# Lab Statistics & Math

## Excelling With Excel: Analytical Method Validation Using LOD and LOQ

Don’t be fooled by bad data. Make sure your results are reliable with this quick guide to determining LOQ and LOD in Excel.

Read More## What to Expect When Working with a Scientific Recruiter

Have you ever wondered what it would be like if someone helped you step-by-step through your job search? A good recruiter does exactly that! Recruiters provide value to job-seekers by reviewing resumes, finding jobs that may be a good fit, and providing interview tips. But how does that process work? In this article we’ll cover…

Read More## Size-Selection Is Essential for Cell-Free DNA Studies

Advances in using cell-free DNA (cfDNA) to glean clinically meaningful information for a patient have been stunning. For the most part, these research studies (or downstream diagnostic tests) isolate fetal DNA in the mother’s blood or tumor-derived DNA from the background of healthy DNA in the bloodstream. Typically known as liquid biopsies, these minimally invasive…

Read More## Mysterious miRNA: Identifying miRNAs and Their Targets

In my first article on this topic we delved into what miRNAs are, how they are generated, and their function. Now, we are going to discuss how to identify miRNAs and their targets. Why Do You Want to Look at Something So Small Anyhow? miRNAs play a crucial role in most physiological processes. It’s not…

Read More## How Many Data Points Do I Need For My Experiment?

To draw a convincing conclusion from your data, you cannot simply shoot for the standard significance cutoff. You also need to consider the statistical power, which is determined in part by the sample size in your experiment.

Read More## Choose the Statistical Package that Will Make Your Data Talk

In the last years, the need for using statistical testing in bioscience has grown exponentially and so has the development of statistical software. It is now common that everyone is using some sort of stats in their basic research. Among the skillful biostatisticians, R is the most popular software for data analysis, but not all…

Read More## 3 Common Myths About p Value: Alternatively Never, Ever Rely on it for Data Interpretation

When it comes to data analysis and interpretation, you need to be very clear about the meaning of a given p value and be aware of all its intrinsic limitations.

Read More## Brushing Up On Your Excel Skills: Part One

Microsoft Excel can be a really powerful, useful tool for certain kinds of data processing and record keeping, and the chances are you probably don’t even know how to use half of the functions it comes with! That’s OK, personally, I find Excel a bit less user-friendly than Word, but also it’s a programme I…

Read More## Problems amplifying GC-rich regions? Problem Solved!

No, it isn’t you that’s the problem, and you’re certainly not alone if you’re having trouble amplifying GC-rich sequence and/or understanding why GC-rich sequences are causing such problems in the first place! Amplification of GC-rich sequences by PCR has been an irritant for scientists for decades! When we say “GC-rich” we mean ?60% of the…

Read More## A Beginners Guide to Studying Exosomes

In this webinar you will learn: Biology of extracellular vesicle biogenesis and secretion. Extracellular vesicle composition and contents. Functional activity of extracellular vesicles. Abstract: Extracellular vesicles (EVs) are a heterogeneous group of vesicles that include exosomes, microvesicles, and apoptotic bodies. There has been increasing interest in EVs in recent years not only as possible biomarkers for…

Read More## Polymerase Incomplete Primer Extension (PIPE) Cloning Method

PIPE PCR is a ligase-independent, restriction enzyme-free cloning strategy like SLIC (link to my SLIC article), SLiCE and CPEC. The PIPE method eliminates sequence constraints and reduces cloning and site mutagenesis to a single PCR step followed by product treatment. It is fast, cost-effective and highly efficient. The key step is designing the primers; one…

Read More## Analyzing Apoptosis – A Review of Analytical Techniques

Now that we’ve learned about the role of apoptosis in good health and disease, it will be useful to know how we can detect apoptosis in cells or organisms. A variety of apoptosis detection kits are commercially available, and here is a roundup of how they work: TUNEL and DNA damage assays The TUNEL assay…

Read More## Beginners Introduction to R Statistical Software

In this webinar you will learn how to import data from Microsoft Excel into R how to use R to perform statistical analyses how get a beautifully formatted figure from your data Summary: This webinar will take the case study approach to introduce R to biologists with little or no previous knowledge of the…

Read More## Ten Non-Chemical Lab Hazards and What They Do to You!

