A comparison of SNPs and microsatellites as linkage mapping markers: lessons from the zebra finch (Taeniopygia guttata)

Background: Genetic linkage maps are essential tools when searching for quantitative trait loci (QTL). To maximize genome coverage and provide an evenly spaced marker distribution a combination of different types of genetic marker are sometimes used. In this study we created linkage maps of four zebra finch (Taeniopygia guttata) chromosomes (1, 1A, 2 and 9) using two types of marker, Single Nucleotide Polymorphisms (SNPs) and microsatellites. To assess the effectiveness and accuracy of each kind of marker we compared maps built with each marker type separately and with both types of marker combined. Linkage map marker order was validated by making comparisons to the assembled zebra finch genome sequence. Results: We showed that marker order was less reliable and linkage map lengths were inflated for microsatellite maps relative to SNP maps, apparently due to differing error rates between the two types of marker. Guidelines on how to minimise the effects of error are provided. In particular, we show that when combining both types of marker the conventional process of building linkage maps, whereby the most informative markers are added to the map first, has to be modified in order to improve map accuracy. Conclusions: When using multiple types and large numbers of markers to create dense linkage maps, the least error prone loci (SNPs) rather than the most informative should be used to create framework maps before the addition of other potentially more error prone markers (microsatellites). This raises questions about the accuracy of marker order and predicted recombination rates in previous microsatellite linkage maps which were created using the conventional building process, however, provided suitable error detection strategies are followed microsatellite-based maps can continue to be regarded as reasonably reliable

Fifty years of spellchecking

A short history of spellchecking from the late 1950s to the present day, describing its development through dictionary lookup, affix stripping, correction, confusion sets, and edit distance to the use of gigantic databases

An examination of the genotyping error detection function of SIMWALK2

This investigation was undertaken to assess the sensitivity and specificity of the genotyping error detection function of the computer program SIMWALK2. We chose to examine chromosome 22, which had 7 microsatellite markers, from a single simulated replicate (330 pedigrees with a pattern of missing genotype data similar to the Framingham families). We created genotype errors at five overall frequencies (0.0, 0.025, 0.050, 0.075, and 0.100) and applied SIMWALK2 to each of these five data sets, respectively assuming that the total error rate (specified in the program), was at each of these same five levels. In this data set, up to an assumed error rate of 10%, only 50% of the Mendelian-consistent mistypings were found under any level of true errors. And since as many as 70% of the errors detected were false-positives, blanking suspect genotypes (at any error probability) will result in a reduction of statistical power due to the concomitant blanking of correctly typed alleles. This work supports the conclusion that allowing for genotyping errors within likelihood calculations during statistical analysis may be preferable to choosing an arbitrary cut-off

Software Patents: What One-Click Buy and Safe Air Travel Have in Common

Have you ever sat in an airplane, typing on your laptop, when the darn thing crashes for the one-millionth time? Have you ever then thought about how the airplane you are sitting in is controlled by software, too--the technical term being fly by wire --and then started sweating uncontrollably? Software controls not only air traffic but plenty of other safety-critical technologies: the tightrope walk of controlling the chain reaction of radioactive elements in nuclear power plants; the navigation and activation of missiles;3 the moves and cutting-depth of a surgical laser when correcting eye-sights; the list goes on... With such reliance on software, malfunction due to errors in the program code becomes unacceptable. Software patents help heighten the standard by supporting the re-use of the code of established and tested systems

BNC! Handle with care! Spelling and tagging errors in the BNC

"You loose your no-claims bonus," instead of "You lose your no-claims bonus," is an example of a real-word spelling error. One way to enable a spellchecker to detect such errors is to prime it with information about likely features of the context for "loose" (verb) as compared with "lose". To this end, we extracted all the examples of "loose" used as a verb from the BNC (World edition, text). There were, apparently, 159 occurrences of "loose" (VVB or VVI). However, on inspection, well over half of these were not verbs at all (tagging errors) and over half of the rest were misspellings of "lose". Only about 15% were actual occurrences of "loose" as a verb. This prompted us to undertake a small investigation into errors in the BNC. We report on some words that occur more often as misspellings than in their own right - only one of the 63 occurrences of "ail", for example, is correct (possibly OCR errors) - and some words that are always mistagged, such as "haulier" and "glazier" (never NN), and "hanker" and "loiter" (never VV). We note in particular that, if a rare word resembles a common word (in spelling), it is more likely to appear as a misspelling of the common word than as a correct spelling of the rare word. These cases require some modification of an earlier conclusion (Damerau and Mays, 1989) on misspellings of rare words. We conclude with a discussion of the desirability, or otherwise, of correcting errors in corpora such as the BNC. The results may be of interest to people who use the BNC as training data or for teaching

