Opportunities and challenges in long-read sequencing data analysis

Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

Love, M. I., Huber, W., & Anders, S. (2014) · Genome Biology · doi:10.1186/s13059-014-0550-8 · Cited by 95,106

<tt>edgeR</tt> : a Bioconductor package for differential expression analysis of digital gene expression data

Robinson, M. D., McCarthy, D. J., & Smyth, G. K. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btp616 · Cited by 41,364

limma powers differential expression analyses for RNA-sequencing and microarray studies

Ritchie, M. E., Phipson, B., Wu, D., Hu, Y., Law, C. W., Shi, W., & Smyth, G. K. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv007 · Cited by 40,458

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features

Liao, Y., Smyth, G. K., & Shi, W. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btt656 · Cited by 27,219

Salmon provides fast and bias-aware quantification of transcript expression

Patro, R., Duggal, G., Love, M. I., Irizarry, R. A., & Kingsford, C. (2017) · Nature Methods · doi:10.1038/nmeth.4197 · Cited by 12,700

Pilon: An Integrated Tool for Comprehensive Microbial Variant Detection and Genome Assembly Improvement

Walker, B. J., Abeel, T., Shea, T., Priest, M., Abouelliel, A., Sakthikumar, S., Cuomo, C. A., Zeng, Q., Wortman, J. R., Young, S., et al. (2014) · PLoS ONE · doi:10.1371/journal.pone.0112963 · Cited by 9,130

Unicycler: Resolving bacterial genome assemblies from short and long sequencing reads

Wick, R. R., Judd, L. M., Gorrie, C. L., & Holt, K. E. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005595 · Cited by 8,728

Canu: scalable and accurate long-read assembly via adaptive k -mer weighting and repeat separationPreprint

Koren, S., Walenz, B. P., Berlin, K., Miller, J. R., Bergman, N. H., & Phillippy, A. M. (2017) · Genome Research · doi:10.1101/gr.215087.116 · Cited by 7,260

Assembly of long, error-prone reads using repeat graphs

Kolmogorov, M., Yuan, J., Lin, Y., & Pevzner, P. A. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0072-8 · Cited by 5,986

Differential expression analysis of multifactor RNA-Seq experiments with respect to biological variation

McCarthy, D. J., Chen, Y., & Smyth, G. K. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks042 · Cited by 5,195

Local read haplotagging enables accurate long-read small variant calling

Kolesnikov, A., Cook, D. E., Nattestad, M., Brambrink, L., McNulty, B., Gorzynski, J. E., Goenka, S. D., Ashley, E. A., Jain, M., Miga, K. H., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50079-5 · Cited by 28

Variable number tandem repeats – Their emerging role in sickness and health

Marshall, J. N. G., Lopez, A. I., Pfaff, A. L., Kõks, S., Quinn, J. P., & Bubb, V. J. (2021) · Experimental Biology and Medicine · doi:10.1177/15353702211003511 · Cited by 29

Analysis of single-cell RNA sequencing data based on autoencoders

Tangherloni, A., Ricciuti, F., Besozzi, D., Lió, P., & Cvejic, A. (2021) · BMC Bioinformatics · doi:10.1186/s12859-021-04150-3 · Cited by 30

The genome of the rice variety LTH provides insight into its universal susceptibility mechanism to worldwide rice blast fungal strains

Yang, L., Zhao, M., Sha, G., Sun, Q., Gong, Q., Yang, Q., Xie, K., Yuan, M., Mortimer, J. C., Xie, W., et al. (2022) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2022.01.030 · Cited by 26

Resource recovery from food-processing wastewaters in a circular economy: a methodology for the future

Durkin, A., Guo, M., Wuertz, S., & Stuckey, D. C. (2022) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2022.102735 · Cited by 26

Epigenetic tumor heterogeneity in the era of single-cell profiling with nanopore sequencing

Ahmed, Y. W., Ababaw, B., Bekele, S. A., Gizaw, S. T., Zerihun, M. F., Wabalo, E. K., Teklemariam, M. D., Mihrete, T. K., Hanurry, E. Y., Gebru, T., et al. (2022) · Clinical Epigenetics · doi:10.1186/s13148-022-01323-6 · Cited by 27

