R Dataset / Package datasets / Puromycin

How To Create a Barplot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Visual
Instructional

How To Create a Stacked Barplot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Visual
Instructional

How To Create a Pie Chart

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Instructional
Visual

How To Compute the Mean

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Numerical
Instructional

How To Create a Plot

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Visual
Instructional

How to Compute the Median

The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Category
Instructional
Numerical

Boxplot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Correlation Coefficient

Submitted by pmagunia on April 22, 2018 - 3:08 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Cumulative Frequency Histogram

Submitted by pmagunia on April 22, 2018 - 3:09 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Dotplot

Submitted by pmagunia on April 22, 2018 - 3:10 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Hollow Histogram

Submitted by pmagunia on April 22, 2018 - 3:10 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Numerical Summaries

Submitted by pmagunia on April 22, 2018 - 2:51 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Pie Chart

Submitted by pmagunia on April 22, 2018 - 3:11 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Plot

Submitted by pmagunia on April 22, 2018 - 3:07 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Ratio

Submitted by pmagunia on December 18, 2021 - 4:28 PM

Regression

Submitted by pmagunia on April 22, 2018 - 3:12 PM

Stem and Leaf Plots

Submitted by pmagunia on April 22, 2018 - 3:12 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.

Visual Summaries

Submitted by pmagunia on April 22, 2018 - 3:13 PM
The Drupal File ID of the selected dataset. The user may load another using the search bar on the operation's page.
Submitted by pmagunia on March 9, 2018 - 1:06 PM
<iframe src="https://embed.picostat.com/r-dataset-package-datasets-puromycin.html" frameBorder="0" width="100%" height="307px" />
Attachment Size
dataset-22769.csv 470 bytes
Dataset License
GNU General Public License v2.0
Documentation License
GNU General Public License v2.0
Documentation

On this Picostat.com statistics page, you will find information about the Puromycin data set which pertains to Reaction Velocity of an Enzymatic Reaction. The Puromycin data set is found in the datasets R package. Try to load the Puromycin data set in R by issuing the following command at the console data("Puromycin"). This may load the data into a variable called Puromycin. If R says the Puromycin data set is not found, you can try installing the package by issuing this command install.packages("datasets") and then attempt to reload the data with library("datasets") followed by data("Puromycin"). Perhaps strangley, if R gives you no output after entering a command, it means the command succeeded. If it succeeded you can see the data by typing Puromycin at the command-line which should display the entire dataset.

If you need to download R, you can go to the R project website. You can download a CSV (comma separated values) version of the Puromycin R data set. The size of this file is about 470 bytes.


Reaction Velocity of an Enzymatic Reaction

Description

The Puromycin data frame has 23 rows and 3 columns of the reaction velocity versus substrate concentration in an enzymatic reaction involving untreated cells or cells treated with Puromycin.

Usage

Puromycin

Format

This data frame contains the following columns:

conc

a numeric vector of substrate concentrations (ppm)

rate

a numeric vector of instantaneous reaction rates (counts/min/min)

state

a factor with levels treated untreated

Details

Data on the velocity of an enzymatic reaction were obtained by Treloar (1974). The number of counts per minute of radioactive product from the reaction was measured as a function of substrate concentration in parts per million (ppm) and from these counts the initial rate (or velocity) of the reaction was calculated (counts/min/min). The experiment was conducted once with the enzyme treated with Puromycin, and once with the enzyme untreated.

Source

Bates, D.M. and Watts, D.G. (1988), Nonlinear Regression Analysis and Its Applications, Wiley, Appendix A1.3.

Treloar, M. A. (1974), Effects of Puromycin on Galactosyltransferase in Golgi Membranes, M.Sc. Thesis, U. of Toronto.

See Also

SSmicmen for other models fitted to this dataset.

