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 · see citing works

<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 · see citing works

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 · see citing works

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 · see citing works

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 · see citing works

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 8,994 · see citing works

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 · see citing works

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 7,340 · see citing works

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 · see citing works

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 · see citing works

Alternative isoform regulation in human tissue transcriptomes

Wang, E. T., Sandberg, R., Luo, S., Khrebtukova, I., Zhang, L., Mayr, C., Kingsmore, S. F., Schroth, G. P., & Burge, C. B. (2008) · Nature · doi:10.1038/nature07509 · Cited by 5,181 · see citing works

Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq

Dominissini, D., Moshitch-Moshkovitz, S., Schwartz, S., Salmon-Divon, M., Ungar, L., Osenberg, S., Cesarkas, K., Jacob-Hirsch, J., Amariglio, N., Kupiec, M., et al. (2012) · Nature · doi:10.1038/nature11112 · Cited by 4,884 · see citing works

Coming of age: ten years of next-generation sequencing technologies

Goodwin, S., McPherson, J. D., & McCombie, W. R. (2016) · Nature Reviews Genetics · doi:10.1038/nrg.2016.49 · Cited by 4,352 · see citing works

Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons

Meyer, K. D., Saletore, Y., Zumbo, P., Elemento, O., Mason, C. E., & Jaffrey, S. R. (2012) · Cell · doi:10.1016/j.cell.2012.05.003 · Cited by 4,223 · see citing works

Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing

Pan, Q., Shai, O., Lee, L. J., Frey, B. J., & Blencowe, B. J. (2008) · Nature Genetics · doi:10.1038/ng.259 · Cited by 3,951 · see citing works

Accurate whole human genome sequencing using reversible terminator chemistry

Bentley, D. R., Balasubramanian, S., Swerdlow, H. P., Smith, G. P., Milton, J., Brown, C. G., Hall, K. P., Evers, D. J., Barnes, C. L., Bignell, H. R., et al. (2008) · Nature · doi:10.1038/nature07517 · Cited by 3,684 · see citing works

Tet proteins can convert 5-methylcytosine to 5-formylcytosine and 5-carboxylcytosine

Ito, S., Shen, L., Dai, Q., Wu, S. C., Collins, L. B., Swenberg, J. A., He, C., & Zhang, Y. (2011) · Science · doi:10.1126/science.1210597 · Cited by 3,451 · see citing works

A genomic sequencing protocol that yields a positive display of 5-methylcytosine residues in individual DNA strands

Frommer, M., McDonald, L. E., Millar, D. S., Collis, C. M., Watt, F., Grigg, G. W., Molloy, P. L., & Paul, C. L. (1992) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.89.5.1827 · Cited by 3,238 · see citing works

Performance of neural network basecalling tools for Oxford Nanopore sequencing

Wick, R. R., Judd, L. M., & Holt, K. E. (2019) · Genome Biology · doi:10.1186/s13059-019-1727-y · Cited by 3,221 · see citing works

The Subread aligner: fast, accurate and scalable read mapping by seed-and-vote

Liao, Y., Smyth, G. K., & Shi, W. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt214 · Cited by 3,064 · see citing works

Fast and accurate de novo genome assembly from long uncorrected readsPreprint

Vaser, R., Sović, I., Nagarajan, N., & Šikić, M. (2017) · Genome Research · doi:10.1101/gr.214270.116 · Cited by 3,059 · see citing works

The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads

Liao, Y., Smyth, G. K., & Shi, W. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz114 · Cited by 2,965 · see citing works

An integrated semiconductor device enabling non-optical genome sequencing

Rothberg, J. M., Hinz, W., Rearick, T. M., Schultz, J., Mileski, W., Davey, M. S., Leamon, J. H., Johnson, K., Milgrew, M. J., Edwards, M. M., et al. (2011) · Nature · doi:10.1038/nature10242 · Cited by 2,187 · see citing works

A tale of three next generation sequencing platforms: comparison of Ion torrent, pacific biosciences and illumina MiSeq sequencers

Quail, M., Smith, M. E., Coupland, P., Otto, T. D., Harris, S. R., Connor, T. R., Bertoni, A., Swerdlow, H. P., & Gu, Y. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-341 · Cited by 2,031 · see citing works

Nanopore sequencing and assembly of a human genome with ultra-long reads

Jain, M., Koren, S., Miga, K. H., Quick, J., Rand, A. C., Sasani, T. A., Tyson, J. R., Beggs, A. D., Dilthey, A. T., Fiddes, I. T., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4060 · Cited by 1,892 · see citing works

Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome

Wenger, A. M., Peluso, P., Rowell, W. J., Chang, P.-C., Hall, R. J., Concepcion, G. T., Ebler, J., Fungtammasan, A., Kolesnikov, A., Olson, N. D., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0217-9 · Cited by 1,841 · see citing works

m6A RNA methylation promotes XIST-mediated transcriptional repression

Patil, D. P., Chen, C.-K., Pickering, B. F., Chow, A., Jackson, C., Guttman, M., & Jaffrey, S. R. (2016) · Nature · doi:10.1038/nature19342 · Cited by 1,747 · see citing works

The Oxford Nanopore MinION: delivery of nanopore sequencing to the genomics community

Jain, M., Olsen, H. E., Paten, B., & Akeson, M. (2016) · Genome Biology · doi:10.1186/s13059-016-1103-0 · Cited by 1,588 · see citing works

Direct detection of DNA methylation during single-molecule, real-time sequencing

Flusberg, B. A., Webster, D. R., Lee, J. H., Travers, K. J., Olivares, E. C., Clark, T. A., Korlach, J., & Turner, S. W. (2010) · Nature Methods · doi:10.1038/nmeth.1459 · Cited by 1,460 · see citing works

The sequence of sequencers: The history of sequencing DNA

Heather, J. M., & Chain, B. (2016) · Genomics · doi:10.1016/j.ygeno.2015.11.003 · Cited by 1,397 · see citing works

Fast and accurate long-read assembly with wtdbg2

Ruan, J., & Li, H. (2019) · Nature Methods · doi:10.1038/s41592-019-0669-3 · Cited by 1,314 · see citing works

Mapping copy number variation by population-scale genome sequencing

1000 Genomes Project, Mills, R. E., Walter, K., Stewart, C., Handsaker, R. E., Chen, K., Alkan, C., Abyzov, A., Yoon, S. C., Ye, K., et al. (2011) · Nature · doi:10.1038/nature09708 · Cited by 1,140 · see citing works

Detecting DNA cytosine methylation using nanopore sequencing

Simpson, J. T., Workman, R. E., Zuzarte, P. C., David, M., Dursi, L. J., & Timp, W. (2017) · Nature Methods · doi:10.1038/nmeth.4184 · Cited by 1,109 · see citing works

Reversible methylation of m6Am in the 5′ cap controls mRNA stability

Mauer, J., Luo, X., Blanjoie, A., Jiao, X., Grozhik, A. V., Patil, D. P., Linder, B., Pickering, B. F., Vasseur, J., Chen, Q., et al. (2016) · Nature · doi:10.1038/nature21022 · Cited by 1,072 · see citing works

Assembling large genomes with single-molecule sequencing and locality-sensitive hashing

Berlin, K., Koren, S., Chin, C.-S., Drake, J. P., Landolin, J. M., & Phillippy, A. M. (2015) · Nature Biotechnology · doi:10.1038/nbt.3238 · Cited by 928 · see citing works

Acetylation of Cytidine in mRNA Promotes Translation Efficiency

Arango, D., Sturgill, D., Alhusaini, N., Dillman, A. A., Sweet, T. J., Hanson, G., Hosogane, M., Sinclair, W. R., Nanan, K. K., Mandler, M. D., et al. (2018) · Cell · doi:10.1016/j.cell.2018.10.030 · Cited by 862 · see citing works

Whole-genome re-sequencing

Bentley, D. (2006) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2006.10.009 · Cited by 805 · see citing works

5-Hydroxymethylcytosine in the mammalian zygote is linked with epigenetic reprogramming

Wossidlo, M., Nakamura, T., Lepikhov, K., Marques, C. J., Zakhartchenko, V., Boiani, M., Arand, J., Nakano, T., Reik, W., & Walter, J. (2011) · Nature Communications · doi:10.1038/ncomms1240 · Cited by 793 · see citing works

