Comparative Performance of the MGISEQ-2000 and Illumina X-Ten Sequencing Platforms for Paleogenomics

The MGISEQ-2000 sequencer is widely used in various omics studies, but the performance of this platform for paleogenomics has not been evaluated. We here compare the performance of MGISEQ-2000 with the Illumina X-Ten on ancient human DNA using four samples from 1750BCE to 60CE. We found there were only slight differences between the two platforms in most parameters (duplication rate, sequencing bias, θ, δS, and λ). MGISEQ-2000 performed well on endogenous rate and library complexity although X-Ten had a higher average base quality and lower error rate. Our results suggest that MGISEQ-2000 and X-Ten have comparable performance, and MGISEQ-2000 can be an alternative platform for paleogenomics sequencing.

Prowler: a novel trimming algorithm for Oxford Nanopore sequence data

Motivation Trimming and filtering tools are useful in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford nanopore technologies (ONT) trimming and filtering tools are currently rudimentary, generally only filtering reads based on whole read average quality. This results in discarding reads that contain regions of high-quality sequence. Here, we propose Prowler, a trimmer that uses a window-based approach inspired by algorithms used to trim short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns. Results Prowler was applied to mammalian and bacterial datasets, to assess its effect on alignment and assembly, respectively. Compared to data filtered with Nanofilt, alignments of data trimmed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler trimmed data had a lower error rate than those filtered with Nanofilt; however, this came at some cost to assembly contiguity. Availability and implementation Prowler is implemented in Python and is available at https://github.com/ProwlerForNanopore/ProwlerTrimmer. Supplementary information Supplementary data are available at Bioinformatics online.

Modelling the Axis Drift of Short Wire Flexures and Increasing Their Support Stiffness Using Polymers

For steel flexures, complex geometries are required to reach high support stiffness and limit axis drift over large ranges of motion. These complex flexures are expensive and difficult to manufacture. This paper presents a method of designing short, polymer wire flexures with high support stiffness and modelling their axis drift using a novel method, the arc method. The arc method is validated against finite element methods (FEM) and physical tests, showing at least a factor 10 lower error than existing pseudo-rigid-body models (PRBM) at 70° deflection, while maintaining a simple modelling approach. The use of polymers increases support stiffness of wire flexures by a factor 7800 with respect to steel at 70° deflection, even though the material stiffness is substantially lower. This is due to the large allowed strain of polymers increasing the possible diameter by a factor 110.

A bootstrapping approach to social media quantification

This work considers the use of classifiers in a downstream aggregation task estimating class proportions, such as estimating the percentage of reviews for a movie with positive sentiment. We derive the bias and variance of the class proportion estimator when taking classification error into account to determine how to best trade off different error types when tuning a classifier for these tasks. Additionally, we propose a method for constructing confidence intervals that correctly adjusts for classification error when estimating these statistics. We conduct experiments on four document classification tasks comparing our methods to prior approaches across classifier thresholds, sample sizes, and label distributions. Prior approaches have focused on providing the most accurate point estimate while this work focuses on the creation of correct confidence intervals that appropriately account for classifier error. Compared to the prior approaches, our methods provide lower error and more accurate confidence intervals.

Prowler: A novel trimming algorithm for Oxford Nanopore sequence data

Motivation: Quality control (QC) tools are critical in DNA sequencing analysis because they increase the accuracy of sequence alignments and thus the reliability of results. Oxford Nanopore Technologies (ONT) QC is currently rudimentary, generally based on whole read average quality. This results in discarding reads that contain regions of high quality sequence. Here we propose Prowler, a multi-window approach inspired by algorithms used to QC short read data. Importantly, we retain the phase and read length information by optionally replacing trimmed sections with Ns. Results: Prowler was applied to mammalian and bacterial datasets, to assess effects on alignment and assembly respectively. Compared to Nanofilt, alignments of data QCed with Prowler had lower error rates and more mapped reads. Assemblies of Prowler QCed data had a lower error rate than Nanofilt QCed data however this came at some cost to assembly contiguity. Availability and implementation: Prowler is implemented in Python and is available at: https://github.com/ProwlerForNanopore/ProwlerTrimmer Contact: [email protected]

Sequencing of Sars-CoV-2 genome using different Nanopore chemistries

Nanopore sequencing has emerged as a rapid and cost-efficient tool for diagnostic and epidemiological surveillance of SARS-CoV-2 during the COVID-19 pandemic. This study compared results from sequencing the SARS-CoV-2 genome using R9 vs R10 flow cells and Rapid Barcoding Kit (RBK) vs Ligation Sequencing Kit (LSK). The R9 chemistry provided a lower error rate (3.5%) than R10 chemistry (7%). The SARS-CoV-2 genome includes few homopolymeric regions. Longest homopolymers were composed of 7 (TTTTTTT) and 6 (AAAAAA) nucleotides. The R10 chemistry resulted in a lower rate of deletions in timine and adenine homopolymeric regions than R9, at expenses of a larger rate (~10%) of mismatches in these regions. The LSK had a larger yield than RBK, and provided longer reads than RBK. It also resulted in a larger percentage of aligned reads (99% vs 93%) and also in a complete consensus genome. The results from this study suggest that the LSK used on a R9 flow cell could maximize the yield and accuracy of the consensus sequence when used in epidemiological surveillance of SARS-CoV-2.

Estimating the Production Function Under Input Market Frictions

Behind many production function estimators lies a crucial assumption that the firm's choice of intermediate inputs depends only on observed choices of other inputs and on unobserved productivity. This assumption fails when market frictions distort the firm's input choices. I derive a test for the assumption, which is rejected in several industries. I show, using weak identification asymptotics, that when the assumption fails a simplified dynamic panel estimator can be used instead of choice-based methods because it requires choices to be distorted. I propose criteria for choosing between estimators, which in simulations yields lower error than either estimator alone.

Progress in quickly finding orthologs as reciprocal best hits

IntroductionFinding orthologs remains an important bottleneck in comparative genomics analyses. While the authors of software for the quick comparison of protein sequences evaluate the speed of their software and compare their results against the most usual software for the task, it is not common for them to evaluate their software for more particular uses, such as finding orthologs as reciprocal best hits (RBH). Here we compared RBH results, between prokaryotic genomes, obtained using software that runs faster than blastp. Namely, lastal, diamond, and MMseqs2.ResultsWe found that lastal required the least time to produce results. However, it yielded fewer results than any other program when comparing evolutionarily distant genomes. The program producing the most similar number of RBH as blastp was MMseqs2. This program also resulted in the lowest error estimates among the programs tested. The results with diamond were very close to those obtained with MMseqs2, with diamond running faster. Our results suggest that the best of the programs tested was diamond, ran with the “sensitive” option, which took 7% of the time as blastp to run, and produced results with lower error rates than blastp.AvailabilityA program to obtain reciprocal best hits using the software we tested is maintained at https://github.com/Computational-conSequences/SequenceTools