I put a recent code snippet put up on the IgorExchange. It’s a simple procedure for averaging a set of 1D waves and putting the results in a new wave. The difference between this code and Average Waves.ipf (which ships with Igor) is that this function takes the average of all points in the wave and places this single value in a new wave. You can specify whether the mean or median is used for the average.
This is a long post about Journal Impact Factors. Thanks to Stephen Curry for encouraging me to post this.
Following on from the last post about publication lag times at cell biology journals, I went ahead and crunched the numbers for all journals in PubMed for one year (2013). Before we dive into the numbers, a couple of points about this kind of information. Some journals “reset the clock” on the received date with manuscripts that are resubmitted. This makes comparisons difficult.
In this post I’ll describe a computational method for splitting two sides of a cell biological structure. It’s a simple method that relies on principal component analysis , otherwise known as PCA.
Having recently got my head around violin plots, I thought I would explain what they are and why you might want to use them. There are several options when it comes to plotting summary data. I list them here in order of granularity, before describing violin plots and how to plot them in some detail.
A bit of navel gazing for this post. Since moving the blog to wordpress.com in the summer, it recently accrued 5000 views.
The transition for scientific journals from print to online has been slow and painful. And it is not yet complete. This week I got an RSS alert to a “new” paper in Oncogene.
An IgorPro tip this week. The default font for plots is Geneva. Most of our figures are assembled using Helvetica for labelling. The default font can be changed in Igor Graph Preferences, but Preferences need to be switched on in order to be implemented. Anyway, I always seem to end up with a mix of Geneva plots and Helevetica plots.
Note : this is not a serious blog post. Neil Hall’s think piece in Genome Biology on the Kardashian index (K-index) caused an online storm recently, spawning hashtags and outrage in not-so-equal measure. Despite all the vitriol that headed Neil’s way, very little of it concerned his use of Microsoft Excel to make his plot of Twitter followers vs total citations!
Fans of data visualisation will know the work of Edward Tufte well. His book “The Visual Display of Quantitative Information” is a classic which covers the history and the principals of conveying data in a concise way, that is easy to interpret. He is also credited with two different dataviz techniques: sparklines and image quilts.