Resolving the complexity of the human genome using single-molecule sequencing

Chaisson, M., Huddleston, J., Dennis, M. Y., Sudmant, P. H., Malig, M., Hormozdiari, F., Antonacci, F., Surti, U., Sandstrom, R. S., Boitano, M., et al. (2014) · Nature · doi:10.1038/nature13907 · Cited by 783 · see citing works

Single molecule real-time (SMRT) sequencing comes of age: applications and utilities for medical diagnostics

Ardui, S., Ameur, A., Vermeesch, J. R., & Hestand, M. S. (2018) · Nucleic Acids Research · doi:10.1093/nar/gky066 · Cited by 741 · see citing works

Chromosome-scale shotgun assembly using an in vitro method for long-range linkage

Putnam, N. H., O'Connell, B. L., Stites, J. C., Rice, B. J., Blanchette, M., Calef, R., Troll, C. J., Fields, A., Hartley, P. D., Sugnet, C. W., et al. (2016) · Genome Research · doi:10.1101/gr.193474.115 · Cited by 732 · see citing works

Structural variant calling: the long and the short of it

Mahmoud, M., Gobet, N., Cruz-Dávalos, D. I., Mounier, N., Dessimoz, C., & Sedlazeck, F. J. (2019) · Genome Biology · doi:10.1186/s13059-019-1828-7 · Cited by 725 · see citing works

Nanopore native RNA sequencing of a human poly(A) transcriptome

Workman, R. E., Tang, A. D., Tang, P. S., Jain, M., Tyson, J. R., Razaghi, R., Zuzarte, P. C., Gilpatrick, T., Payne, A., Quick, J., et al. (2019) · Nature Methods · doi:10.1038/s41592-019-0617-2 · Cited by 708 · see citing works

A single-molecule long-read survey of the human transcriptome

Sharon, D., Tilgner, H., Grubert, F., & Snyder, M. (2013) · Nature Biotechnology · doi:10.1038/nbt.2705 · Cited by 701 · see citing works

Assessment of transcript reconstruction methods for RNA-seq

The RGASP Consortium, Steijger, T., Abril, J. F., Engström, P. G., Kokocinski, F., Hubbard, T. J., Guigó, R., Harrow, J., & Bertone, P. (2013) · Nature Methods · doi:10.1038/nmeth.2714 · Cited by 699 · see citing works

Haplotyping germline and cancer genomes with high-throughput linked-read sequencing

Zheng, G. X. Y., Lau, B. T., Schnall-Levin, M., Jarosz, M. V., Bell, J., Hindson, C. M., Kyriazopoulou-Panagiotopoulou, S., Masquelier, D. A., Merrill, L., Terry, J. M., et al. (2016) · Nature Biotechnology · doi:10.1038/nbt.3432 · Cited by 678 · see citing works

From squiggle to basepair: computational approaches for improving nanopore sequencing read accuracy

Rang, F. J., Kloosterman, W. P., & de Ridder, J. (2018) · Genome biology · doi:10.1186/s13059-018-1462-9 · Cited by 673 · see citing works

Structural variation in the sequencing era

Ho, S. S., Urban, A. E., & Mills, R. E. (2019) · Nature Reviews Genetics · doi:10.1038/s41576-019-0180-9 · Cited by 608 · see citing works

A survey of the sorghum transcriptome using single-molecule long reads

Abdel‐Ghany, S. E., Hamilton, M., Jacobi, J. L., Ngam, P. B., Devitt, N. P., Schilkey, F., Ben‐Hur, A., & Reddy, A. S. N. (2016) · Nature Communications · doi:10.1038/ncomms11706 · Cited by 595 · see citing works

The advantages of SMRT sequencing

Roberts, R. J., Carneiro, M. O., & Schatz, M. C. (2013) · Genome biology · doi:10.1186/gb-2013-14-6-405 · Cited by 584 · see citing works

Improved reference genome of Aedes aegypti informs arbovirus vector control

Matthews, B. J., Dudchenko, O., Kingan, S. B., Koren, S., Antoshechkin, I. A., Crawford, J. E., Glassford, W. J., Herre, M., Redmond, S. N., Rose, N. H., et al. (2018) · Nature · doi:10.1038/s41586-018-0692-z · Cited by 578 · see citing works

Nanopore sequencing and the Shasta toolkit enable efficient de novo assembly of eleven human genomes

Shafin, K., Pesout, T., Lorig-Roach, R., Haukness, M., Olsen, H. E., Bosworth, C., Armstrong, J., Tigyi, K., Maurer, N., Koren, S., et al. (2020) · Nature Biotechnology · doi:10.1038/s41587-020-0503-6 · Cited by 567 · see citing works

N6-methyl-adenine: an epigenetic signal for DNA–protein interactions

Wion, D., & Casadesús, J. (2006) · Nature Reviews Microbiology · doi:10.1038/nrmicro1350 · Cited by 527 · see citing works

Accurate detection of m6A RNA modifications in native RNA sequences

Liu, H., Begik, O., Lucas, M. C., Ramírez, J. M., Mason, C. E., Wiener, D., Schwartz, S., Mattick, J. S., Smith, M. A., & Novoa, E. M. (2019) · Nature Communications · doi:10.1038/s41467-019-11713-9 · Cited by 516 · see citing works

Mapping DNA methylation with high-throughput nanopore sequencing

Rand, A. C., Jain, M., Eizenga, J. M., Musselman-Brown, A., Olsen, H. E., Akeson, M., & Paten, B. (2017) · Nature Methods · doi:10.1038/nmeth.4189 · Cited by 507 · see citing works

Full-length transcript characterization of SF3B1 mutation in chronic lymphocytic leukemia reveals downregulation of retained introns

Tang, A. D., Soulette, C. M., van Baren, M. J., Hart, K. L., Hrabeta‐Robinson, E., Wu, C. J., & Brooks, A. N. (2020) · Nature Communications · doi:10.1038/s41467-020-15171-6 · Cited by 497 · see citing works

Characterizing the Major Structural Variant Alleles of the Human Genome

Audano, P. A., Sulovari, A., Graves-Lindsay, T. A., Cantsilieris, S., Sorensen, M., Welch, A. E., Dougherty, M. L., Nelson, B. J., Shah, A., Dutcher, S. K., et al. (2019) · Cell · doi:10.1016/j.cell.2018.12.019 · Cited by 492 · see citing works

The birth of the Epitranscriptome: deciphering the function of RNA modifications

Saletore, Y., Meyer, K. D., Korlach, J., Vilfan, I. D., Jaffrey, S. R., & Mason, C. E. (2012) · Genome biology · doi:10.1186/gb-2012-13-10-175 · Cited by 485 · see citing works

Comprehensive comparison of Pacific Biosciences and Oxford Nanopore Technologies and their applications to transcriptome analysis

Weirather, J. L., de Cesare, M., Wang, Y., Piazza, P., Sebastiano, V., Wang, X., Buck, D., & Au, K. F. (2017) · F1000Research · doi:10.12688/f1000research.10571.2 · Cited by 483 · see citing works

The advantages of SMRT sequencing

Roberts, R. J., Carneiro, M. O., & Schatz, M. C. (2013) · Genome biology · doi:10.1186/gb-2013-14-7-405 · Cited by 454 · see citing works

SQANTI: extensive characterization of long-read transcript sequences for quality control in full-length transcriptome identification and quantificationPreprint

Tardáguila, M., de la Fuente, L., Martí, C., Pereira, C., Pardo-Palacios, F. J., del Risco, H., Ferrell, M., Mellado-López, M., Macchietto, M. G., Verheggen, K., et al. (2018) · Genome Research · doi:10.1101/gr.222976.117 · Cited by 441 · see citing works

Ordered Restriction Maps of Saccharomyces cerevisiae Chromosomes Constructed by Optical Mapping

Schwartz, D. C., Li, X., Hernandez, L. I., Ramnarain, S. P., Huff, E. J., & Wang, Y.-K. (1993) · Science · doi:10.1126/science.8211116 · Cited by 411 · see citing works

One chromosome, one contig: complete microbial genomes from long-read sequencing and assembly

Koren, S., & Phillippy, A. M. (2014) · Current Opinion in Microbiology · doi:10.1016/j.mib.2014.11.014 · Cited by 406 · see citing works

Widespread Polycistronic Transcripts in Fungi Revealed by Single-Molecule mRNA Sequencing