Your lab is full of non-chemical hazards that can explode, stab, kill, and – as if that wasn’t enough – bite. Here’s a list of those hazards to remind you why Environmental Health & Safety exists! 1. Centrifuges Centrifuges are dangerous, especially when not cared for! An unmaintained ultracentrifuge imploded in an American lab in…

Read More## The Establishment of the Nobel Prize

Let’s play a game. I’ll say a word and you say what comes to your mind. Ready? Go! Cat… Kitchen… Doctor… Airplane… Nobel… I have no idea what you said when I said cat but I’d say most of you said “prize” when I said Nobel. Alfred Nobel’s name is most often remembered because of…

Read More## An Easy Way to Start Using R in Your Research: Making Pretty Plots With ggplot

The thing that was most difficult for me as an R beginner was plotting graphs with error bars – there is no concise way to do this with base graphics. There are workarounds, often using the ‘arrows’ command, but isn’t there a simpler way? Yes, in fact there are a handful of plotting packages for…

Read More## R You Ready? Using R for Statistical Tests

We’ve been slowly coaxing you along in our R tutorials. We’ve introduced what R is, gave you a basic tutorial into how to use R and also spent some time learning how to explore your data with R. By now you are probably itching to use R for more complicated analyses. To indulge you, I…

Read More## An Easy Way to Start Using R in Your Research: Exploratory Data Analysis

As you’ve probably kind of guessed from our previous articles Introducng R and the Basic R Tutorial, we think R programming language and R-studio are great tools for data analysis and figure production. And now we are about to prove it! So, you’ve collected some data and are pretty sure you know what statistical test…

Read More## Let’s Talk About Stats: Getting the Most out of your Multiple Datasets with Post-hoc Testing

So you’ve performed a test such as an ANOVA and have found that there is statistical significance in your data (lucky you!), however you now want to know where that significance lies. When you are comparing multiple sets of data it might seem like a logical thought to simply perform an individual t-test between each…

Read More## Let’s Talk About Stats: Comparing Multiple Datasets

Last week I focused on the left-hand side of this diagram and talked about statistical tests for comparing only two datasets. Unfortunately, many experiments are more complicated and have three or more datasets. Different statistical tests are used for comparing multiple data sets. Today I will focus on the right side of the diagram and…

Read More## Let’s Talk About Stats: Comparing Two Sets of Data

There are so may statistical tests out there it can be difficult to determine which is the right test to use. Below is a simple diagram to help you quickly determine which test is right for you. Although this is by no means a comprehensive guide, it includes some of the most common tests and…

Read More## Let’s Talk About Stats: Understanding the Lingo

The first hurdle in learning about statistics is the language. It’s terrible to be reading about a particular statistical test and have to be looking up the meaning of every third word. The type of data you have, the number of measurements, the range of your data values and how your data cluster are all…

Read More## How to Deal With a Failed Experiment

Scientific success is often defined by how well your experiments progress and the results you produce. However, scientific research is driven by a curiosity about the unknown, and you cannot always be prepared for the unknown. Inevitably there will come a time when your experiments fail. In this article I give you some of the…

Read More## Internships During Graduate School: How to Start a Side Career Without Quitting Your Day Job

The clock strikes 10:00 pm, your thumb has a raging case of carpal tunnel syndrome, the trash is full of tubes containing unsuccessful PCR reactions, and you wonder…Is this really what I want to do with my life? How do you get your mojo back when you’re knee deep in research? One option to consider…

Read More## The Ten Lab Commandments: Or the Guide to a Happy Lab

This guide is full of very simple but effective tips so you can have a pleasant lab experience, and help create a happy lab.