Frontal theta band oscillations predict error correction and posterror slowing in typing

Performance errors are associated with robust behavioral and electroencephalography (EEG) effects. However, there is a debate about the nature of the relationship between these effects and implicit versus explicit error awareness. Our aim was to study the relationship between error related electrophysiological effects, such as spectral perturbations in fronto-medial theta band oscillations (FMT), and error awareness in typing. Typing has an advantage as an experimental paradigm in that detected errors are quickly and habitually signaled by the participant using backspace, allowing separation of detected from undetected errors without interruption in behavior. Typing is thought to be controlled hierarchically via inner and outer loops, which rely on different sources for error detection. Touch-typist participants were asked to copy-type 100 sentences as EEG was recorded in the absence of visual feedback. Continuous EEG data were analyzed using independent component analysis (ICA). Time-frequency and ERP analyses were applied to emergent independent components. The results show that single-trial FMT parameters and error related negativity (ERN) amplitude predict overt, adaptive posterror actions such as error correction via backspace; and, posterror slowing, reflecting implicit error awareness. In addition, we found that those uncorrected errors which were slowed down the most were also the ones associated with a high level of FMT activity. Our results as a whole show that FMT are related to neural mechanisms involved in explicit awareness of errors, and input from inner loop is sufficient for error correction in typing. (PsycINFO Database Record (c) 2017 APA, all rights reserved

The Sizing and Optimization Language (SOL): A computer language to improve the user/optimizer interface

The nonlinear mathematical programming method (formal optimization) has had many applications in engineering design. A figure illustrates the use of optimization techniques in the design process. The design process begins with the design problem, such as the classic example of the two-bar truss designed for minimum weight as seen in the leftmost part of the figure. If formal optimization is to be applied, the design problem must be recast in the form of an optimization problem consisting of an objective function, design variables, and constraint function relations. The middle part of the figure shows the two-bar truss design posed as an optimization problem. The total truss weight is the objective function, the tube diameter and truss height are design variables, with stress and Euler buckling considered as constraint function relations. Lastly, the designer develops or obtains analysis software containing a mathematical model of the object being optimized, and then interfaces the analysis routine with existing optimization software such as CONMIN, ADS, or NPSOL. This final state of software development can be both tedious and error-prone. The Sizing and Optimization Language (SOL), a special-purpose computer language whose goal is to make the software implementation phase of optimum design easier and less error-prone, is presented

Typing performance of blind users:an analysis of touch behaviors, learning effect, and in-situ usage

Non-visual text-entry for people with visual impairments has focused mostly on the comparison of input techniques reporting on performance measures, such as accuracy and speed. While researchers have been able to establish that non-visual input is slow and error prone, there is little understanding on how to improve it. To develop a richer characterization of typing performance, we conducted a longitudinal study with five novice blind users. For eight weeks, we collected in-situ usage data and conducted weekly laboratory assessment sessions. This paper presents a thorough analysis of typing performance that goes beyond traditional aggregated measures of text-entry and reports on character-level errors and touch measures. Our findings show that users improve over time, even though it is at a slow rate (0.3 WPM per week). Substitutions are the most common type of error and have a significant impact on entry rates. In addition to text input data, we analyzed touch behaviors, looking at touch contact points, exploration movements, and lift positions. We provide insights on why and how performance improvements and errors occur. Finally, we derive some implications that should inform the design of future virtual keyboards for non-visual input. Categories and Subject Descriptors H.5.2 [Information Interfaces and Presentation]: User Interfaces- Input devices and strategies. K4.2 [Computers an

Performance breakdown effects dissociate from error detection effects in typing

Mistakes in skilled performance are often observed to be slower than correct actions. This error slowing has been associated with cognitive control processes involved in performance monitoring and error detection. A limited literature on skilled actions, however, suggests that preerror actions may also be slower than accurate actions. This contrasts with findings from unskilled, discrete trial tasks, where preerror performance is usually faster than accurate performance. We tested 3 predictions about error-related behavioural changes in continuous typing performance. We asked participants to type 100 sentences without visual feedback. We found that (a) performance before errors was no different in speed than that before correct key-presses, (b) error and posterror key-presses were slower than matched correct key-presses, and (c) errors were preceded by greater variability in speed than were matched correct key-presses. Our results suggest that errors are preceded by a behavioural signature, which may indicate breakdown of fluid cognition, and that the effects of error detection on performance (error and posterror slowing) can be dissociated from breakdown effects (preerror increase in variability). © 2013 © 2013 The Experimental Psychology Society