Gordon, S., Tseng, E., Salamov, A. A., Zhang, J., Meng, X., Zhao, Z., Kang, D., Underwood, J. G., Grigoriev, I. V., Figueroa, M., et al. (2015) · PLoS ONE · doi:10.1371/journal.pone.0132628 · Cited by 403 · see citing works

Mapping and phasing of structural variation in patient genomes using nanopore sequencing

Cretu-Stancu, M., van Roosmalen, M. J., Renkens, I., Nieboer, M. M., Middelkamp, S., de Ligt, J., Pregno, G., Giachino, D. F., Mandrile, G., Valle-Inclán, J. E., et al. (2017) · Nature Communications · doi:10.1038/s41467-017-01343-4 · Cited by 392 · see citing works

Nanopore long-read RNAseq reveals widespread transcriptional variation among the surface receptors of individual B cells

Byrne, A., Beaudin, A. E., Olsen, H. E., Jain, M., Cole, C., Palmer, T., DuBois, R. M., Forsberg, E. C., Akeson, M., & Vollmers, C. (2017) · Nature Communications · doi:10.1038/ncomms16027 · Cited by 379 · see citing works

Long reads: their purpose and place

Pollard, M., Gurdasani, D., Mentzer, A. J., Porter, T., & Sandhu, M. S. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy177 · Cited by 365 · see citing works

Mechanism and Function of Oxidative Reversal of DNA and RNA Methylation

Shen, L., Song, C., He, C., & Zhang, Y. (2014) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060713-035513 · Cited by 359 · see citing works

The Expanding Landscape of Alternative Splicing Variation in Human Populations

Park, E., Pan, Z., Zhang, Z., Lin, L., & Xing, Y. (2018) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2017.11.002 · Cited by 357 · see citing works

Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells

Gupta, I., Collier, P. G., Haase, B., Mahfouz, A., Joglekar, A., Floyd, T., Koopmans, F., Barres, B., Smit, A. B., Sloan, S. A., et al. (2018) · Nature Biotechnology · doi:10.1038/nbt.4259 · Cited by 343 · see citing works

Characterization of the human ESC transcriptome by hybrid sequencing

Au, K. F., Sebastiano, V., Afshar, P. T., Durruthy, J. D., Lee, L., Williams, B. A., van Bakel, H., Schadt, E. E., Reijo-Pera, R. A., Underwood, J. G., et al. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1320101110 · Cited by 341 · see citing works

Long-read sequence assembly of the gorilla genome

Gordon, D., Huddleston, J., Chaisson, M. J. P., Hill, C. M., Kronenberg, Z. N., Munson, K. M., Malig, M., Raja, A., Fiddes, I., Hillier, L. W., et al. (2016) · Science · doi:10.1126/science.aae0344 · Cited by 333 · see citing works

BulkVis: a graphical viewer for Oxford nanopore bulk FAST5 files

(2018) · doi:10.1093/bioinformatics/bty841 · Cited by 326 · see citing works

Detection of DNA base modifications by deep recurrent neural network on Oxford Nanopore sequencing data

Liu, Q., Li, F., Yu, G., Wang, D., Xiao, C., & Wang, K. (2019) · Nature Communications · doi:10.1038/s41467-019-10168-2 · Cited by 326 · see citing works

Rapid draft sequencing and real-time nanopore sequencing in a hospital outbreak of Salmonella

Quick, J., Ashton, P., Calus, S., Chatt, C., Gossain, S., Hawker, J. I., Nair, S., Neal, K. R., Nye, K., Peters, T. M., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0677-2 · Cited by 309 · see citing works

De novo Identification of DNA Modifications Enabled by Genome-Guided Nanopore Signal ProcessingPreprint

Stoiber, M. H., Quick, J., Egan, R. S., Lee, J. E., Celniker, S., Neely, R. K., Loman, N. J., Pennacchio, L. A., & Brown, J. B. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/094672 · Cited by 276 · see citing works

Comparison of long-read sequencing technologies in the hybrid assembly of complex bacterial genomes

Maio, N. D., Shaw, L. P., Hubbard, A. T. M., George, S. A., Sanderson, N. D., Swann, J., Wick, R. R., AbuOun, M., Stubberfield, E. J., Hoosdally, S., et al. (2019) · Microbial Genomics · doi:10.1099/mgen.0.000294 · Cited by 273 · see citing works

Defining a personal, allele-specific, and single-molecule long-read transcriptome

Tilgner, H., Grubert, F., Sharon, D., & Snyder, M. P. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1400447111 · Cited by 266 · see citing works

Long-read sequencing and de novo assembly of a Chinese genome

Shi, L., Guo, Y., Dong, C., Huddleston, J., Yang, H., Han, X., Fu, A., Li, Q., Li, N., Gong, S., et al. (2016) · Nature Communications · doi:10.1038/ncomms12065 · Cited by 257 · see citing works

A comprehensive examination of Nanopore native RNA sequencing for characterization of complex transcriptomes

Soneson, C., Yao, Y., Bratus-Neuenschwander, A., Patrignani, A., Robinson, M. D., & Hussain, S. (2019) · Nature Communications · doi:10.1038/s41467-019-11272-z · Cited by 257 · see citing works

Pacific biosciences sequencing technology for genotyping and variation discovery in human data

Carneiro, M. O., Russ, C., Ross, M. G., Gabriel, S., Nusbaum, C., & DePristo, M. A. (2012) · BMC Genomics · doi:10.1186/1471-2164-13-375 · Cited by 255 · see citing works

Long-read genome sequencing identifies causal structural variation in a Mendelian disease

Merker, J. D., Wenger, A. M., Sneddon, T. P., Grove, M. E., Zappala, Z., Frésard, L., Waggott, D. M., Utiramerur, S., Hou, Y., Smith, K. S., et al. (2017) · Genetics in Medicine · doi:10.1038/gim.2017.86 · Cited by 253 · see citing works

DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning

Ni, P., Huang, N., Zhang, Z., Wang, D., Liang, F., Yu, M., Xiao, C., Luo, F., & Wang, J. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz276 · Cited by 252 · see citing works

DeepNano: Deep recurrent neural networks for base calling in MinION nanopore reads

Boža, V., Brejová, B., & Vinař, T. (2017) · PLoS ONE · doi:10.1371/journal.pone.0178751 · Cited by 246 · see citing works

Errors in long-read assemblies can critically affect protein prediction

Watson, M., & Warr, A. (2019) · Nature Biotechnology · doi:10.1038/s41587-018-0004-z · Cited by 242 · see citing works

Efficient and unique cobarcoding of second-generation sequencing reads from long DNA molecules enabling cost-effective and accurate sequencing, haplotyping, and de novo assemblyPreprint

Wang, O., Chin, R. G., Cheng, X., Wu, M. K. Y., Mao, Q., Tang, J., Sun, Y., Anderson, E., Lam, H. K., Chen, D., et al. (2019) · Genome Research · doi:10.1101/gr.245126.118 · Cited by 232 · see citing works

Improving nanopore read accuracy with the R2C2 method enables the sequencing of highly multiplexed full-length single-cell cDNA

Volden, R., Palmer, T., Byrne, A., Cole, C., Schmitz, R. J., Green, R. E., & Vollmers, C. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1806447115 · Cited by 228 · see citing works

Deciphering bacterial epigenomes using modern sequencing technologies

Beaulaurier, J., Schadt, E. E., & Fang, G. (2018) · Nature Reviews Genetics · doi:10.1038/s41576-018-0081-3 · Cited by 228 · see citing works

Comprehensive transcriptome analysis using synthetic long-read sequencing reveals molecular co-association of distant splicing events

Tilgner, H., Jahanbani, F., Blauwkamp, T., Moshrefi, A., Jaeger, E., Chen, F., Harel, I., Bustamante, C. D., Rasmussen, M., & Snyder, M. P. (2015) · Nature Biotechnology · doi:10.1038/nbt.3242 · Cited by 223 · see citing works

Direct RNA sequencing on nanopore arrays redefines the transcriptional complexity of a viral pathogen

Depledge, D. P., Srinivas, K. P., Sadaoka, T., Bready, D., Mori, Y., Placantonakis, D. G., Mohr, I., & Wilson, A. C. (2019) · Nature Communications · doi:10.1038/s41467-019-08734-9 · Cited by 217 · see citing works