Read More## A Guide for Solving Your Lab Math Problems

Math is an important part of lab life, from making solutions to calculating protein concentrations, and miscalculations can cause mayhem for your experiments. Therefore it is important that your math is right, or you could spend weeks trying to figure out what’s going wrong in your experiments. I was hopeless at remembering how to do…

Read More## Show Us Your Moves: Making an MSD Plot

In the previous article, I showed you how to interpret mean-squared displacement (MSD) and showed four easy things you can learn from an MSD graph at a quick glance. Now let’s turn from analyzing an MSD plot to making one. I am going to use the programming language R to generate simulated data and then…

Read More## How Does it Move? Interpreting Motion of an Object with the Mean-Squared Displacement

Stuff moves. It is useful to study how stuff moves, because motion analysis can tell us a lot about the object that is moving. For example, we can learn if an object’s motion is aimless, diffusive wandering, or directed towards some goal, free to explore the available environment, or restricted to a confined space. Studying…

Read More## An Easy Way to Start Using R in Your Research: Basic Tutorial

So now you’re convinced that R is the language for you, you’ve downloaded R-Studio (from http://www.rstudio.com/) and opened it, and. . .what the hell do you do now? Great question! I always find it easiest to learn by doing something, rather than just by seeing a list of possibilities, so here I’ll walk you through…

Read More## An Easy Way to Start Using R in Your Research – Introduction

Working with large datasets can be very frustrating and time consuming. If only there were more tools out there to simplify things without needing to invest a PhD’s worth of time to learn how to use them! I am here to tell you that there is a solution, and a free one at that. If…

Read More## Statistics: A Good P-value is Not Enough

Like many scientists, I don’t consider myself a statistics expert. But I am determined to do things right in my science, and that includes statistics. In my experience, a lot of scientists who are “scared” of statistics fall into the trap of ignoring the existence of anything beyond a t-test. But using the right method…

Read More## Time for T: How to Use the Student’s T-test

To pull together our discussions so far on hypothesis testing and p-values, we will use the t distribution as an example to see how it all works. The t distribution (you may have heard it called Student’s t) is a probability distribution that looks like a bell-shaped curve (or normal distribution). If we sample repeatedly from…

Read More## Pseudoreplication: Don’t Fall For This Simple Statistical Mistake

Now we come to the third part of our trifecta; in the last two posts I have gone over p-values and how they determine significance in null hypothesis testing, and we talked about degrees of freedom and their effect on the p-value. Finally, we come to pseudoreplication: where it can all go terribly wrong. Replication…

Read More## Build A CV You Can Be Proud Of – Part III: Analytical Skills… Including the Dreaded Statistics!

In the previous article in this series, we covered teamwork and networking. Now it’s time to move on to what many people consider the most boring part of the lab work: the analysis. I know we all wish that a simple histogram or a rather nice-looking Western blot or PCR would suffice. But the fact…

Read More## How Free is Your Degree?

In the last post I talked about p-values and how we define significance in null hypothesis testing. P-values are inherently linked to degrees of freedom; a lack of knowledge about degrees of freedom invariably leads to poor experimental design, mistaken statistical tests and awkward questions from peer reviewers or conference attendees. Even if you think…

Read More## Don’t Be Another P-value Victim

In previous articles, I’ve primed you on hypothesis testing and how we are forced to choose between minimising either Type I or Type II errors. In the world of the null hypothesis fetish, the p-value (p) is the most revered number. It may also be the least understood. The p-value is the probability, assuming the…

Read More## Types of Statistical Errors and What They Mean

This column is loaded with pop quizzes for you to test yourself on. If you haven’t already done so, catch up on yesterday’s piece on hypothesis testing for a refresher. Take a gander at the table below for a summary of the two types of error that can result from hypothesis testing. Type I Errors occur…

Read More## A Primer on Statistical Hypotheses

Hypothesis testing is the foundation around which we prove our science is worth funding, publishing and sitting through a conference presentation for. I can’t overstate the importance of understanding hypothesis testing, such is the integral part it plays in biological analyses. The Null Hypothesis Fundamental to statistics is the concept of a null hypothesis, and…

Read More## Why You Should Care More About Statistics

In this, the first in a series of articles on statistics, I want to set out some of the main reasons why you, as a biologist, should improve your knowledge of statistics. The general consensus is that biologists are not strong when it comes to statistics. There’s nothing in our brains that stops us from…

Read More## Does Anyone Know the Funny Handshake?

Greg Petsko, President of the American Society for Biochemistry wrote a very interesting article recently in which he drew attention to the parallels between the PhD/Postdoc system and the medieval trade guilds, and the problems our profession faces because it is drifting away from that system. In the trade guild system the right of an…

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