Systematic characterization of cancer transcriptome at transcript resolution

Hu, W., Wu, Y., Shi, Q., Wu, J., Kong, D., Wu, X., He, X., Liu, T., & Li, S. (2022) · Nature Communications · doi:10.1038/s41467-022-34568-z · Cited by 25

Scalable sequence database search using partitioned aggregated Bloom comb trees

Marchet, C., & Limasset, A. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad225 · Cited by 30

Emergent statistical laws in single-cell transcriptomic data

Lazzardi, S., Valle, F., Mazzolini, A., Scialdone, A., Caselle, M., & Osella, M. (2023) · Physical review. E · doi:10.1103/physreve.107.044403 · Cited by 27

Ethanol preservation and pretreatments facilitate quality DNA extractions in recalcitrant plant species

Johnson, G. P., Canty, S. W. J., Lichter‐Marck, I. H., Wagner, W. L., & Wen, J. (2023) · Applications in Plant Sciences · doi:10.1002/aps3.11519 · Cited by 26

A risk-reward examination of sample multiplexing reagents for single cell RNA-Seq

Brown, D. V., Anttila, C. J. A., Ling, L., Grave, P., Baldwin, T. M., Munnings, R. B., Farchione, A. J., Bryant, V. L., Dunstone, A., Biben, C., et al. (2024) · Genomics · doi:10.1016/j.ygeno.2024.110793 · Cited by 26

pyrpipe : a Python package for RNA-Seq workflows

Singh, U., Li, J., Seetharam, A. S., & Wurtele, E. S. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab049 · Cited by 26

Sequencing by Expansion (SBX) – a novel, high-throughput single-molecule sequencing technologyPreprint

Kokoris, M. S., McRuer, R. N., Nabavi, M., Jacobs, A., Prindle, M. J., Cech, C., Berg, K., Lehmann, T., Machacek, C., Tabone, J. C., et al. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.02.19.639056 · Cited by 26

‘Longing’ for the Next Generation of Liquid Biopsy: The Diagnostic Potential of Long Cell-Free DNA in Oncology and Prenatal Testing

Yu, S. C. Y., Choy, L. Y. L., & Lo, Y. M. D. (2023) · Molecular Diagnosis & Therapy · doi:10.1007/s40291-023-00661-2 · Cited by 26

Comprehensive single-cell genome analysis at nucleotide resolution using the PTA Analysis Toolbox

Middelkamp, S., Manders, F., Peci, F., van Roosmalen, M. J., González, D. M., Bertrums, E. J. M., van der Werf, I. M., Derks, L. L. M., Groenen, N. M., Verheul, M., et al. (2023) · Cell Genomics · doi:10.1016/j.xgen.2023.100389 · Cited by 29

DiffDomain enables identification of structurally reorganized topologically associating domains

Hua, D., Gu, M., Zhang, X., Du, Y., Xie, H., Qi, L., Du, X., Bai, Z., Zhu, X., & Tian, D. (2024) · Nature Communications · doi:10.1038/s41467-024-44782-6 · Cited by 24

SATB2 organizes the 3D genome architecture of cognition in cortical neurons

Wahl, N., Espeso‐Gil, S., Chietera, P., Nagel, A., Laighneach, A., Morris, D. W., Rajarajan, P., Akbarian, S., Dechant, G., & Apostolova, G. (2024) · Molecular Cell · doi:10.1016/j.molcel.2023.12.024 · Cited by 24

Measuring, visualizing, and diagnosing reference bias with biastools

Lin, M.-J., Iyer, S., Chen, N.-C., & Langmead, B. (2024) · Genome biology · doi:10.1186/s13059-024-03240-8 · Cited by 29

Recurrent hybridization and gene flow shaped Norway and Siberian spruce evolutionary history over multiple glacial cycles

Zhou, Q., Karunarathne, P., Li, L., Chen, C., Opgenoorth, L., Heer, K., Vendramin, G. G., Piotti, A., Николаевна, Н. Е., Lascoux, M., et al. (2024) · Molecular Ecology · doi:10.1111/mec.17495 · Cited by 26

scTrends: A living review of commercial single-cell and spatial 'omic technologies