A hybrid approach for de novo human genome sequence assembly and phasing

Mostovoy, Y., Levy‐Sakin, M., Lam, J. C., Lam, E. T., Hastie, A. R., Marks, P., Lee, J., Chu, C., Lin, C. J., Džakula, Ž., et al. (2016) · Nature Methods · doi:10.1038/nmeth.3865 · Cited by 216 · see citing works

DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics

Nowicka, M., & Robinson, M. D. (2016) · F1000Research · doi:10.12688/f1000research.8900.2 · Cited by 207 · see citing works

De Novo Assembly of a New Solanum pennellii Accession Using Nanopore Sequencing

Schmidt, M., Vogel, A., Denton, A. K., Istace, B., Wormit, A., van de Geest, H., Bolger, M., Alseekh, S., Maß, J., Pfaff, C., et al. (2017) · The Plant Cell · doi:10.1105/tpc.17.00521 · Cited by 202 · see citing works

Illumina TruSeq Synthetic Long-Reads Empower De Novo Assembly and Resolve Complex, Highly-Repetitive Transposable Elements

McCoy, R. C., Taylor, R. W., Blauwkamp, T. A., Kelley, J. L., Kertesz, M., Pushkarev, D., Petrov, D. A., & Fiston-Lavier, A.-S. (2014) · PLoS ONE · doi:10.1371/journal.pone.0106689 · Cited by 199 · see citing works

Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces

Lee, N., Hwang, S., Kim, J., Cho, S., Palsson, B. Ø., & Cho, B. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.06.024 · Cited by 196 · see citing works

A survey of the complex transcriptome from the highly polyploid sugarcane genome using full-length isoform sequencing and de novo assembly from short read sequencing

Hoang, N. V., Furtado, A., Mason, P. J., Marquardt, A., Kasirajan, L., Thirugnanasambandam, P. P., Botha, F. C., & Henry, R. J. (2017) · BMC Genomics · doi:10.1186/s12864-017-3757-8 · Cited by 195 · see citing works

Sequencing of human genomes with nanopore technology

Bowden, R. J., Davies, R. W., Heger, A., Pagnamenta, A. T., de Cesare, M., Oikkonen, L., Parkes, D., Freeman, C., Dhalla, F., Patel, S. Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-09637-5 · Cited by 193 · see citing works

Chiron: translating nanopore raw signal directly into nucleotide sequence using deep learning

Teng, H., Cao, M. D., Hall, M. B., Duarte, T., Wang, S., & Coin, L. (2018) · GigaScience · doi:10.1093/gigascience/giy037 · Cited by 189 · see citing works

Single-molecule sequencing detection of N6-methyladenine in microbial reference materials

McIntyre, A. B. R., Alexander, N., Burton, A. S., Castro-Wallace, S. L., Chiu, C. Y., John, K. K., Stahl, S. E., Li, S., & Mason, C. E. (2019) · Nature Communications · doi:10.1038/s41467-019-08289-9 · Cited by 187 · see citing works

A technology-agnostic long-read analysis pipeline for transcriptome discovery and quantificationPreprint

Wyman, D., Balderrama-Gutierrez, G., Reese, F., Jiang, S., Rahmanian, S., Forner, S., Matheos, D. P., Zeng, W., Williams, B. A., Trout, D. E., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/672931 · Cited by 163 · see citing works

Analysis of RNA base modification and structural rearrangement by single-molecule real-time detection of reverse transcription

Vilfan, I. D., Tsai, Y., Clark, T. A., Wegener, J., Dai, Q., Yi, C., Pan, T., Turner, S. W., & Korlach, J. (2013) · Journal of Nanobiotechnology · doi:10.1186/1477-3155-11-8 · Cited by 159 · see citing works

Structural variants identified by Oxford Nanopore PromethION sequencing of the human genomePreprint

Coster, W. D., Rijk, P. D., Roeck, A. D., Pooter, T. D., D’Hert, S., Stražišar, M., Sleegers, K., & Broeckhoven, C. V. (2019) · Genome Research · doi:10.1101/gr.244939.118 · Cited by 159 · see citing works

FMLRC: Hybrid long read error correction using an FM-index

Wang, J., Holt, J., McMillan, L., & Jones, C. D. (2018) · BMC Bioinformatics · doi:10.1186/s12859-018-2051-3 · Cited by 158 · see citing works

Understanding RNA modifications: the promises and technological bottlenecks of the ‘epitranscriptome’

Schaefer, M., Kapoor, U., & Jantsch, M. F. (2017) · Open Biology · doi:10.1098/rsob.170077 · Cited by 152 · see citing works

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 · see citing works

Highly Contiguous Genome Assemblies of 15 Drosophila Species Generated Using Nanopore Sequencing

Miller, D. E., Staber, C. J., Zeitlinger, J., & Hawley, R. S. (2018) · G3 Genes Genomes Genetics · doi:10.1534/g3.118.200160 · Cited by 143 · see citing works

Capturing the dynamics of genome replication on individual ultra-long nanopore sequence reads

Müller, C. A., Boemo, M. A., Spingardi, P., Kessler, B. M., Kriaučionis, S., Simpson, J. T., & Nieduszynski, C. A. (2019) · Nature Methods · doi:10.1038/s41592-019-0394-y · Cited by 142 · see citing works

Improving and correcting the contiguity of long-read genome assemblies of three plant species using optical mapping and chromosome conformation capture dataPreprint

Jiao, W., Accinelli, G. G., Hartwig, B., Kiefer, C., Baker, D., Severing, E. I., Willing, E., Piednoël, M., Woetzel, S., Madrid, E., et al. (2017) · Genome Research · doi:10.1101/gr.213652.116 · Cited by 140 · see citing works

INC-Seq: accurate single molecule reads using nanopore sequencing

Li, C., Chng, K. R., Boey, E. J. H., Ng, A. H. Q., Wilm, A., & Nagarajan, N. (2016) · GigaScience · doi:10.1186/s13742-016-0140-7 · Cited by 137 · see citing works

SARS-CoV-2 growth, furin-cleavage-site adaptation and neutralization using serum from acutely infected hospitalized COVID-19 patients

Klimstra, W. B., Tilston-Lunel, N. L., Nambulli, S., Boslett, J., McMillen, C. M., Gilliland, T., Dunn, M. D., Sun, C., Wheeler, S. E., Wells, A., et al. (2020) · Journal of General Virology · doi:10.1099/jgv.0.001481 · Cited by 137 · see citing works

Detection of RNA modifications

Kellner, S. M., Burhenne, J., & Helm, M. (2010) · RNA Biology · doi:10.4161/rna.7.2.11468 · Cited by 134 · see citing works

Using long-read sequencing to detect imprinted DNA methylation

Gigante, S., Gouil, Q. A., Lucattini, A., Keniry, A., Beck, T. J., Tinning, M., Gordon, L., Woodruff, C., Speed, T. P., Blewitt, M. E., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz107 · Cited by 133 · see citing works

Going beyond five bases in DNA sequencing

Korlach, J., & Turner, S. W. (2012) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2012.04.002 · Cited by 125 · see citing works

Next-generation sequencing technologies for detection of modified nucleotides in RNAs

Schwartz, S., & Motorin, Y. (2016) · RNA Biology · doi:10.1080/15476286.2016.1251543 · Cited by 125 · see citing works

Increasing the accuracy of nanopore DNA sequencing using a time-varying cross membrane voltage

Noakes, M. T., Brinkerhoff, H. D., Laszlo, A. H., Derrington, I. M., Langford, K. W., Mount, J. W., Bowman, J. L., Baker, K. S., Doering, K. M., Tickman, B. I., et al. (2019) · Nature Biotechnology · doi:10.1038/s41587-019-0096-0 · Cited by 123 · see citing works

Beyond sequencing: optical mapping of DNA in the age of nanotechnology and nanoscopy

Levy‐Sakin, M., & Ebenstein, Y. (2013) · Current Opinion in Biotechnology · doi:10.1016/j.copbio.2013.01.009 · Cited by 118 · see citing works

Tools and pipelines for BioNano data: molecule assembly pipeline and FASTA super scaffolding tool

Shelton, J. M., Coleman, M. C., Herndon, N., Lu, N., Lam, E. T., Anantharaman, T., Sheth, P., & Brown, S. J. (2015) · BMC Genomics · doi:10.1186/s12864-015-1911-8 · Cited by 118 · see citing works

