Giese SH et al. (2014) Bioinformatics "Specificity control for read alignments using an artificial reference genome-guided false discovery rate."

Giese SH, Zickmann F, Renard BY

[Bioinformatics, 2014]

MOTIVATION: Accurate estimation, comparison and evaluation of read mapping error rates is a crucial step in the processing of next-generation sequencing data, as further analysis steps and interpretation assume the correctness of the mapping results. Current approaches are either focused on sensitivity estimation and thereby disregard specificity or are based on read simulations. Although continuously improving, read simulations are still prone to introduce a bias into the mapping error quantitation and cannot capture all characteristics of an individual dataset. RESULTS: We introduce ARDEN (artificial reference driven estimation of false positives in next-generation sequencing data), a novel benchmark method that estimates error rates of read mappers based on real experimental reads, using an additionally generated artificial reference genome. It allows a dataset-specific computation of error rates and the construction of a receiver operating characteristic curve. Thereby, it can be used for optimization of parameters for read mappers, selection of read mappers for a specific problem or for filtering alignments based on quality estimation. The use of ARDEN is demonstrated in a general read mapper comparison, a parameter optimization for one read mapper and an application example in single-nucleotide polymorphism discovery with a significant reduction in the number of false positive identifications. AVAILABILITY: The ARDEN source code is freely available at http://sourceforge.net/projects/arden/.

Shimko TC et al. (2014) PLoS One "COPASutils: an R package for reading, processing, and visualizing data from COPAS large-particle flow cytometers."

Shimko TC, Andersen EC

[PLoS One, 2014]

The R package COPASutils provides a logical workflow for the reading, processing, and visualization of data obtained from the Union Biometrica Complex Object Parametric Analyzer and Sorter (COPAS) or the BioSorter large-particle flow cytometers. Data obtained from these powerful experimental platforms can be unwieldy, leading to difficulties in the ability to process and visualize the data using existing tools. Researchers studying small organisms, such as Caenorhabditis elegans, Anopheles gambiae, and Danio rerio, and using these devices will benefit from this streamlined and extensible R package. COPASutils offers a powerful suite of functions for the rapid processing and analysis of large high-throughput screening data sets.

Lee H et al. (2023) BMC Genomics "Benchmarking datasets for assembly-based variant calling using high-fidelity long reads."

Kim J, Lee J, Lee H

[BMC Genomics, 2023]

BACKGROUND: Recent advances in long-read sequencing technologies have enabled accurate identification of all genetic variants in individuals or cells; this procedure is known as variant calling. However, benchmarking studies on variant calling using different long-read sequencing technologies are still lacking. RESULTS: We used two Caenorhabditis elegans strains to measure several variant calling metrics. These two strains shared true-positive genetic variants that were introduced during strain generation. In addition, both strains contained common and distinguishable variants induced by DNA damage, possibly leading to false-positive estimation. We obtained accurate and noisy long reads from both strains using high-fidelity (HiFi) and continuous long-read (CLR) sequencing platforms, and compared the variant calling performance of the two platforms. HiFi identified a 1.65-fold higher number of true-positive variants on average, with 60% fewer false-positive variants, than CLR did. We also compared read-based and assembly-based variant calling methods in combination with subsampling of various sequencing depths and demonstrated that variant calling after genome assembly was particularly effective for detection of large insertions, even with 10 × sequencing depth of accurate long-read sequencing data. CONCLUSIONS: By directly comparing the two long-read sequencing technologies, we demonstrated that variant calling after genome assembly with 10 × or more depth of accurate long-read sequencing data allowed reliable detection of true-positive variants. Considering the high cost of HiFi sequencing, we herein propose appropriate methodologies for performing cost-effective and high-quality variant calling: 10 × assembly-based variant calling. The results of the present study may facilitate the development of methods for identifying all genetic variants at the population level.

Lesack K et al. (2022) PLoS One "Different structural variant prediction tools yield considerably different results in Caenorhabditis elegans."

Lesack K, Andersen EC, Wasmuth JD, Mariene GM

[PLoS One, 2022]

The accurate characterization of structural variation is crucial for our understanding of how large chromosomal alterations affect phenotypic differences and contribute to genome evolution. Whole-genome sequencing is a popular approach for identifying structural variants, but the accuracy of popular tools remains unclear due to the limitations of existing benchmarks. Moreover, the performance of these tools for predicting variants in non-human genomes is less certain, as most tools were developed and benchmarked using data from the human genome. To evaluate the use of long-read data for the validation of short-read structural variant calls, the agreement between predictions from a short-read ensemble learning method and long-read tools were compared using real and simulated data from Caenorhabditis elegans. The results obtained from simulated data indicate that the best performing tool is contingent on the type and size of the variant, as well as the sequencing depth of coverage. These results also highlight the need for reference datasets generated from real data that can be used as 'ground truth' in benchmarks.