Jonghe, J. D., Opzoomer, J. W., Vilas‐Zornoza, A., Nilges, B. S., Crane, P., Vicari, M., Lee, H., Lara‐Astiaso, D., Groß, T., Morf, J., et al. (2024) · Cell Genomics · doi:10.1016/j.xgen.2024.100723 · Cited by 27

Dice-XMBD: Deep Learning-Based Cell Segmentation for Imaging Mass Cytometry

Xiao, X., Qiao, Y., Jiao, Y., Fu, N., Yang, W., Wang, L., Yu, R., & Han, J. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.721229 · Cited by 25

Assessing deep learning methods in cis -regulatory motif finding based on genomic sequencing data

Wang, Y., Zhang, S., Ma, A., Wang, C., Wu, Z., Xu, D., & Ma, Q. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab374 · Cited by 25

A review of durian plant-bat pollinator interactions

Fuad, A. B. H., Lim, V.-C., Yazid, H., Khan, F. A. A., Chong, J. L., Nelson, B. R., Seelan, J. S. S., Appalasamy, S., Mokhtar, S. I., & Kumaran, J. V. (2021) · Journal of Plant Interactions · doi:10.1080/17429145.2021.2015466 · Cited by 25

Chromosome‐level de novo genome assembly of Telopea speciosissima (New South Wales waratah) using long‐reads, linked‐reads and Hi‐C

Chen, S. H., Rossetto, M., van der Merwe, M. M., Lu‐Irving, P., Yap, J. S., Sauquet, H., Bourke, G., Amos, T. G., Bragg, J. G., & Edwards, R. J. (2022) · Molecular Ecology Resources · doi:10.1111/1755-0998.13574 · Cited by 26

Multi-Omic Approaches to Investigate Molecular Mechanisms in Peach Post-Harvest Ripening

Sirangelo, T. M., Rogers, H. J., & Spadafora, N. D. (2022) · Agriculture · doi:10.3390/agriculture12040553 · Cited by 25

Fast and memory-efficient mapping of short bisulfite sequencing reads using a two-letter alphabet

Brandine, G. D. S., & Smith, A. D. (2021) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqab115 · Cited by 25

Deep Metagenomic Sequencing for Endophthalmitis Pathogen Detection Using a Nanopore Platform

Low, L., Nakamichi, K., Akileswaran, L., Lee, C. S., Lee, A., Moussa, G., Murray, P. I., Wallace, G. R., Gelder, R. N. V., & Rauz, S. (2022) · American Journal of Ophthalmology · doi:10.1016/j.ajo.2022.05.022 · Cited by 26

Metatranscriptomic Comparison of Viromes in Endemic and Introduced Passerines in New Zealand

French, R. K., Filion, A., Niebuhr, C. N., & Holmes, E. C. (2022) · Viruses · doi:10.3390/v14071364 · Cited by 25

Application of advanced genomic tools in food safety rapid diagnostics: challenges and opportunities

Banerjee, G., Agarwal, S., Marshall, A., Jones, D. H., Sulaiman, I. M., Sur, S., & Banerjee, P. (2022) · Current Opinion in Food Science · doi:10.1016/j.cofs.2022.100886 · Cited by 25

The first gapless, reference-quality, fully annotated genome from a Southern Han Chinese individual

Chao, K.-H., Zimin, A. V., Pertea, M., & Salzberg, S. L. (2023) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkac321 · Cited by 25

Chromosome-scale Genome Assembly of the Yellow Nutsedge (Cyperus esculentus)

Zhao, X., Yi, L., Ren, Y., Li, J., Ren, W., Hou, Z., Su, S., Wang, J., Zhang, Y., Dong, Q., et al. (2023) · Genome Biology and Evolution · doi:10.1093/gbe/evad027 · Cited by 27

Extensive de novo activity stabilizes epigenetic inheritance of CG methylation in Arabidopsis transposons

Lyons, D. B., Briffa, A., He, S., Choi, J., Hollwey, E., Colicchio, J. M., Anderson, I., Feng, X., Howard, M., & Zilberman, D. (2023) · Cell Reports · doi:10.1016/j.celrep.2023.112132 · Cited by 26