Rapid de novo assembly of the European eel genome from nanopore sequencing reads

Jansen, H. J., Liem, M. K., Jong-Raadsen, S. A., Dufour, S., Weltzien, F., Swinkels, W., Koelewijn, A., Palstra, A. P., Pelster, B., Spaink, H. P., et al. (2017) · Scientific Reports · doi:10.1038/s41598-017-07650-6 · Cited by 118 · see citing works

ntEdit: scalable genome sequence polishing

Warren, R. L., Coombe, L., Mohamadi, H., Zhang, J., Jaquish, B. C., Isabel, N., Jones, S. J. M., Bousquet, J., Bohlmann, J., & Birol, İ. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz400 · Cited by 116 · see citing works

Tools and Strategies for Long-Read Sequencing and De Novo Assembly of Plant Genomes

Jung, H., Winefield, C. S., Bombarely, A., Prentis, P. J., & Waterhouse, P. M. (2019) · Trends in Plant Science · doi:10.1016/j.tplants.2019.05.003 · Cited by 115 · see citing works

A new era of long-read sequencing for cancer genomics

Sakamoto, Y., Sereewattanawoot, S., & Suzuki, A. (2019) · Journal of Human Genetics · doi:10.1038/s10038-019-0658-5 · Cited by 115 · see citing works

Transcriptome profiling of mouse samples using nanopore sequencing of cDNA and RNA molecules

Sessegolo, C., Cruaud, C., Silva, C. D., Cologne, A., Dubarry, M., Derrien, T., Lacroix, V., & Aury, J. (2019) · Scientific Reports · doi:10.1038/s41598-019-51470-9 · Cited by 108 · see citing works

Single molecule-level detection and long read-based phasing of epigenetic variations in bacterial methylomes

Beaulaurier, J., Zhang, X., Zhu, S., Sebra, R., Rosenbluh, C., Deikus, G. Y., Shen, N., Munera, D., Waldor, M. K., Chess, A. J., et al. (2015) · Nature Communications · doi:10.1038/ncomms8438 · Cited by 102 · see citing works

Long-read sequencing for rare human genetic diseases

Mitsuhashi, S., & Matsumoto, N. (2019) · Journal of Human Genetics · doi:10.1038/s10038-019-0671-8 · Cited by 100 · see citing works

Precision methylome characterization ofMycobacterium tuberculosiscomplex (MTBC) using PacBio single-molecule real-time (SMRT) technology

Zhu, L., Zhong, J., Jia, X., Liu, G., Kang, Y., Dong, M., Zhang, X., Li, Q., Yue, L., Li, C., et al. (2015) · Nucleic Acids Research · doi:10.1093/nar/gkv1498 · Cited by 99 · see citing works

Combination of short-read, long-read, and optical mapping assemblies reveals large-scale tandem repeat arrays with population genetic implicationsPreprint

Weissensteiner, M. H., Pang, A. W. C., Bunikis, I., Höijer, I., Pettersson, O. V., Suh, A., & Wolf, J. B. W. (2017) · Genome Research · doi:10.1101/gr.215095.116 · Cited by 99 · see citing works

Synthetic long-read sequencing reveals intraspecies diversity in the human microbiome

Kuleshov, V., Jiang, C., Zhou, W., Jahanbani, F., Batzoglou, S., & Snyder, M. P. (2015) · Nature Biotechnology · doi:10.1038/nbt.3416 · Cited by 98 · see citing works

Human Genome Assembly in 100 MinutesPreprint

Chin, C.-S., & Khalak, A. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/705616 · Cited by 97 · see citing works

DRIMSeq: a Dirichlet-multinomial framework for multivariate count outcomes in genomics

Nowicka, M., & Robinson, M. D. (2016) · F1000Research · doi:10.12688/f1000research.8900.1 · Cited by 95 · see citing works

Introduction to Isoform Sequencing Using Pacific Biosciences Technology (Iso-Seq)

Gonzalez‐Garay, M. L. (2015) · Translational bioinformatics · doi:10.1007/978-94-017-7450-5_6 · Cited by 94 · see citing works

A comparative evaluation of hybrid error correction methods for error-prone long reads

Fu, S.-H., Wang, A., & Au, K. (2019) · Genome Biology · doi:10.1186/s13059-018-1605-z · Cited by 94 · see citing works

Improvements in Genomic Technologies: Application to Crop Genomics

Yuan, Y., Bayer, P. E., Batley, J., & Edwards, D. (2017) · Trends in biotechnology · doi:10.1016/j.tibtech.2017.02.009 · Cited by 91 · see citing works

The Origins, Evolution, and Functional Potential of Alternative Splicing in Vertebrates

Mudge, J. M., Frankish, A., Fernandez-Banet, J., Alioto, T., Derrien, T., Howald, C., Reymond, A., Guigó, R., Hubbard, T., & Harrow, J. (2011) · Molecular Biology and Evolution · doi:10.1093/molbev/msr127 · Cited by 82 · see citing works

NanoMod: a computational tool to detect DNA modifications using Nanopore long-read sequencing data

Liu, Q., Georgieva, D., Egli, D. M., & Wang, K. (2019) · BMC Genomics · doi:10.1186/s12864-018-5372-8 · Cited by 77 · see citing works

Single-cell mRNA isoform diversity in the mouse brain

Karlsson, K., & Linnarsson, S. (2017) · BMC Genomics · doi:10.1186/s12864-017-3528-6 · Cited by 76 · see citing works

Comparison of the MGISEQ-2000 and Illumina HiSeq 4000 sequencing platforms for RNA sequencing

Jeon, S. A., Park, J., Kim, J.-H., Kim, J., Kim, S., Kim, J. C., & Kim, S. (2019) · Genomics & Informatics · doi:10.5808/gi.2019.17.3.e32 · Cited by 73 · see citing works

Detecting DNA Modifications from SMRT Sequencing Data by Modeling Sequence Context Dependence of Polymerase Kinetic

Feng, Z., Fang, G., Korlach, J., Clark, T. A., Luong, K., Zhang, X., Wong, W. H., & Schadt, E. E. (2013) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002935 · Cited by 71 · see citing works

Illumina Synthetic Long Read Sequencing Allows Recovery of Missing Sequences even in the “Finished” C. elegans Genome

Li, R., Hsieh, C.-L., Young, A. G., Zhang, Z., Ren, X., & Zhao, Z. (2015) · Scientific Reports · doi:10.1038/srep10814 · Cited by 69 · see citing works

The long reads ahead: de novo genome assembly using the MinION

de Lannoy, C. V., de Ridder, D., & Risse, J. E. (2017) · F1000Research · doi:10.12688/f1000research.12012.2 · Cited by 69 · see citing works

Whale watching with BulkVis: A graphical viewer for Oxford Nanopore bulk fast5 filesPreprint

Payne, A., Holmes, N., Rakyan, V. K., et al. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/312256 · Cited by 67 · see citing works

De novo assembly of a haplotype-resolved human genome

Cao, H., Wu, H., Luo, R., Huang, S., Sun, Y., Tong, X., Xie, Y., Liu, B., Yang, H., Zheng, H., et al. (2015) · Nature Biotechnology · doi:10.1038/nbt.3200 · Cited by 65 · see citing works

Hybrid assembly with long and short reads improves discovery of gene family expansions

Miller, J. R., Zhou, P., Mudge, J., Gurtowski, J., Lee, H., Ramaraj, T., Walenz, B. P., Liu, J., Stupar, R. M., Denny, R. L., et al. (2017) · BMC Genomics · doi:10.1186/s12864-017-3927-8 · Cited by 65 · see citing works

A robust benchmark for germline structural variant detectionPreprint

Zook, J. M., Hansen, N. F., Olson, N. D., Chapman, L. M., Mullikin, J. C., Xiao, C., Sherry, S. T., Koren, S., Phillippy, A. M., Boutros, P. C., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/664623 · Cited by 62 · see citing works

High-Fidelity Nanopore Sequencing of Ultra-Short DNA Targets

Wilson, B. D., Eisenstein, M. S., & Soh, H. T. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b00856 · Cited by 56 · see citing works

Applying next-generation sequencing to unravel the mutational landscape in viral quasispecies

Lu, I., Muller, C. P., & HeFeng, F. Q. (2020) · Virus Research · doi:10.1016/j.virusres.2020.197963 · Cited by 56 · see citing works

