Pre-filtered GCaMP calcium activity waveforms

Description

A dataset containing calcium activity and observed times during a behavioral paradigm pilot study; organized into 10 individual trials

Usage

data(GCaMP)

Format

A data frame with 11 rows and 814 columns

Time

observed times of Trial.n values, in seconds

Trial.n

values of calcium activity signals for trial n

...

Source

Dr. David Root, Maier-Watkins laboratory

Averages signals across trials

Description

'averaged_trials' averages values over each time point, across the specified trials

Usage

averaged_trials(Dataframe, Trials)

Arguments

Value

a data frame with observation times and averaged values

Examples

### Format data frame
df.new <- format_data(GCaMP)

### Plot the average fluorescence signal across trials 1-5
df.1thru5 <- averaged_trials(df.new, 1:5)

plot(x = df.1thru5$Time, df.1thru5$Values)

Get average curve slopes

Description

'avg_curve_slope' finds the average curve slopes for a trial using inflect_points_df and lm

Usage

avg_curve_slope(Dataframe, Trial)

Arguments

Value

vector of average rate of change for each curve

Note

curves of a single value will result in the average slope being labeled as NA

Examples

df.new <- format_data(data = GCaMP)
avg_curve_slope(Dataframe = df.new, Trial = 1)

Compare mean activity between trials

Description

'between_trial_change' finds the difference in means during same time range between sets of trials.

Usage

between_trial_change(Dataframe, TrialRange1, TrialRange2,
  Time.period = c(min(Dataframe[1]), max(Dataframe[1])))

Arguments

Value

Number representing mean difference of trial set 2 and trial set 1

Examples

# How much did the mean value change 2s after epoc between trials 1-5 and trials 6-10?
df.new <- format_data(data = GCaMP)
between_trial_change(Dataframe = df.new, TrialRange1 = c(1, 5),
TrialRange2 = c(6, 10), Time.period = c(0, 2))

Compute centered area under curve

Description

'centered_AUC' computes the area under the curve (AUC) after centering values using a specified function, such as mean or min. Computed using trapezoidal integration.

Usage

centered_AUC(Dataframe, Trial, FUN = mean)

Arguments

Value

Data frame of AUCs and curve number for each curve

Examples

# Get AUCs for trial 2, centered at the mean
df.new <- format_data(data = GCaMP)
centered_AUC(Dataframe = df.new, Trial = 2, FUN = mean)

Compare mean activity in consecutive trials

Description

'consecutive_trial_change' finds the change in means between consecutive trials.

Usage

consecutive_trial_change(Dataframe, Trials, Time.period)

Arguments

Value

Data frame with the "Mean.Change" column representing differences in means between trial n and trial n + 1 for the user-inputted range of trials.

Examples

### How much did the mean value change after epoc between consecutive trials in trials 1-10?
df.new <- format_data(data = GCaMP)
consecutive_trial_change(Dataframe = df.new, Trials = c(1, 10), Time.period = c(0, 4))

Get peaks/valleys in waveform data

Description

‘find_peaks' finds peaks or valleys in waveform by using inflection points, with filter of ’n' increasing/decreasing points on both sides of each inflection point.

Usage

find_peaks(x, n.points = 3)

Arguments

Value

a numeric vector of indices

Examples

### Format data frame
df.new <- format_data(GCaMP)

### How many peaks are there in trial 1 with 10 decreasing data points on each side?
peak.indices <- find_peaks(df.new$Trial1, n.points = 10)

### When do they occur?
data.frame(times = df.new$Time[peak.indices], vals = df.new$Trial1[peak.indices])

Reformat and label data into GCalcium format

Description

'format_data' changes the format of data from wide time series to long format with labeled columns. If data is already in long format, the function simply re-labels the columns

Usage

format_data(data)

Arguments

Value

Data frame with labeled time and trial columns

Examples

df.new <- format_data(GCaMP)

Find inflection pooints

Description

'inflect_points' finds inflection points of waveform data

Usage

inflect_points(x)

Arguments

Value

Inflection points of the input vector

Examples

df.new <- format_data(GCaMP)
inflect_points(df.new$Trial1)

Find inflection points and curve numbers

Description

'inflect_points_df' finds inflection points of activity waves, returning a summarized data frame

Usage

inflect_points_df(Dataframe, Trial)

Arguments

Value

data frame with variables indicating the time, raw values, curve numbers, and inflection points corresponding to each data point of the input

Examples

df.new <- format_data(GCaMP)
inflect_points_df(Dataframe = df.new, Trial = 1)

Summarize data within windows of time

Description

'moving_window' summarizes data within windows of a certain length.

Usage

moving_window(Dataframe, Trial, Window.length, FUN = mean)

Arguments

Value

a data frame with start and stop times of each window, the chronological number of each window, and summarized values

Examples

### Format data frame
df.new <- format_data(GCaMP)

### In trial 5, how does the average fluorescence change in 1 second time frames?
moving_window(Dataframe = df.new, Trial = 5, Window.length = 1, FUN = mean)

Find the percent change from baseline

Description

'perc_baseline' calculates the percent change from a user-specified baseline period

Usage

perc_baseline(Dataframe, Baseline.times, Baseline.frame = FALSE)

Arguments

Value

a GCalcium-format data frame with values transformed to percent baseline

Examples

### Format data frame
df.new <- format_data(GCaMP)

### Transform into percent baseline: relative to -3s to -1s before epoc
perc_baseline(Dataframe = df.new, Baseline.times = c(-3, -1))

Plot specified trials

Description

'plot_trials' plots the user-inputted trials. This function automatically adjusts the x- and y- axis limits to fit all data

Usage

plot_trials(Dataframe, Trials, ...)

Arguments

Value

a single plot of user-specified trials

Examples

### Format data frame
df.new <- format_data(GCaMP)

### Specify and plot trials
my.trials <- c(1, 2, 7, 8)
plot_trials(Dataframe = df.new, Trials = my.trials)

Get mean activity change within a trial

Description

'within_trial_change' finds the change in mean values between beginning and end of entered time range.

Usage

within_trial_change(Dataframe, Trial, Beg.period = FALSE,
  End.period = FALSE)

Arguments

Value

vector with AUC for each curve in a trial

Examples

# In trial 1, how much did the mean value change between -2s and 0s, and 0 and 2s?
df.new <- format_data(data = GCaMP)
within_trial_change(Dataframe = df.new, Trial = 1, Beg.period = c(-2, 0), End.period = c(0, 2))

Transform values into z scores

Description

'z_score' transforms input values to z scores. Allows user input of mu and sigma values for comparing distributions.

Usage

z_score(xvals, mu = FALSE, sigma = FALSE)

Arguments

Value

a numeric vector of z scores

Examples

# Format data
df.new <- format_data(GCaMP)

# Split data
basevals <- df.new$Trial1[df.new$Time <= 0]
eventvals <- df.new$Trial1[df.new$Time > 0]

# Find baseline (pre-epoc) values
base.mu <- mean(basevals)
base.sigma <- sd(basevals)

# Compute values
z_score(x = eventvals, mu = base.mu, sigma = base.sigma)