Stepwise use of genomics and transcriptomics technologies increases diagnostic yield in Mendelian disorders

Colin, E., Duffourd, Y., Chevarin, M., Tisserant, É., Verdez, S., Paccaud, J., Bruel, A., Mau‐Them, F. T., Denommé‐Pichon, A., Thévenon, J., et al. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1021920 · Cited by 27

YACHT : an ANI-based statistical test to detect microbial presence/absence in a metagenomic sample

Koslicki, D., White, S., Ma, C., & Novikov, A. (2024) · Bioinformatics · doi:10.1093/bioinformatics/btae047 · Cited by 25

Unbiased integration of single cell multi-omics dataPreprint

Dou, J., Liang, S., Mohanty, V., Cheng, X., Kim, S., Choi, J., Li, Y., Rezvani, K., Chen, R., & Chen, K. (2020) · Research Square · doi:10.1101/2020.12.11.422014 · Cited by 28

Contrasting and combining transcriptome complexity captured by short and long RNA sequencing readsPreprint

Han, S. W., Jewell, S., Thomas‐Tikhonenko, A., & Barash, Y. (2024) · Genome Research · doi:10.1101/gr.278659.123 · Cited by 25

Combining DNA and protein alignments to improve genome annotation with LiftOnPreprint

Chao, K.-H., Heinz, J., Hoh, C., Mao, A., Shumate, A., Pertea, M., & Salzberg, S. L. (2024) · Genome Research · doi:10.1101/gr.279620.124 · Cited by 29

Embeddings of genomic region sets capture rich biological associations in lower dimensions

Gharavi, E., Gu, A., Zheng, G., Smith, J. P., Cho, H. J., Zhang, A., Brown, D. E., & Sheffield, N. C. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab439 · Cited by 25

Physical and Chemicals Mutagenesis in Plant Breeding

Bado, S., Forster, B. P., & Maghuly, F. (2023) · Springer eBooks · doi:10.1007/978-981-16-9720-3_3 · Cited by 24

Integration of Artificial Intelligence, Machine Learning and Deep Learning Techniques in Genomics: Review on Computational Perspectives for NGS Analysis of DNA and RNA Seq Data

Chandrashekar, K. S., Niranjan, V., Vishal, A., & Setlur, A. S. (2024) · Current Bioinformatics · doi:10.2174/0115748936284044240108074937 · Cited by 28

Benchmarking computational methods for single-cell chromatin data analysis

Luo, S., Germain, P., Robinson, M. D., & von Meyenn, F. (2024) · Genome biology · doi:10.1186/s13059-024-03356-x · Cited by 20

Circulating Tumor DNA detection in cancer: a comprehensive overview of current detection methods and prospects

de Abreu, A. R., Wyninckx, A., Vandamme, T., de Beeck, K. O., Camp, G. V., Peeters, M., Laurent‐Puig, P., Taı̈eb, J., Taly, V., & Benhaïm, L. (2025) · The Oncologist · doi:10.1093/oncolo/oyaf204 · Cited by 29

Application of phylogenomic tools to unravel anthozoan evolution

Quek, Z. B. R., & Huang, D. (2021) · Coral Reefs · doi:10.1007/s00338-021-02072-3 · Cited by 24

HBV Integration Induces Complex Interactions between Host and Viral Genomic Functions at the Insertion Site

Zhang, D., Zhang, K., Protzer, U., & Zeng, C. (2021) · Journal of Clinical and Translational Hepatology · doi:10.14218/jcth.2021.00062 · Cited by 26

A chromosomal level genome sequence for Quasipaa spinosa (Dicroglossidae) reveals chromosomal evolution and population diversity

Hu, X., Jiang, Z., Ming, Y., Jian, J., Jiang, S., Zhang, D., Zhang, J., Zheng, S., Fang, X., Yang, Y., et al. (2021) · Molecular Ecology Resources · doi:10.1111/1755-0998.13560 · Cited by 25

Recent advances in understanding the ecology of the filamentous bacteria responsible for activated sludge bulking

