Statistical hypothesis testing , commonly referred to as “statistics”, is a topic of consternation among cell biologists. This is a short practical guide I put together for my lab. Hopefully it will be useful to others. Note that statistical hypothesis testing is a huge topic and one post cannot hope to cover everything that you need to know.

This post follows on from “Getting Started“. In the lab we use IgorPRO for pretty much everything. We have many analysis routines that run in Igor, we have scripts for processing microscope metadata etc, and we use it for generating all figures for our papers. Even so, people in the lab engage with it to varying extents. The main battle is that the use of Excel is pretty ubiquitous.

More on the theme of “The Digital Cell“: using quantitative, computational approaches in cell biology. So you want to get started? Well, the short version of this post is: Find something that you need to automate and get going! Programming http://www.instruction-manuals.co.uk/imageIM/four/seven/bbc.gif I make no claim to be a computer wizard.

The future of cell biology, even for small labs, is quantitative and computational. What does this mean and what should it look like? My group is not there yet, but in this post I’ll describe where we are heading. The graphic below shows my current view of the ideal workflow for my lab. The graphic is pretty self-explanatory, but to walk you through: A lab member sets up a microscopy experiment.

If you are a cell biologist, you will have noticed the change in emphasis in our field. At one time, cell biology papers were – in the main – qualitative . Micrographs of “representative cells”, western blots of a “typical experiment”… This descriptive style gave way to more quantitative approaches, converting observations into numbers that could be objectively assessed.

University of Warwick is a popular conference destination, with thousands of visitors per year. Next time you visit and stay on campus, why not bring your running shoes and try out these routes? Route 1 This is just over 10K and it takes you from main campus out towards Cryfield Pavilion. A path goes to the Greenway (a former railway), which is a nice flat gravel track.

I recently finished reading The Art of Data Science by Roger Peng & Elizabeth Matsui. Roger, together with Jeff Leek, writes the Simply Statistics blog and he works at JHU with Elizabeth. The aim of the book is to give a guide to data analysis. It is not meant as a comprehensive data analysis “how to”, nor is it a manual for statistics or programming.

Previously, I wrote a post with tips for new PIs on lab organisation. Since that time, I’ve started using Trello to organise operations in my lab. Trello is basically a way to track the progress of projects. Collaborative working is built-in. A friend had begun using Trello as she got involved in building an app. It seems that Trello is popular among teams working to develop software.

This is just a quick tip as it took me a little while to sort this out. In the lab we have two QNAP TS-869 Pro NAS devices. Each was set up with a single RAID6 storage pool and I ran them as a primary and replicant via rsync. We recently bought a bigger server and so the plan was to repurpose one of the NAS boxes to be a Time Machine for all the computers in the lab.

I recently gave a talk at a retreat for new PIs working at QMUL. My talk was focussed on tips for getting started, i.e. the nitty gritty of running an efficient lab. It was a mix of things I’ve been told, worked out for myself or that I’d learned the hard way. PIs are expected to be able to do lots of things that can be full-time jobs in themselves.