Examples

require(stats); require(graphics)plot(rate ~ conc, data = Puromycin, las = 1,
     xlab = "Substrate concentration (ppm)",
     ylab = "Reaction velocity (counts/min/min)",
     pch = as.integer(Puromycin$state),
     col = as.integer(Puromycin$state),
     main = "Puromycin data and fitted Michaelis-Menten curves")
## simplest form of fitting the Michaelis-Menten model to these data
fm1 <- nls(rate ~ Vm * conc/(K + conc), data = Puromycin,
           subset = state == "treated",
           start = c(Vm = 200, K = 0.05))
fm2 <- nls(rate ~ Vm * conc/(K + conc), data = Puromycin,
           subset = state == "untreated",
           start = c(Vm = 160, K = 0.05))
summary(fm1)
summary(fm2)
## add fitted lines to the plot
conc <- seq(0, 1.2, length.out = 101)
lines(conc, predict(fm1, list(conc = conc)), lty = 1, col = 1)
lines(conc, predict(fm2, list(conc = conc)), lty = 2, col = 2)
legend(0.8, 120, levels(Puromycin$state),
       col = 1:2, lty = 1:2, pch = 1:2)## using partial linearity
fm3 <- nls(rate ~ conc/(K + conc), data = Puromycin,
           subset = state == "treated", start = c(K = 0.05),
           algorithm = "plinear")