Milani, M et al. (2005) Scanning "Read-out of soft X-ray contact microscopy microradiographs by focused ion beam/scanning electron microscope."

Zrimec, A, Drobne, D, Tatti, F, Batani, D, Orsini, F, Poletti, G, Zullini, A, Milani, M

[Scanning, 2005]

A novel focused ion beam-based technique is presented for the read-out of microradiographs of Caenorhabditis elegans nematodes generated by soft x-ray contact microscopy (SXCM). In previous studies, the read-out was performed by atomic force microscopy (AFM), but in our work SXCM microradiographs were imaged by scanning ion microscopy (SIM) in a focused ion beam/scanning electron microscope (FIB/SEM). It allows an ad libitum selection of a sample region for gross morphologic to nanometric investigations, with a sequence of imaging and cutting. The FIB/SEM is less sensitive to height variation of the relief, and sectioning makes it possible to analyse the sample further. The SXCM can be coupled to SIM in a more efficient and faster way than to AFM. Scanning ion microscopy is the method of choice for the read-out of microradiographs of small multicellular organisms.

Huang YT et al. (2017) BMC Bioinformatics "An efficient error correction algorithm using FM-index."

Huang YT, Huang YW

[BMC Bioinformatics, 2017]

BACKGROUND: High-throughput sequencing offers higher throughput and lower cost for sequencing a genome. However, sequencing errors, including mismatches and indels, may be produced during sequencing. Because, errors may reduce the accuracy of subsequent de novo assembly, error correction is necessary prior to assembly. However, existing correction methods still face trade-offs among correction power, accuracy, and speed. RESULTS: We develop a novel overlap-based error correction algorithm using FM-index (called FMOE). FMOE first identifies overlapping reads by aligning a query read simultaneously against multiple reads compressed by FM-index. Subsequently, sequencing errors are corrected by k-mer voting from overlapping reads only. The experimental results indicate that FMOE has highest correction power with comparable accuracy and speed. Our algorithm performs better in long-read than short-read datasets when compared with others. The assembly results indicated different algorithms has its own strength and weakness, whereas FMOE is good for long or good-quality reads. CONCLUSIONS: FMOE is freely available at https://github.com/ythuang0522/FMOC .

Galindo-Malagn XA et al. (2022) Zootaxa "New species, synonymies and records in the genus Rhagovelia Mayr, 1865 (Hemiptera: Heteroptera: Veliidae) from Colombia."

Moreira FFF, Morales I, Mondragn-F SP, Galindo-Malagn XA

[Zootaxa, 2022]

Rhagovelia medinae sp. nov., of the hambletoni group (angustipes complex), and R. utria sp. nov., of the hirtipes group (robusta complex), are described, illustrated, and compared with similar congeners. Based on the examination of type specimens, six new synonymies are proposed: R. elegans Uhler, 1894 = R. pediformis Padilla-Gil, 2010, syn. nov.; R. cauca Polhemus, 1997 = R. azulita Padilla-Gil, 2009, syn. nov., R. huila Padilla-Gil, 2009, syn. nov., R. oporapa Padilla-Gil, 2009, syn. nov, R. quilichaensis Padilla-Gil, 2011, syn. nov.; and R. gaigei, Drake Hussey, 1947 = R. victoria Padilla-Gil, 2012 syn. nov. The first record from Colombia is presented for R. trailii (White, 1879), and the distributions of the following species are extended in the country: R. cali Polhemus, 1997, R. castanea Gould, 1931, R. cauca Polhemus, 1997, R. gaigei Drake Hussey, 1957, R. elegans Uhler, 1894, R. femoralis Champion, 1898, R. malkini Polhemus, 1997, R. perija Polhemus, 1997, R. sinuata Gould, 1931, R. venezuelana Polhemus, 1997, R. williamsi Gould, 1931, and R. zeteki Drake, 1953.

Desai A et al. (2013) PLoS One "Identification of optimum sequencing depth especially for de novo genome assembly of small genomes using next generation sequencing data."