Comparative assessment of long-read error correction software applied to Nanopore RNA-sequencing data

Lima, L., Marchet, C., Caboche, S., Silva, C. D., Istace, B., Aury, J., Touzet, H., & Chikhi, R. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbz058 · Cited by 55 · see citing works

Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencing

Senabouth, A., Andersen, S. B., Shi, Q., Shi, L., Jiang, F., Zhang, W., Wing, K., Daniszewski, M., Lukowski, S. W., Hung, S. S. C., et al. (2020) · NAR Genomics and Bioinformatics · doi:10.1093/nargab/lqaa034 · Cited by 55 · see citing works

Mycobacterium bovis: From Genotyping to Genome Sequencing

Guimarães, A. M. S., & Zimpel, C. K. (2020) · Microorganisms · doi:10.3390/microorganisms8050667 · Cited by 52 · see citing works

Deciphering highly similar multigene family transcripts from Iso-Seq data with IsoCon

Sahlin, K., Tomaszkiewicz, M., Makova, K., & Medvedev, P. (2018) · Nature Communications · doi:10.1038/s41467-018-06910-x · Cited by 51 · see citing works

Efficiency of PacBio long read correction by 2nd generation Illumina sequencing

Mahmoud, M., Żywicki, M., Twardowski, T., & Karlowski, W. M. (2017) · Genomics · doi:10.1016/j.ygeno.2017.12.011 · Cited by 49 · see citing works

Yet another de novo genome assembler

Vaser, R., & Šikić, M. (2019) · International symposium on image and signal processing and analysis/ISPA ... · doi:10.1109/ispa.2019.8868909 · Cited by 49 · see citing works

Antibodies specific for nucleic acid modifications

Feederle, R., & Schepers, A. (2017) · RNA Biology · doi:10.1080/15476286.2017.1295905 · Cited by 39 · see citing works

Isoform Evolution in Primates through Independent Combination of Alternative RNA Processing Events

Zhang, S., Wang, C., Yan, S., Fu, A., Luan, X., Li, Y., Shen, Q. S., Zhong, X., Chen, J., Wang, X., et al. (2017) · Molecular Biology and Evolution · doi:10.1093/molbev/msx212 · Cited by 39 · see citing works

Long-read sequencing reveals the complex splicing profile of the psychiatric risk gene CACNA1C in human brainPreprint

Clark, M. B., Wrzesinski, T., Garcia, A. B., Hall, N. A. L., Kleinman, J. E., Hyde, T., Weinberger, D. R., Harrison, P. J., Haerty, W., & Tunbridge, E. M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/260562 · Cited by 37 · see citing works

A sequencer coming of age: De novo genome assembly using MinION reads

de Lannoy, C. V., de Ridder, D., & Risse, J. E. (2017) · F1000Research · doi:10.12688/f1000research.12012.1 · Cited by 37 · see citing works

Nanopore sequencing and Hi-C scaffolding provide insight into the evolutionary dynamics of transposable elements and piRNA production in wild strains of Drosophila melanogaster

Ellison, C. E., & Cao, W. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1080 · Cited by 36 · see citing works

Haplotype-Phased Synthetic Long Reads from Short-Read Sequencing

Stapleton, J. A., Kim, J., Hamilton, J. P., Wu, M., Irber, L. C., Maddamsetti, R., Briney, B. S., Newton, L. A., Burton, D. R., Brown, C. T., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0147229 · Cited by 35 · see citing works

Ion Mobility-Mass Spectrometry Reveals That α-Hemolysin from Staphylococcus aureus Simultaneously Forms Hexameric and Heptameric Complexes in Detergent Micelle Solutions

Wilson, J., Rolland, A. D., Klausen, G. M., & Prell, J. S. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.9b02243 · Cited by 31 · see citing works

Hybrid assembly of ultra-long Nanopore reads augmented with 10x-Genomics contigs: Demonstrated with a human genome

Ma, Z. S., Li, L., Ye, C., Peng, M., & Zhang, Y. (2018) · Genomics · doi:10.1016/j.ygeno.2018.12.013 · Cited by 29 · see citing works

Next regeneration sequencing for reference genomes

Burgess, D. J. (2018) · Nature Reviews Genetics · doi:10.1038/nrg.2018.5 · Cited by 28 · see citing works

The importance of identifying alternative splicing in vertebrate genome annotation

Frankish, A., Mudge, J. M., Thomas, M., & Harrow, J. (2012) · Database · doi:10.1093/database/bas014 · Cited by 26 · see citing works

Yet another de novo genome assemblerPreprint

Vaser, R., & Šikić, M. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/656306 · Cited by 24 · see citing works

New technologies boost genome quality

Pennisi, E. (2017) · Science · doi:10.1126/science.357.6346.10 · Cited by 16 · see citing works

Mapping DNA replication with nanopore sequencingPreprint

Hennion, M., Arbona, J., Cruaud, C., Proux, F., Tallec, B. L., Novikova, E., Engelen, S., Lemainque, A., Audit, B., & Hyrien, O. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/426858 · Cited by 16 · see citing works

Visualization tools for human structural variations identified by whole-genome sequencing

Yokoyama, T., & Kasahara, M. (2019) · Journal of Human Genetics · doi:10.1038/s10038-019-0687-0 · Cited by 14 · see citing works

Comparative performance of the BGI and Illumina sequencing technology for single-cell RNA-sequencingPreprint

Senabouth, A., Andersen, S. B., Shi, Q., Shi, L., Liu, P., Jiang, F., Zhang, W., Wing, K., Daniszewski, M., Lukowski, S. W., et al. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/552588 · Cited by 11 · see citing works

Using dried blood spot samples from a trio for linked-read whole-exome sequencing

Mortensen, Ó., Lydersen, L. N., Apol, K. D., Andorsdóttir, G., Steig, B. Á., & Gregersen, N. O. (2019) · European Journal of Human Genetics · doi:10.1038/s41431-019-0343-3 · Cited by 10 · see citing works

Computational haplotype recovery and long-read validation identifies novel isoforms of industrially relevant enzymes from natural microbial communitiesPreprint

Nicholls, S. M., Aubrey, W., Edwards, A., Grave, K. D., Huws, S., Schietgat, L., Soares, A., Creevey, C. J., & Clare, A. J. (2018) · Research Portal (Queen's University Belfast) · doi:10.1101/223404 · Cited by 7 · see citing works

YaHS: yet another Hi-C scaffolding tool

Zhou, C., McCarthy, S. A., & Durbin, R. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btac808 · Cited by 2,440 · see citing works

Nanopore sequencing technology, bioinformatics and applications

Wang, Y., Zhao, Y., Bollas, A. E., Wang, Y., & Au, K. F. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-01108-x · Cited by 1,756 · see citing works

Next-Generation Sequencing Technology: Current Trends and Advancements

Satam, H., Joshi, K., Mangrolia, U., Waghoo, S., Zaidi, G., Rawool, S., Thakare, R. P., Banday, S., Mishra, A. K., Das, G., et al. (2023) · Biology · doi:10.3390/biology12070997 · Cited by 1,299 · see citing works

The Tabula Sapiens: A multiple-organ, single-cell transcriptomic atlas of humans

The Tabula Sapiens Consortium*, Jones, R. C., Karkanias, J., Krasnow, M. A., Pisco, A. O., Quake, S. R., Salzman, J., Yosef, N., Bulthaup, B., Brown, P., et al. (2022) · Science · doi:10.1126/science.abl4896 · Cited by 1,056 · see citing works

hdWGCNA identifies co-expression networks in high-dimensional transcriptomics data

Morabito, S., Reese, F., Rahimzadeh, N., Miyoshi, E., & Swarup, V. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2023.100498 · Cited by 773 · see citing works

Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues

Pham, D., Tan, X., Balderson, B., Xu, J., Grice, L. F., Yoon, S., Willis, E. F., Tran, M., Lam, P. Y., Raghubar, A. M., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-43120-6 · Cited by 716 · see citing works

Statistics or biology: the zero-inflation controversy about scRNA-seq data

Jiang, R., Sun, T., Song, D., & Li, J. J. (2022) · Genome Biology · doi:10.1186/s13059-022-02601-5 · Cited by 614 · see citing works

scBERT as a Large-scale Pretrained Deep Language Model for Cell Type Annotation of Single-cell RNA-seq Data

