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Alex — Internet's Most Popular Rat
Poster Rat for Rat Genome Sequencing
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The rat genome sequencing project at the Baylor College of Medicine Human Genome Sequencing Centre is complete. The genome has been analyzed and published. I'd like to introduce you one of the faces of the project: Alex, the genomics rat idol. Arguably, Alex is the most popular rat on the internet. For the justification of this strong statement, read on. 
▲ Alex, the rat. Rattus norvegicus on an ABI 3700 genome sequencer.
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▲ Alex, the rat. Rattus norvegicus on an ABI 3700 genome sequencer.
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Alex's BiographyAlex was born in May 2000. It's well known that a rat's cuteness reaches maximum at about 3-4 weeks. After this critical time, a pet store rat is less likely to be purchased and may be asked to act as snake food. In Alex's case, she was perilously close to her deadline. Luckily for her, we paid a ransom of $6.99 to the Noah's Ark pet shop in Vancouver. She was on her last cute leg. 
▲ Portrait of Alex, the genome rat (Rattus norvegicus). Here, she is seen in a forced portrait position
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From May 2000 Alex spent most of her time hoarding food pellets and riding on shoulders. 
▲ Portrait of Alex, the genome rat (Rattus norvegicus). Riding on shoulder.
Alex liked to bite. And rats only bite hard — they don't nibble. Her contention for this unattractive behaviour was the uncanny similarity between a finger and a pellet of food. Other than unpredictable bouts of biting (by far the most exciting aspect of her personality), Alex lacked other distinguishing characteristics. Alex died of a seizure in late 2002. She was buried outside of the Museum of Anthropology. A ratty pair of underwear served as a burial shroud. And I hope you got that last pun. |
DOWNLOAD ALL PHOTOS.
Photos are for public use. Use, modification and distribution of these photos is unrestricted. Alex's PopularityDespite my best efforts at meaningful work, this web page continues to be the most popular of all my online offerings, making for a somewhat embarrassing achievement. Alex's images consistently show up first in Google's web search for 'rat', 'rat image' and image search for 'rat'. 
▲ Alex image is the first for Google's 'rat' search query (retrieved 16 Mar 2013).
(rat Google search)
▲ Alex image is the first for Google's 'rat image' search query (retrieved 16 Mar 2013).
(rat Google search)
Finally, Alex appears as the first entry in Google images for 'rat'. 
▲ Alex image is the first for Google's 'rat image' search query (retrieved 16 Mar 2013).
(rat Google search)
Alex's Public AppearancesAlex is neither without modesty nor public fame. Her first cover-ratgirl appearance was on the April 2004 issue of Genome Research. 
▲ Alex the rat appeared on the cover of Genome Research (April 2004).
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More recently, she's appeared on the cover of Ethnologie Francaise (Jan-Mar 2009 issue). 
▲ Alex the rat appeared on the cover of Ethnologie Francaise (1/2009).
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The topic of the issue was the relationship between animals and humans. It is fitting therefore to recount here the relationship I shared with Alex during her sojourn with us. |
news + thoughts
Quantile regression
Quantile regression robustly estimates the typical and extreme values of a response.Quantile regression explores the effect of one or more predictors on quantiles of the response. It can answer questions such as "What is the weight of 90% of individuals of a given height?"
Unlike in traditional mean regression methods, no assumptions about the distribution of the response are required, which makes it practical, robust and amenable to skewed distributions.
Quantile regression is also very useful when extremes are interesting or when the response variance varies with the predictors.
Das, K., Krzywinski, M. & Altman, N. (2019) Points of significance: Quantile regression. Nature Methods 16:451–452.
Background reading
Altman, N. & Krzywinski, M. (2015) Points of significance: Simple linear regression. Nature Methods 12:999–1000.
Analyzing outliers: Robust methods to the rescue
Robust regression generates more reliable estimates by detecting and downweighting outliers.Outliers can degrade the fit of linear regression models when the estimation is performed using the ordinary least squares. The impact of outliers can be mitigated with methods that provide robust inference and greater reliability in the presence of anomalous values.
We discuss MM-estimation and show how it can be used to keep your fitting sane and reliable.
Greco, L., Luta, G., Krzywinski, M. & Altman, N. (2019) Points of significance: Analyzing outliers: Robust methods to the rescue. Nature Methods 16:275–276.
Background reading
Altman, N. & Krzywinski, M. (2016) Points of significance: Analyzing outliers: Influential or nuisance. Nature Methods 13:281–282.
Two-level factorial experiments
To find which experimental factors have an effect, simultaneously examine the difference between the high and low levels of each.Two-level factorial experiments, in which all combinations of multiple factor levels are used, efficiently estimate factor effects and detect interactions—desirable statistical qualities that can provide deep insight into a system.
They offer two benefits over the widely used one-factor-at-a-time (OFAT) experiments: efficiency and ability to detect interactions.
Since the number of factor combinations can quickly increase, one approach is to model only some of the factorial effects using empirically-validated assumptions of effect sparsity and effect hierarchy. Effect sparsity tells us that in factorial experiments most of the factorial terms are likely to be unimportant. Effect hierarchy tells us that low-order terms (e.g. main effects) tend to be larger than higher-order terms (e.g. two-factor or three-factor interactions).
Smucker, B., Krzywinski, M. & Altman, N. (2019) Points of significance: Two-level factorial experiments Nature Methods 16:211–212.
Background reading
Krzywinski, M. & Altman, N. (2014) Points of significance: Designing comparative experiments.. Nature Methods 11:597–598.