• Description
• Parameters
  • Working Directory
  • About Data
    • Time Points
    • Number of Replicates
  • Smoothing
    • Gaussian Process Variance Parameter
    • Gaussian Process Scale Parameter
  • Gene Set Analysis (GSA)
    • Biological Function Annotation Files
    • Enrichment Analysis FDR Cutoff
    • Minimum % of Genes to Consider a Pathway to Be Tested
    • Minimum Number of Genes For Hypothesis Testing
  • Select Data
    • Gene Name Column
    • mRNA Concentration Data
    • Data Input Form 1
    • Protein Expression Data
    • Data Input Form 2
  • MCMC Parameters
    • MCMC Burn-In
    • MCMC Thinning
    • MCMC Samples
• Output
  • General Output
  • GSA Output (if GSA had been checked)

PECA-R (Rate) is a model that separates estimation of rate parameters from absolute concentration data, approximating synthesis and degradation rates from via two assumptions. See manuscript for PECAplus for detailed descriptions.

NOTE: if the data was derived from SILAC experiments, use PECA-pS instead. If one has SILAC data but wishes to use PECA-R for analysis, one has to derive 'artificial' absolute concentrations by summing over the two channels (e.g. heavy and light).

NOTE: the degradation rates for each interval can be easily average over the entire time course and converted to half-lives using the following formula:

, where is the average degradation rate

Specifies the directory where input files, output matrices and plots produced by PECA will be saved. It can be specified manually by typing in the path or the folder can be provided by using the "Select" button.

Friendly Reminder: DO NOT SELECT DESKTOP as the tool produces MANY files

Specification of the time points in the datasets(default: 0 1 2 3 4 5). Time points can be in any units such as, minutes or hours, but units need to be the same across the entire list. They should be all numeric values, each separated by a whitespace.

Specification of the number of replicates in the datasets for mRNA data and label-free proteomics data (default: 1)

If checked, Gaussian Process (GP) smoothing will be applied to the datasets (default: unchecked).

Determines the variation of values from the mean (default 2.0). A small value will result in the function values changing quickly.

Scaling factor that determines the smoothness of the curve (default 1.0). A small value will result in a function that stays close to the mean value.

If checked, a time-dependent functional enrichment analysis will be performed on the output matrix of PECA, specifically on the change point score based on synthesis and degradation rates for PECA-pS and R. The result will be displayed as two additional output matrix - the first one for synthesis rates and the second one for degradation rates (default unchecked). The resulting matrix reports the biological functions whose members are up or down-regulated at specific time points.

Specifies the file path of the function annotation file that should be used for the time-dependent functional enrichment analysis.

File Format:

1. First column named as ‘Pathwayid’, specifying the pathway IDs, e.g. from Gene Ontology and Consensus Pathway DataBase
2. Second column named as the same name as gene name columns provided in the parameters, specifying the genes involved
3. Third column named as 'pathway', specifying the pathways involved

Defines the FDR cutoff for which enrichment analysis should use when analyzing biological functions at specific time points (default 0.05, i.e. 5%). The value of this parameter should lie between 0 and 1 (e.g., 0.05, 0.1, 0.2).

Specifies the minimum percentage of genes needed in the experimental data for a pathway to be analyzed (default 0). For instance, if 20% is specified, then at least 20 genes need to be present in the experimental data for a pathway of 100 genes. The value of this parameter should lie between 0 and 100.

Specifies the minimum number of significant genes (within the FDR cutoff) from the experimental data for a particular pathway to be reported (default 1). Anything below this number will be assigned a p-value of 1. The value of this parameter should be a positive integer.

The selected text column will be used as the gene ID identifiers in PECA analysis (default: first text column).

The selected expression/numerical columns that should be used as mRNA data (default: first third of expression/numeric columns).

The columns should be ordered by timepoints and then by replicate

Order:

• time point 1 replicate 1
• …
• time point N replicate 1
• time point 1 replicate 2
• …
• time point N replicate 2

Specification for the data input form of mRNA Concentration Data, i.e. what data transformation has been applied already (default: Raw).

• Raw: unprocessed, untransformed data.

• ln: log_e transformed data.

• log_2: log₂ transformed data.

• log_10: log₁₀ transformed data.

• log_custom: log_X transformed data, where X is a specified positive real value

The selected expression/numerical columns that should be used as 'artificial' protein expressions.

Same order as mRNA Data. The number of columns should also match mRNA Data.

Specification for the data input form of Data 1 (default: Raw).

Same as Data Input Form 1

PECA model parameters are estimated using a sampling-based algorithm called MCMC (Markov chain Monte Carlo), which requires the parameters below. All values should be positive integers.

Defines the iterations to be thrown away at the beginning of MCMC run, i.e. the burn-in period (default: 1000).

Defines the interval in which iterations of MCMC are recorded (default: 10).

Defines the total of number of post-burn-in samples to be recorded from MCMC (default: 1000).

The text column is the gene name column provided from Gene Name Column

The main/expression columns are the log_e transformed mRNA and protein expression data sets.

The numeric columns contain: RY, DY, signedCPSX, signedCPDX, FDR_SX, FDR_DX, where X indexes time point (i.e. X=1 refers to the second time point) and Y indexes time point interval starting from 0 (i.e. Y=0 refers to the interval between the first and second time points).

• RY is the synthesis rate for the time interval preceding the specified time point (e.g. if Y = 1, then the interval is between time point indices 1 and 2)

• DY is the degradation rate for the time interval

• signedCPSX is the change point score for synthesis rates

• signedCPDX is the change point score for degradation rates

• FDR_SX is the False Discovery Rate for synthesis rate

• FDR_DX is the False Discovery Rate for degradation rate

GSA Output produces two additional matrices. The first additional matrix is GSA analysis on synthesis rates and the second one on degradation rates. The two additional matrices follow the same format as described below.

The text column contains: the gene name column provided from Gene Name Column, GO_name, GO_id

• GO_name is the name of the Gene Ontology

• GO_id is the ID of the Gene Ontology

The numeric columns contain: MaxSig(Up), MaxSig(Down), Max(Both), GO_size, GO_size_background, Up(X), Down(X), Sig(X), where X indexes time points corresponding to signedCPSX

• MaxSig(Up) is the maximum value of -log₁₀(Up(X)) for all X

• MaxSig(Down) is the maximum value of -log₁₀(Down(X)) for all X

• Max(Both) is the maximum value of -log₁₀(Sig(X)) for all X

• GO_size is the number of genes in the pathway

• GO_size_background is the number of genes in the pathway that appears in the experimental data

• Up(X) is the p-value calculated from the number of up-regulated genes

• Down(X) is the p-value calculated from the number of down-regulated genes

• Sig(X) is the p-value calculated from the number of up and down-regulated genes