Yang, F., Wang, W., Wang, F., Fang, Y., Tang, D., Huang, J., Lu, H., & Yao, J. (2021) · doi:10.1101/2021.12.05.471261 · Cited by 617 · see citing works

Joint probabilistic modeling of single-cell multi-omic data with totalVI

Gayoso, A., Steier, Z., Lopez, R., Regier, J., Nazor, K. L., Streets, A., & Yosef, N. (2021) · Nature Methods · doi:10.1038/s41592-020-01050-x · Cited by 592 · see citing works

Improved transcriptome assembly using a hybrid of long and short reads with StringTie

Shumate, A., Wong, B. Y., Pertea, G. M., & Pertea, M. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009730 · Cited by 473 · see citing works

Rapid and sensitive detection of genome contamination at scale with FCS-GX

Astashyn, A., Tvedte, E. S., Sweeney, D., Sapojnikov, V., Bouk, N., Joukov, V., Mozes, E., Strope, P. K., Sylla, P. M., Wagner, L., et al. (2024) · Genome biology · doi:10.1186/s13059-024-03198-7 · Cited by 480 · see citing works

Examining horizontal gene transfer in microbial communities

Brito, I. (2021) · Nature Reviews Microbiology · doi:10.1038/s41579-021-00534-7 · Cited by 447 · see citing works

Signatures of plasticity, metastasis, and immunosuppression in an atlas of human small cell lung cancer

Chan, J. M., Quintanal-Villalonga, À., Gao, V. R., Xie, Y., Allaj, V., Chaudhary, O., Masilionis, I., Egger, J. V., Chow, A. T., Walle, T., et al. (2021) · Cancer Cell · doi:10.1016/j.ccell.2021.09.008 · Cited by 440 · see citing works

Pangenome graph construction from genome alignments with Minigraph-Cactus

Hickey, G., Monlong, J., Ebler, J., Novak, A. M., Eizenga, J. M., Gao, Y., Human Pangenome Reference Consortium, Abel, H. J., Antonacci-Fulton, L. L., Asri, M., et al. (2024) · Nature Biotechnology · doi:10.1038/s41587-023-01793-w · Cited by 343 · see citing works

Machine learning in plant science and plant breeding

van Dijk, A. D. J., Kootstra, G., Kruijer, W., & de Ridder, D. (2020) · iScience · doi:10.1016/j.isci.2020.101890 · Cited by 324 · see citing works

plotsr: visualizing structural similarities and rearrangements between multiple genomes

Goel, M., & Schneeberger, K. (2022) · Bioinformatics · doi:10.1093/bioinformatics/btac196 · Cited by 319 · see citing works

Transcriptome variation in human tissues revealed by long-read sequencing

Glinos, D. A., Garborcauskas, G., Hoffman, P. J., Ehsan, N., Jiang, L., Gokden, A., Dai, X.-G., Aguet, F., Brown, K. L., Garimella, K., et al. (2021) · Nature · doi:10.1038/s41586-022-05035-y · Cited by 278 · see citing works

Epigenetic patterns in a complete human genome

Gershman, A., Sauria, M. E. G., Guitart, X., Vollger, M. R., Hook, P. W., Hoyt, S. J., Jain, M., Shumate, A., Razaghi, R., Koren, S., et al. (2022) · Science · doi:10.1126/science.abj5089 · Cited by 297 · see citing works

DestVI identifies continuums of cell types in spatial transcriptomics data

Lopez, R., Li, B., Keren-Shaul, H., Boyeau, P., Kedmi, M., Pilzer, D., Jelinski, A., Yofe, I., David, E., Wagner, A., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-022-01272-8 · Cited by 276 · see citing works

Identifying biases and their potential solutions in human microbiome studies

Nearing, J. T., Comeau, A. M., & Langille, M. G. I. (2021) · Microbiome · doi:10.1186/s40168-021-01059-0 · Cited by 240 · see citing works

rMATS-turbo: an efficient and flexible computational tool for alternative splicing analysis of large-scale RNA-seq data

Wang, Y., Xie, Z., Kutschera, E., Adams, J. I., Kadash-Edmondson, K. E., & Xing, Y. (2024) · Nature Protocols · doi:10.1038/s41596-023-00944-2 · Cited by 277 · see citing works

Diversity and ecology of protists revealed by metabarcoding

Burki, F., Sandín, M. M., & Jamy, M. (2021) · Current Biology · doi:10.1016/j.cub.2021.07.066 · Cited by 247 · see citing works

Curated variation benchmarks for challenging medically relevant autosomal genes

Wagner, J., Olson, N. D., Harris, L., McDaniel, J., Cheng, H., Fungtammasan, A., Hwang, Y.-C., Gupta, R., Wenger, A. M., Rowell, W. J., et al. (2022) · Nature Biotechnology · doi:10.1038/s41587-021-01158-1 · Cited by 241 · see citing works

DNA methylation-calling tools for Oxford Nanopore sequencing: a survey and human epigenome-wide evaluation

Liu, Y., Rosikiewicz, W., Pan, Z., Jillette, N., Wang, P., Taghbalout, A., Foox, J., Mason, C. E., Carroll, M. P., Cheng, A. W., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02510-z · Cited by 242 · see citing works

Semi-automated assembly of high-quality diploid human reference genomes

Jarvis, E. D., Formenti, G., Rhie, A., Guarracino, A., Yang, C., Wood, J., Tracey, A., Thibaud-Nissen, F., Vollger, M. R., Porubsky, D., et al. (2022) · Nature · doi:10.1038/s41586-022-05325-5 · Cited by 209 · see citing works

BiG-SLiCE: A highly scalable tool maps the diversity of 1.2 million biosynthetic gene clusters

Kautsar, S. A., van der Hooft, J. J. J., de Ridder, D., & Medema, M. H. (2021) · GigaScience · doi:10.1093/gigascience/giaa154 · Cited by 224 · see citing works

Third-Generation Sequencing: The Spearhead towards the Radical Transformation of Modern Genomics

Athanasopoulou, K., Boti, M. A., Adamopoulos, P. G., Skourou, P. C., & Scorilas, A. (2021) · Life · doi:10.3390/life12010030 · Cited by 234 · see citing works

A review of computational tools for generating metagenome-assembled genomes from metagenomic sequencing data

Yang, C., Chowdhury, D., Zhang, Z., Cheung, W. K., Lü, A., Bian, Z., & Zhang, L. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.11.028 · Cited by 226 · see citing works

Multi-omics data integration considerations and study design for biological systems and disease

Graw, S., Chappell, K., Washam, C. L., Gies, A. J., Bird, J. T., Robeson, M. S., & Byrum, S. D. (2020) · Molecular Omics · doi:10.1039/d0mo00041h · Cited by 223 · see citing works

Comprehensive characterization of single-cell full-length isoforms in human and mouse with long-read sequencing

Tian, L., Jabbari, J. S., Thijssen, R., Gouil, Q. A., Amarasinghe, S. L., Voogd, O., Kariyawasam, H., Du, M. R. M., Schuster, J., Wang, C., et al. (2021) · Genome biology · doi:10.1186/s13059-021-02525-6 · Cited by 207 · see citing works

Chromosome-scale and haplotype-resolved genome assembly of a tetraploid potato cultivar

Sun, H., Jiao, W., Krause, K., Campoy, J. A., Goel, M., Folz‐Donahue, K., Kukat, C., Hüettel, B., & Schneeberger, K. (2022) · Nature Genetics · doi:10.1038/s41588-022-01015-0 · Cited by 213 · see citing works

Current and emerging trends in techniques for plant pathogen detection

Venbrux, M., Crauwels, S., & Rediers, H. (2023) · Frontiers in Plant Science · doi:10.3389/fpls.2023.1120968 · Cited by 211 · see citing works

Next generation sequencing of SARS-CoV-2 genomes: challenges, applications and opportunities

Chiara, M., D’Erchia, A. M., Gissi, C., Manzari, C., Parisi, A., Resta, N., Zambelli, F., Picardi, E., Pavesi, G., Horner, D. S., et al. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa297 · Cited by 202 · see citing works

Perspectives and Benefits of High-Throughput Long-Read Sequencing in Microbial Ecology

Tedersoo, L., Albertsen, M., Anslan, S., & Callahan, B. J. (2021) · Applied and Environmental Microbiology · doi:10.1128/aem.00626-21 · Cited by 203 · see citing works