--

Dataset imported from https://www.r-project.org.
Picostat Manual
How To Register With a Username
  1. Go to the user registration page.
  2. Enter a username and email address into the form.
  3. Answer the ReCaptcha (this is used to prevent spam).
  4. Click Submit.
  5. Click the link that was sent to the email address you registered with.
  6. Clicking the link will open another page on Picostat where you can select a password.
  7. Click Save and enter any profile details you wish to enter.
How To Register With Google Single Sign On (SSO)
  1. Go to the user login page.
  2. Click the Google button that says "Sign in with Google". This will redirect you to a page controlled by Google.
  3. Enter your Google username and password if you are not already authenticated.
  4. Review the Picostat Terms of Use and Privacy Policy. Then submit the Google form if you accept the terms.
  5. Google will redirect you back to Picostat with your new account created and you will be logged in.
  6. Enter any profile details you wish to share.
How To Login With a Username and Password
  1. Go to the user login page.
  2. Enter your username and password that you registered with.
  3. Click "Login". You will be redirected to your user homepage authenticated.
How To Login With Google Single Sign On (SSO)
  1. Go to the user login page.
  2. Click the button that says "Sign in with Google".
  3. If you already registered with Picostat via Google SSO, you will be redirected to your user homepage authenticated.
How To Import a Dataset
  1. Create a Picostat account or login with your existing picostat account (see above).
  2. Go to the dataset import page.
  3. Select a license for the dataset. The default is "No License" but allows Picostat to host a copy of the dataset as per the privacy policy. You may wish to uncheck the "Public" option if you do not wish to share your dataset with others. R Datasets that come by downloading R have a GNU General Public License v3.0 which may also be selected from the Picostat dropdown.
  4. Enter a title for the dataset
  5. Choose a dataset input methods. Available options include:
    • Random data - this populates your dataset with random numbers between 0 and 100. You can specify the number of rows and columns for the random dataset.
    • CSV, TSV or TXT file - you will have the option upload a file within the current file size limit and also specify the header and whether or not the dataset is a contingency table. With contingency tables, the first column becomes a label for the rows. Currently with Picostat, there is limited support for contingency tables. Choose "Yes" to the Header option if the first line of the data contains titles for the rows. Also choose the Separator for the dataset. A separator is what breaks the data up. In some cases, a comma would separate data values in a row. You will also have the option to add documentation in the form keyboarded text and also uploaded documentation attachments. You can also specify a license for the documentation.
    • Copy and Paste. This selection contains many of the same fields as importing a file with an additional textarea to copy and paste data to.
    • Empty dataset. Start with a blank dataset and manually add data with the Picostat dataset editor.
    • Excel file - Choose this option if you would like to convert your Excel spreadsheet to a Picostat dataset. With this selection, you will have the option to specify whether to use the first row in the Excel file as column names. If you would like to choose a specific sheet to use, you can also specify with entering its name in the text input.
    • sas7bdat file - SAS is a powerful statistical software package that has its own proprietary file format. Choose this option if you are importing a SAS file.
    • SPSS sav file - SPSS is a statistical package owned by IBM. You can import SPSS files by choosing this option.
  6. Choose whether or not the dataset contains a header. Some of the dataset input methods allow you to specify whether or not a Header exists on the file. Sometimes dataset files contain a Header as the first row which names the columns. If you choose "Yes" to this, the first row in the dataset will become column headers.
  7. You can also add documentation and specify a documentation license. This can be used to help explain your dataset to those unfamiliar with it.
  8. Choose whether or not to upload an supporting attachments.
  9. Pass the captcha. To prevent spam submissions, Picostat has a captcha which is used to prevent automated submissions by bots.
  10. Choose a privacy setting for the dataset. You can also specify whether or not the dataset is Public. If you uncheck this setting, only you and the Picostat administrator will be able to view the dataset.
  11. Submit the form. Once the form is validated, you will be redirected to the dataset homepage where you can choose to edit or perform statistical operations on the dataset.
How To Perform Statistical Analysis with Picostat
  1. Go to any dataset homepage. You can get a full list at the dashboard.
  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Analyis. Choose from one of the following:
    • Numerical Summaries - Here you can get the:
      1. Arithmetic mean
      2. Median
      3. Quartiles
      4. Minimum and Maximum
      5. Stem-and-leaf plot
      6. Standard deviation and Variance
      7. IQR
      8. Cumulative frequencies
    • Plot - a plot of two columns on the cartesian coordinate system
    • Boxplot - a Boxplot (box-and-whisker plot) of a column.
    • Correlation Coefficient - Compute the correlation coefficient between two columns.
    • Cumulative Frequency Histogram - Display a cumulative frequency histogram
    • Dotplot
    • Hollow Histogram - Plot two columns on the same histogram with a different color for each column.
    • Pie Chart
    • Regression - Perform a simple linear regression and compute the p-value and regression line. Also plots the data with the regression line.
    • Stem and Leaf Plots - Plot a one or two-sided stem-and-leaf plot from one or two columns respectively.
    • Visual Summaries - plots the following:
      1. Frequency Histogram
      2. Relative Frequency Histogram
      3. Cumulative Frequency Histogram
      4. Boxplot (Box-and-whisker plot)
      5. Dotplot
  3. PDF - Check this box if you want to download a PDF of the output from the statistical analysis application.
  4. HTML - Check this box if you want a link to the HTML page created with the application.
  5. R File - Check this box if you want a link to download the R commands used to generate output from this statistical application. You should be able to copy the commands verbatim into R Studio or R to recreate the analysis.
How To Use Educational Applications with Picostat
  1. Go to any dataset homepage. You can get a full list at the dashboard.
  2. Near the top of the page there will be two drop downs. One for analysis and one for education. Here we will choose Education. Choose from one of the following:
    • How To Create a Barplot - This will show you how to create a bar chart after selecting a column with the mouse.
    • How To Create a Stacked Barplot - This application will show you how to create a stacked bar plot from a column vector.
    • How To Create a Pie Chart - This application will show you how to create a pie chart from a column of data
    • How To Compute the Mean - This application will show you how to compute the mean from a column vector
    • How To Create a Plot - This app will show you how to plot two columns in the cartesian coordinate system.
    • How To Compute the Media - This statisistical app will show you how to compute the median from a column vector.
  3. PDF - Check this box if you want to download a PDF of the output from the education application.
  4. HTML - Check this box if you want a link to the HTML page created with the application.
Recent Queries For This Dataset

No queries made on this dataset yet.
Title Authored on Content type
R Dataset / Package gap / PD March 9, 2018 - 1:06 PM Dataset
R Dataset / Package Zelig / klein March 9, 2018 - 1:06 PM Dataset
R Dataset / Package robustbase / heart March 9, 2018 - 1:06 PM Dataset
R Dataset / Package wooldridge / return March 9, 2018 - 1:06 PM Dataset
muskducks December 8, 2022 - 12:09 PM Dataset
Title
Tutorial: How healthy is the Starbucks menu?
Tutorial: Which Animal Has the Highest Brain To Body Weight Ratio?
Picostat Manual
Title Link
Quiz: Brain To Body Weight Ratio

Requires login.
Quiz: Analysis of the Starbucks menu

Requires login.