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About Caroline

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So far Caroline has created 10 blog entries.

Chemical Screen: Evaluating drug sensitivity

The study of the cellular response to a chemical compound is crucial to the development of new therapeutic drugs. Such an analysis is usually done by a screen experiment where the disease-specific cells (such as leukemia primary cells) are exposed to chemical compound for different concentrations. The response, in the form of sensitivity, of these cells is conventionally quantified by the IC50 or the l’EC50. Here are some notions to keep in mind when we analyze these values.  IC50/EC50 : estimate of [...]

By | 2017-02-13T11:16:27+00:00 February 13, 2017|Categories: Data Analysis, Uncategorized|0 Comments

Bootstraps and Confidence Intervals

When analyzing data, you might want or need to fit a specific curve to a particular dataset. This type of analysis can result in instructive outputs regarding the relationship between two (or more...) quantifiable parameters. The main object of this post is not how to implement such fitting, but rather how to display the goodness of such a fit i.e. how to calculate a confidence interval around a fitted curve. That being said, I will show how to do curve fitting in [...]

By | 2016-11-08T09:30:03+00:00 September 29, 2016|Categories: Data Analysis, Data Visualization, R|1 Comment

SciPy and Logistic Regressions

Given a set of data points, we often want to see if there exists a satisfying relationship between them. Linear regressions can easily be visualized with Seaborn, a Python library that is meant for exploration and visualization rather than statistical analysis. As for logistic regressions, SciPy is a good tool when one does not have his or her own analysis script. Let's look at the optimize package                        from scipy.optimize import [...]

By | 2016-11-08T09:30:04+00:00 June 9, 2016|Categories: Bioinformatics, Data Analysis, Data Visualization, Python|0 Comments

Formatting data for Circos with R

When generating a Circos plot, the formatting of the data to be represented is a crucial step. Here are some pointers on how to avoid the dreadful *** CIRCOS ERROR ***. All data files must be in text format. For instance, using R, I would generate a myData.txt file that I would then call within a specific plot block (<plot>...</plot>). Data files are used for 2-dimensional graphical representations (histogram, scatter plot, heatmap, tiles), labels (which are technically also a type [...]

By | 2016-11-08T09:30:09+00:00 October 29, 2015|Categories: Circos, Data Visualization, R|0 Comments

Draw me a Circos

How pretty would that look in my article? Very Pretty! As well as being informative! You might want to use a Circos for your own personal analysis or as an article figure. In both cases, this kind of representation is useful when it comes to visualizing data in a more global or complete manner:  you can have multiple types of data ranging across various chromosomal sequences. However, as wonderful and exciting the idea of having your own personal Circos might [...]

By | 2016-11-08T09:30:10+00:00 August 20, 2015|Categories: Bioinformatics, Biology, Data Visualisation|0 Comments