Nittami, T., & Batinovic, S. (2021) · Letters in Applied Microbiology · doi:10.1111/lam.13634 · Cited by 24

Identification of alternative splicing-derived cancer neoantigens for mRNA vaccine development

Cheng, R., Xu, Z., Luo, M., Wang, P., Cao, H., Jin, X., Zhou, W., Xiao, L., & Jiang, Q. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab553 · Cited by 25

Towards standardized and reproducible research in skin microbiomes

Ruuskanen, M. O., Vats, D., Potbhare, R., RaviKumar, A., Munukka, E., Ashma, R., & Lahti, L. (2022) · Environmental Microbiology · doi:10.1111/1462-2920.15945 · Cited by 24

Novel primers for 16S rRNA gene-based archaeal and bacterial community analysis in oceanic trench sediments

Yang, N., Tian, C., Lv, Y., Hou, J., Yang, Z., Xiao, X., & Zhang, Y. (2022) · Applied Microbiology and Biotechnology · doi:10.1007/s00253-022-11893-3 · Cited by 26

A high-throughput multiplexing and selection strategy to complete bacterial genomes

Arredondo-Alonso, S., Pöntinen, A. K., Cléon, F., Gladstone, R. A., Schürch, A. C., Johnsen, P. J., Samuelsen, Ø., & Corander, J. (2021) · GigaScience · doi:10.1093/gigascience/giab079 · Cited by 24

Evaluation of nanopore sequencing for epigenetic epidemiology: a comparison with DNA methylation microarrays

Flynn, R. J., Washer, S. J., Jeffries, A. R., Andrayas, A., Shireby, G. L., Meena Kumari, B., Schalkwyk, L. C., Mill, J. S., & Hannon, E. J. (2022) · Human Molecular Genetics · doi:10.1093/hmg/ddac112 · Cited by 24

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

Jeong, Y., Sousa, L. B. D. A. E., Thalmeier, D., Tóth, R., Ganslmeier, M., Breuer, K., Plass, C., & Lutsik, P. (2022) · Briefings in Bioinformatics · doi:10.1093/bib/bbac248 · Cited by 24

Using Nanopore Sequencing to Obtain Complete Bacterial Genomes from Saliva Samples

Baker, J. L. (2022) · mSystems · doi:10.1128/msystems.00491-22 · Cited by 25

High-Throughput Separation of Long DNA in Deterministic Lateral Displacement Arrays

Ström, O. E., Beech, J. P., & Tegenfeldt, J. O. (2022) · Micromachines · doi:10.3390/mi13101754 · Cited by 24

Genetic Modifiers of Sickle Cell Disease

Pincez, T., Ashley‐Koch, A. E., Lettre, G., & Telen, M. J. (2022) · Hematology/Oncology Clinics of North America · doi:10.1016/j.hoc.2022.06.006 · Cited by 28

Not a waste: Wastewater surveillance to enhance public health

Gitter, A., Oghuan, J., Godbole, A. R., Chavarria, C. A., Monserrat, C., Hu, T., Wang, Y., Maresso, A. W., Hanson, B., Mena, K. D., et al. (2023) · Frontiers in Chemical Engineering · doi:10.3389/fceng.2022.1112876 · Cited by 25

Characterization of complex structural variation in the CYP2D6-CYP2D7-CYP2D8 gene loci using single-molecule long-read sequencing

Turner, A., Derezinski, A. D., Gaedigk, A., Berres, M. E., Gregornik, D. B., Brown, K., Broeckel, U., & Scharer, G. H. (2023) · Frontiers in Pharmacology · doi:10.3389/fphar.2023.1195778 · Cited by 24

k-mer-Based Genome-Wide Association Studies in Plants: Advances, Challenges, and Perspectives

Karikari, B., Lemay, M., & Belzile, F. J. (2023) · Genes · doi:10.3390/genes14071439 · Cited by 28

Chaining for accurate alignment of erroneous long reads to acyclic variation graphs

Ma, J., Cáceres, M., Salmela, L., Mäkinen, V., & Tomescu, A. I. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad460 · Cited by 23

Single-cell multi-omics topic embedding reveals cell-type-specific and COVID-19 severity-related immune signatures

