fit_methodWhat method was used to fit the 2D Hill equation
dataset_nameName of dataset in MuSyC portal

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