Fast alignment and preprocessing of chromatin profiles with Chromap

As sequencing depth of chromatin studies continually grows deeper for sensitive profiling of regulatory elements or chromatin spatial structures, aligning and preprocessing of these sequencing data have become the bottleneck for analysis. Here we present Chromap, an ultrafast method for aligning and preprocessing high throughput chromatin profiles. Chromap is comparable to BWA-MEM and Bowtie2 in alignment accuracy and is over 10 times faster than traditional workflows on bulk ChIP-seq/Hi-C profiles and than 10x Genomics’ CellRanger v2.0.0 pipeline on single-cell ATAC-seq profiles.

Imageless robotic-assisted revision arthroplasty from UKA to TKA

Background and objective It is evident from the national joint registries that numbers of revision knee arthroplasty operations are rising. The aim of this article is to introduce a new robotic-assisted approach in UKA to TKA revision arthroplasty and investigate the alignment accuracy, implant component use and surgery time and to compare it to primary robotic-assisted TKA arthroplasty. Methods This retrospective, case-control study included patients undergoing image-less robotic-assisted revision arthroplasty from UKA to TKA (n = 20) and patients undergoing image-less robotic-assisted primary TKA (control group, n = 20) from 11/2018 to 07/2020. The control group was matched based on the BMI and natural alignment. Comparison of groups was based on postoperative alignment, outlier rate, tibial insert size, lateral bone resection depth, incision-to-wound closure time. All surgeries were performed by a single senior surgeon using the same bi-cruciate stabilizing TKA system. Statistical analysis consisted of parametric t‑testing and Fisher’s exact test with a level of significance of p < 0.05. Results The two groups showed no differences in mean BMI, natural alignment (p > 0.05) and mean overall limb alignment. No outlier was found for OLA and slope analysis. The smallest insert size (9 mm) was used in 70% of the cases in the revision group (n = 14) and in 90% of the cases in the primary group (n = 18, p = 0.24), distal femoral and tibial resection depth showed no statistical difference (p > 0.05). The incision to wound closure time was longer in the revision group but showed no significant difference. Conclusion Image-less robotic-assisted revision arthroplasty from UKA to TKA showed a comparable surgery time, and alignment accuracy in comparison to primary robotic-assisted TKA. Comparable bone preservation and subsequent tibial insert size use was observed for both groups.

Recursive MAGUS: Scalable and accurate multiple sequence alignment

Multiple sequence alignment tools struggle to keep pace with rapidly growing sequence data, as few methods can handle large datasets while maintaining alignment accuracy. We recently introduced MAGUS, a new state-of-the-art method for aligning large numbers of sequences. In this paper, we present a comprehensive set of enhancements that allow MAGUS to align vastly larger datasets with greater speed. We compare MAGUS to other leading alignment methods on datasets of up to one million sequences. Our results demonstrate the advantages of MAGUS over other alignment software in both accuracy and speed. MAGUS is freely available in open-source form at https://github.com/vlasmirnov/MAGUS.

Fast alignment and preprocessing of chromatin profiles with Chromap

We present Chromap, an ultrafast method for aligning and preprocessing high throughput chromatin profiles. Chromap is comparable to BWA-MEM and Bowtie2 in alignment accuracy and is over 10 times faster than traditional workflows on bulk ChIP-seq / Hi-C profiles and than 10x Genomics' CellRanger v2.0.0 pipeline on single-cell ATAC-seq profiles.

Recursive MAGUS: scalable and accurate multiple sequence alignment

Multiple sequence alignment tools struggle to keep pace with rapidly growing sequence data, as few methods can handle large datasets while maintaining alignment accuracy. We recently introduced MAGUS, a new state-of-the-art method for aligning large numbers of sequences. In this paper, we present a comprehensive set of enhancements that allow MAGUS to align vastly larger datasets with greater speed. We compare MAGUS to other leading alignment methods on datasets of up to one million sequences. Our results demonstrate the advantages of MAGUS over other alignment software in both accuracy and speed. MAGUS is freely available in open-source form at https://github.com/vlasmirnov/MAGUS.

Integrated Navigation on Vehicle Based on Low Cost MEMS SINS/GNSS using LS-SVM

The high-precision initial alignment time for the MEMS SINS/GNSS combination system is too long, and it is difficult to ensure the flexible navigation of existing low-cost vehicles. A LS-SVM-assisted fast alignment method is proposed, which uses MEMS gyroscopes, accelerometers and dual-antenna satellite receivers to achieve fast alignment under MEMS SINS/GNSS. Based on the analysis of traditional coordinates and strapdown inertial navigation, the dynamic error model is given. The self-aligned frame of LS-SVM is proposed. At the same time, the EKF filter for training is designed and the motion characteristics of the car body are selected. The state equations and observations, using the EKF to train the LS-SVM model, ultimately achieve fast alignment. Finally, the proposed method is simulated and tested. The final attitude alignment accuracy is better than 0.2° and the alignment time is 10s. Compared with the EKF alignment method under the traditional direct transfer alignment, the alignment accuracy and the alignment time are significantly improved, which can meet the requirements of low-cost vehicle flexibility.

Taking the accuracy of printed electronics beyond 1μm

Researchers at VTT Technical Research Centre of Finland are developing printed electronics beyond the 1μm mark. Reverse-offset printing technique can achieve sub-micron line resolution and μm-scale alignment accuracy

HISAT-3N: a rapid and accurate three-nucleotide sequence aligner

Nucleotide conversion sequencing technologies such as bisulfite-seq and SLAM-seq are powerful tools to explore the intricacies of cellular processes. In this paper, we describe HISAT-3N (hierarchical indexing for spliced alignment of transcripts - 3 nucleotides), which rapidly and accurately aligns sequences consisting of nucleotide conversions by leveraging powerful hierarchical index and repeat index algorithms originally developed for the HISAT software. Tests on real and simulated data sets demonstrate that HISAT-3N is over 7 times faster, has greater alignment accuracy, and has smaller memory requirements than other modern systems. Taken together HISAT-3N is the ideal aligner for use with converted sequence technologies.