Zhou, M., Zhang, H., Bai, Z., Mann‐Krzisnik, D., Wang, F., & Li, Y. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100563 · Cited by 24

FL-circAS: an integrative resource and analysis for full-length sequences and alternative splicing of circular RNAs with nanopore sequencing

Chiang, T.-W., Jhong, S.-E., Chen, Y., Chen, C.-Y., Wu, W.-S., & Chuang, T. (2023) · Nucleic Acids Research · doi:10.1093/nar/gkad829 · Cited by 23

An extension of the Walsh-Hadamard transform to calculate and model epistasis in genetic landscapes of arbitrary shape and complexity

Faure, A. J., Lehner, B., Pina, V. M., Colomé, C. S., & Weghorn, D. (2024) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1012132 · Cited by 24

Cross‐Modal Graph Contrastive Learning with Cellular Images

Zheng, S., Rao, J., Zhang, J., Zhou, L., Xie, J., Cohen, E., Lu, W., Li, C., & Yang, Y. (2024) · Advanced Science · doi:10.1002/advs.202404845 · Cited by 23

Comprehensive and deep evaluation of structural variation detection pipelines with third-generation sequencing data

Liu, Z., Xie, Z., & Li, M. (2024) · Genome biology · doi:10.1186/s13059-024-03324-5 · Cited by 25

Long-read proteogenomics to connect disease-associated sQTLs to the protein isoform effectors of disease

Abood, A., Mesner, L. D., Jeffery, E. D., Murali, M., Lehe, M. D., Saquing, J., Farber, C. R., & Sheynkman, G. (2024) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2024.07.003 · Cited by 25

Extreme mitochondrial reduction in a novel group of free-living metamonads

Williams, S. K., Jerlström-Hultqvist, J., Eglit, Y., Salas-Leiva, D. E., Curtis, B. A., Orr, R. J. S., Stairs, C. W., Atalay, T. N., MacMillan, N., Simpson, A. G. B., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-50991-w · Cited by 23

An Improved Chromosome‐scale Genome Assembly and Population Genetics resource for Populus tremula .

Robinson, K. M., Schiffthaler, B., Liu, H., Rydman, S. M., Rendón‐Anaya, M., Kalman, T. A., Kumar, V., Canovi, C., Bernhardsson, C., Delhomme, N., et al. (2024) · Physiologia Plantarum · doi:10.1111/ppl.14511 · Cited by 24

GUNC: Detection of Chimerism and Contamination in Prokaryotic GenomesPreprint

Orakov, A. N., Fullam, A., Coelho, L. P., Khedkar, S., Szklarczyk, D., Mende, D. R., Schmidt, T., & Peer Bork, B. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.16.422776 · Cited by 24

Challenges in identifying mRNA transcript starts and ends from long-read sequencing dataPreprint

Calvo-Roitberg, E., Daniels, R. F., & Pai, A. A. (2024) · Genome Research · doi:10.1101/gr.279559.124 · Cited by 24

Comparing assembly strategies for third-generation sequencing technologies across different genomes

Espinosa, E., Bautista, R., Fernandez, I., Jiménez, R. L., Zapata, E. L., & Plata, Ó. (2023) · Genomics · doi:10.1016/j.ygeno.2023.110700 · Cited by 26

Enhancing Clinical Utility: Utilization of International Standards and Guidelines for Metagenomic Sequencing in Infectious Disease Diagnosis

Kan, C.-M., Tsang, H. F., Pei, X. M., Ng, S. S. M., Yim, A. K., Yu, A. C.-S., & Wong, S. C. C. (2024) · International Journal of Molecular Sciences · doi:10.3390/ijms25063333 · Cited by 28

Decoding the m6A epitranscriptomic landscape for biotechnological applications using a direct RNA sequencing approach

Liu, C., Liang, H., Wan, A. H., Xiao, M., Sun, L., Yu, Y., Yan, S., Deng, Y., Liu, R., Fang, J., et al. (2025) · Nature Communications · doi:10.1038/s41467-025-56173-6 · Cited by 25