Jha V, Jere A, Yadav A, Bangar U, Dhaygude K, Marwah VS, Kulkarni V, Desai A

[PLoS One, 2013]

Next Generation Sequencing (NGS) is a disruptive technology that has found widespread acceptance in the life sciences research community. The high throughput and low cost of sequencing has encouraged researchers to undertake ambitious genomic projects, especially in de novo genome sequencing. Currently, NGS systems generate sequence data as short reads and de novo genome assembly using these short reads is computationally very intensive. Due to lower cost of sequencing and higher throughput, NGS systems now provide the ability to sequence genomes at high depth. However, currently no report is available highlighting the impact of high sequence depth on genome assembly using real data sets and multiple assembly algorithms. Recently, some studies have evaluated the impact of sequence coverage, error rate and average read length on genome assembly using multiple assembly algorithms, however, these evaluations were performed using simulated datasets. One limitation of using simulated datasets is that variables such as error rates, read length and coverage which are known to impact genome assembly are carefully controlled. Hence, this study was undertaken to identify the minimum depth of sequencing required for de novo assembly for different sized genomes using graph based assembly algorithms and real datasets. Illumina reads for E.coli (4.6 MB) S.kudriavzevii (11.18 MB) and C. elegans (100 MB) were assembled using SOAPdenovo, Velvet, ABySS, Meraculous and IDBA-UD. Our analysis shows that 50X is the optimum read depth for assembling these genomes using all assemblers except Meraculous which requires 100X read depth. Moreover, our analysis shows that de novo assembly from 50X read data requires only 6-40 GB RAM depending on the genome size and assembly algorithm used. We believe that this information can be extremely valuable for researchers in designing experiments and multiplexing which will enable optimum utilization of sequencing as well as analysis resources.

Pan CT et al. (2014) Biomed Res Int "miRSeq: a user-friendly standalone toolkit for sequencing quality evaluation and miRNA profiling."

Li SC, Tsai KW, Hung TM, Pan CT, Yu HR, Lin WC, Pan CY

[Biomed Res Int, 2014]

MicroRNAs (miRNAs) present diverse regulatory functions in a wide range of biological activities. Studies on miRNA functions generally depend on determining miRNA expression profiles between libraries by using a next-generation sequencing (NGS) platform. Currently, several online web services are developed to provide small RNA NGS data analysis. However, the submission of large amounts of NGS data, conversion of data format, and limited availability of species bring problems. In this study, we developed miRSeq to provide alternatives. To test the performance, we had small RNA NGS data from four species, including human, rat, fly, and nematode, analyzed with miRSeq. The alignments results indicate that miRSeq can precisely evaluate the sequencing quality of samples regarding percentage of self-ligation read, read length distribution, and read category. miRSeq is a user-friendly standalone toolkit featuring a graphical user interface (GUI). After a simple installation, users can easily operate miRSeq on a PC or laptop by using a mouse. Within minutes, miRSeq yields useful miRNA data, including miRNA expression profiles, 3' end modification patterns, and isomiR forms. Moreover, miRSeq supports the analysis of up to 105 animal species, providing higher flexibility.

Li R et al. (2015) Sci Rep "Illumina Synthetic Long Read Sequencing Allows Recovery of Missing Sequences even in the "Finished" C. elegans Genome."

Li R, Young A, Ren X, Hsieh CL, Zhao Z, Zhang Z

[Sci Rep, 2015]

Most next-generation sequencing platforms permit acquisition of high-throughput DNA sequences, but the relatively short read length limits their use in genome assembly or finishing. Illumina has recently released a technology called Synthetic Long-Read Sequencing that can produce reads of unusual length, i.e., predominately around 10 Kb. However, a systematic assessment of their use in genome finishing and assembly is still lacking. We evaluate the promise and deficiency of the long reads in these aspects using isogenic C. elegans genome with no gap. First, the reads are highly accurate and capable of recovering most types of repetitive sequences. However, the presence of tandem repetitive sequences prevents pre-assembly of long reads in the relevant genomic region. Second, the reads are able to reliably detect missing but not extra sequences in the C. elegans genome. Third, the reads of smaller size are more capable of recovering repetitive sequences than those of bigger size. Fourth, at least 40 Kbp missing genomic sequences are recovered in the C. elegans genome using the long reads. Finally, an N50 contig size of at least 86 Kbp can be achieved with 24 x reads but with substantial mis-assembly errors, highlighting a need for novel assembly algorithm for the long reads.