ModiDeC: a multi-RNA modification classifier for direct nanopore sequencing

Alagna, N., Mündnich, S., Miedema, J., Pastore, S., Lehmann, L., Wierczeiko, A., Friedrich, J., Walz, L., Jörg, M., Butto, T., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkaf673 · Cited by 23

Comparison of current methods for genome-wide DNA methylation profiling

de Abreu, A. R., Ibrahim, J., Lemonidis, V., Mateiu, L. M., Camp, G. V., & de Beeck, K. O. (2025) · Epigenetics & Chromatin · doi:10.1186/s13072-025-00616-3 · Cited by 23

Long-read sequencing transcriptome quantification with lr-kallisto

Loving, R. K., Sullivan, D. K., Reese, F., Rebboah, E., Sakr, J., Rezaie, N., Liang, H. Y., Filimban, G., Kawauchi, S., Booeshaghi, A. S., et al. (2025) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1013692 · Cited by 23

More than causing (epi)genomic instability: emerging physiological implications of transposable element modulation

Hsu, P., Yu, S., Tsai, Y., Chang, J.-Y., Tsai, L., Ye, C.-H., Song, N.-Y., Yau, L.-C., & Lin, S. (2021) · Journal of Biomedical Science · doi:10.1186/s12929-021-00754-2 · Cited by 24

Current practices and emerging possibilities for reducing the spread of oomycete pathogens in terrestrial and aquatic production systems in the European Union

Benavent-Celma, C., López‐García, N., Ruba, T., Ściślak, M. E., Street-Jones, D., van West, P., Woodward, S., & Witzell, J. (2021) · Fungal Biology Reviews · doi:10.1016/j.fbr.2021.10.001 · Cited by 25

Human land use impacts viral diversity and abundance in a New Zealand river

French, R. K., Charon, J., Lay, C. L., Muller, C. G., & Holmes, E. C. (2022) · Virus Evolution · doi:10.1093/ve/veac032 · Cited by 27

Evaluating Illumina-, Nanopore-, and PacBio-based genome assembly strategies with the bald notothen,Trematomus borchgrevinki

Rayamajhi, N., CHENG, C.-H. C., & Catchen, J. (2022) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkac192 · Cited by 27

The impact of Piscirickettsia salmonis infection on genome-wide DNA methylation profile in Atlantic Salmon

Mukiibi, R., Peñaloza, C., Gutiérrez, A. P., Yañez, J. M., Houston, R. D., & Robledo, D. (2022) · Genomics · doi:10.1016/j.ygeno.2022.110503 · Cited by 23

Enhanced mitochondrial genome analysis: bioinformatic and long-read sequencing advances and their diagnostic implications

Macken, W. L., Falabella, M., Pizzamiglio, C., Woodward, C. E., Scotchman, E., Chitty, L. S., Polke, J. M., Bugiardini, E., Hanna, M. G., Vandrovcová, J., et al. (2023) · Expert Review of Molecular Diagnostics · doi:10.1080/14737159.2023.2241365 · Cited by 23

Nitrate-driven anaerobic oxidation of ethane and butane by bacteria

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Accelerated Dynamic Time Warping on GPU for Selective Nanopore Sequencing

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Transkingdom Network Analysis (TkNA): a systems framework for inferring causal factors underlying host–microbiota and other multi-omic interactions

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SHARE-Topic: Bayesian interpretable modeling of single-cell multi-omic data

Kazwini, N. E., & Sanguinetti, G. (2024) · Genome biology · doi:10.1186/s13059-024-03180-3 · Cited by 22

The genetic architecture of protein interaction affinity and specificity

Bendel, A. M., Faure, A. J., Klein, D., Shimada, K., Lyautey, R., Schiffelholz, N., Kempf, G., Cavadini, S., Lehner, B., & Diss, G. (2024) · Nature Communications · doi:10.1038/s41467-024-53195-4 · Cited by 22

Graph contrastive learning as a versatile foundation for advanced scRNA-seq data analysis

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Global Genomics of Man-O'-War (Physalia) Reveals Ocean Surface Biodiversity

Church, S. H., Abedon, R. B., Ahuja, N., Anthony, C. J., Destanović, D., Ramirez, D. A., Rojas, L. M., Albinsson, M. E., Trasobares, I. Á., Bergemann, R., et al. (2024) · Current Biology · doi:10.1016/j.cub.2025.05.066 · Cited by 23

Potential applications and future prospects of metagenomics in aquatic ecosystems

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Genome analysis of Spiroplasma citri strains from different host plants and its leafhopper vectors

Rattner, R. J., Thapa, S. P., Dang, T., Osman, F., Selvaraj, V., Maheshwari, Y., Pagliaccia, D., Espíndola, A. S., Hajeri, S., Chen, J., et al. (2021) · BMC Genomics · doi:10.1186/s12864-021-07637-8 · Cited by 22

Evaluation of whole-genome sequence data analysis approaches for short- and long-read sequencing of Mycobacterium tuberculosis

Peker, N., Schuele, L., Kok, N., Miani, M. A. T., Neuenschwander, S. M., de Beer, J., Akkerman, O. W., Peter, S., Ramette, A., Merker, M., et al. (2021) · Microbial Genomics · doi:10.1099/mgen.0.000695 · Cited by 22

Long-read sequencing on the SMRT platform enables efficient haplotype linkage analysis in preimplantation genetic testing for β-thalassemia

Wu, H., Chen, D., Zhao, Q., Shen, X., Liao, Y.-B., Li, P., Chiu, P. C. N., & Zhou, C. (2022) · Journal of Assisted Reproduction and Genetics · doi:10.1007/s10815-022-02415-1 · Cited by 22

Hybridization Dynamics and Extensive Introgression in the Daphnia longispina Species Complex: New Insights from a High-Quality Daphnia galeata Reference Genome

Nickel, J. H., Schell, T., Holtzem, T., Thielsch, A., Dennis, S. R., Schlick-Steiner, B. C., Steiner, F. M., Möst, M., Pfenninger, M., Schwenk, K., et al. (2021) · Genome Biology and Evolution · doi:10.1093/gbe/evab267 · Cited by 22

Pathways to polar adaptation in fishes revealed by long‐read sequencing

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NAb-seq: an accurate, rapid, and cost-effective method for antibody long-read sequencing in hybridoma cell lines and single B cells

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Detection of nucleotide modifications in bacteria and bacteriophages: Strengths and limitations of current technologies and software

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NanoSTR: A method for detection of target short tandem repeats based on nanopore sequencing data

Lang, J., Xu, Z., Wang, Y., Jiguo, S., & Yang, Z. P. (2023) · Frontiers in Molecular Biosciences · doi:10.3389/fmolb.2023.1093519 · Cited by 22

Implementation of Nanopore sequencing as a pragmatic workflow for copy number variant confirmation in the clinic

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DISCERN: deep single-cell expression reconstruction for improved cell clustering and cell subtype and state detection

Hausmann, F., Ergen, C., Khatri, R., Marouf, M., Hänzelmann, S., Gagliani, N., Huber, S., Machart, P., & Bonn, S. (2023) · Genome biology · doi:10.1186/s13059-023-03049-x · Cited by 21

scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning

Wang, J., Fonseca, G. J., & Ding, J. (2024) · Nature Communications · doi:10.1038/s41467-024-50150-1 · Cited by 22

long-read-tools.org: an interactive catalogue of analysis methods for long-read sequencing data

Amarasinghe, S., Ritchie, M., & Gouil, Q. A. (2021) · La Trobe University · doi:10.26181/14337101

A comprehensive evaluation of long read error correction methods

Zhang, H., Jain, C., & Aluru, S. (2020) · BMC Genomics · doi:10.1186/s12864-020-07227-0 · Cited by 150

Long-read error correction: a survey and qualitative comparisonPreprint

Morisse, P., Thierry Lecroq, B., & Lefebvre, A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.03.06.977975 · Cited by 16

Additional file 1 of Opportunities and challenges in long-read sequencing data analysis

Amarasinghe, S., Su, S., Dong, X., Zappia, L., Ritchie, M., & Gouil, Q. A. (2020) · Figshare · doi:10.6084/m9.figshare.11826234

LoRDEC: a tool for correcting errors in long sequencing reads

Rivals, É. (2015) · HAL