Microbiome diversity and dysbiosis in aquaculture

Villamil, S. I., Huerlimann, R., & Jerry, D. R. (2020) · Reviews in Aquaculture · doi:10.1111/raq.12513 · Cited by 204 · see citing works

Chromatin accessibility profiling methods

Minnoye, L., Marinov, G. K., Krausgruber, T., Pan, L., Marand, A. P., Secchia, S., Greenleaf, W. J., Furlong, E. E. M., Zhao, K., Schmitz, R. J., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00008-9 · Cited by 206 · see citing works

Mini review: Genome mining approaches for the identification of secondary metabolite biosynthetic gene clusters in Streptomyces

Lee, N., Hwang, S., Kim, J., Cho, S., Palsson, B. Ø., & Cho, B. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.06.024 · Cited by 196 · see citing works

Nanopore sequencing and its application to the study of microbial communities

Ciuffreda, L., Rodríguez-Pérez, H., & Flores, C. (2021) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2021.02.020 · Cited by 169 · see citing works

Benchmarking of Nanopore R10.4 and R9.4.1 flow cells in single-cell whole-genome amplification and whole-genome shotgun sequencing

Ni, Y., Liu, X., Simeneh, Z. M., Yang, M., & Li, R. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.03.038 · Cited by 196 · see citing works

A deep siamese neural network improves metagenome-assembled genomes in microbiome datasets across different environments

Pan, S., Zhu, C., Zhao, X., & Coelho, L. P. (2022) · Nature Communications · doi:10.1038/s41467-022-29843-y · Cited by 195 · see citing works

Discovering multiple types of DNA methylation from bacteria and microbiome using nanopore sequencing

Tourancheau, A., Mead, E. A., Zhang, X., & Fang, G. (2021) · Nature Methods · doi:10.1038/s41592-021-01109-3 · Cited by 192 · see citing works

The application of long-read sequencing in clinical settings

Oehler, J. B., Wright, H., Stark, Z., Mallett, A. J., & Schmitz, U. (2023) · Human Genomics · doi:10.1186/s40246-023-00522-3 · Cited by 189 · see citing works

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Gaudêncio, S. P., Bayram, E., Bilela, L. L., Cueto, M., Díaz‐Marrero, A. R., HAZNEDAROĞLU, B. Z., Jiménez, C., Mandalakis, M., Pereira, F., Reyes, F., et al. (2023) · Marine Drugs · doi:10.3390/md21050308 · Cited by 204 · see citing works

Illuminating the dark side of the human transcriptome with long read transcript sequencing

Kuo, R. I., Cheng, Y., Zhang, R., Brown, J. W. S., Smith, J., Archibald, A. L., & Burt, D. W. (2020) · BMC Genomics · doi:10.1186/s12864-020-07123-7 · Cited by 168 · see citing works

Detection of aberrant splicing events in RNA-seq data using FRASER

Mertes, C., Scheller, I. F., Yépez, V. A., Çelik, M. H., Liang, Y., Kremer, L. S., Gušić, M., Prokisch, H., & Gagneur, J. (2021) · Nature Communications · doi:10.1038/s41467-020-20573-7 · Cited by 180 · see citing works

Full-length transcript sequencing of human and mouse cerebral cortex identifies widespread isoform diversity and alternative splicing

Leung, S. K., Jeffries, A. R., Castanho, I., Jordan, B. T., Moore, K., Davies, J. P., Dempster, E. L., Bray, N. J., O’Neill, P., Tseng, E., et al. (2021) · Cell Reports · doi:10.1016/j.celrep.2021.110022 · Cited by 168 · see citing works

A simple guide to de novo transcriptome assembly and annotation

Raghavan, V., Kraft, L., Mesny, F., & Rigerte, L. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbab563 · Cited by 175 · see citing works

Single-cell RNA sequencing reveals SARS-CoV-2 infection dynamics in lungs of African green monkeys

Speranza, E. E., Williamson, B. N., Feldmann, F., Sturdevant, G. L., Pérez-Pérez, L., Meade-White, K. D., Smith, B. J., Lovaglio, J., Martens, C., Munster, V. J., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abe8146 · Cited by 160 · see citing works

Features and applications of haplotypes in crop breeding

Bhat, J. A., Yu, D., Bohra, A., Ganie, S. A., & Varshney, R. K. (2021) · Communications Biology · doi:10.1038/s42003-021-02782-y · Cited by 182 · see citing works

The giant diploid faba genome unlocks variation in a global protein crop

Jayakodi, M., Golicz, A. A., Kreplak, J., Fechete, L. I., Angra, D., Bednář, P., Bornhofen, E., Zhang, H., Boussageon, R., Kaur, S., et al. (2023) · Nature · doi:10.1038/s41586-023-05791-5 · Cited by 166 · see citing works

Marine mammal conservation: over the horizon

Nelms, S. E., Alfaro‐Shigueto, J., Arnould, J., Ávila, I. C., Nash, S. B., Campbell, E., Carter, M., Collins, T., Currey, R. J. C., Domit, C., et al. (2021) · Endangered Species Research · doi:10.3354/esr01115 · Cited by 170 · see citing works

Toward a genome sequence for every animal: Where are we now?

Hotaling, S., Kelley, J. L., & Frandsen, P. B. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2109019118 · Cited by 167 · see citing works

Cobolt: integrative analysis of multimodal single-cell sequencing data

Gong, B., Zhou, Y., & Purdom, E. (2021) · Genome Biology · doi:10.1186/s13059-021-02556-z · Cited by 168 · see citing works

Long-Read DNA Sequencing: Recent Advances and Remaining Challenges

Warburton, P. E., & Sebra, R. P. (2023) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev-genom-101722-103045 · Cited by 163 · see citing works

Plant pan-genomics and its applications

Shi, J., Tian, Z., Lai, J., & Huang, X. (2022) · Molecular Plant · doi:10.1016/j.molp.2022.12.009 · Cited by 163 · see citing works

isoCirc catalogs full-length circular RNA isoforms in human transcriptomes

Xin, R., Gao, Y. P., Gao, Y., Wang, R., Kadash-Edmondson, K. E., Liu, B., Wang, Y., Lin, L., & Xing, Y. (2021) · Nature Communications · doi:10.1038/s41467-020-20459-8 · Cited by 159 · see citing works

Integrating spatial transcriptomics data across different conditions, technologies and developmental stages

Zhou, X., Dong, K., & Zhang, S. (2023) · Nature Computational Science · doi:10.1038/s43588-023-00528-w · Cited by 160 · see citing works

Determining Hosts of Antibiotic Resistance Genes: A Review of Methodological Advances

Rice, E. W., Wang, P., Smith, A. L., & Stadler, L. B. (2020) · Environmental Science & Technology Letters · doi:10.1021/acs.estlett.0c00202 · Cited by 158 · see citing works

The role of alternative splicing in adaptation and evolution

Verta, J., & Jacobs, A. (2021) · Trends in Ecology & Evolution · doi:10.1016/j.tree.2021.11.010 · Cited by 148 · see citing works

Complete sequencing of ape genomes

Yoo, D., Rhie, A., Hebbar, P., Antonacci, F., Logsdon, G. A., Solar, S. J., Antipov, D., Pickett, B. D., Safonova, Y., Montinaro, F., et al. (2025) · Nature · doi:10.1038/s41586-025-08816-3 · Cited by 157 · see citing works

Comparison of Transformations for Single-Cell RNA-Seq Data

Ahlmann-Eltze, C., & Huber, W. (2021) · doi:10.1101/2021.06.24.449781 · Cited by 148 · see citing works

pipeComp, a general framework for the evaluation of computational pipelines, reveals performant single cell RNA-seq preprocessing tools

Germain, P., Sonrel, A., & Robinson, M. D. (2020) · Genome biology · doi:10.1186/s13059-020-02136-7 · Cited by 139 · see citing works

RNA-seq data science: From raw data to effective interpretation

Deshpande, D., Chhugani, K., Chang, Y., Karlsberg, A., Loeffler, C., Zhang, J., Muszyńska, A., Munteanu, V., Yang, H. T., Rotman, J., et al. (2023) · Frontiers in Genetics · doi:10.3389/fgene.2023.997383 · Cited by 147 · see citing works

In vivo hypermutation and continuous evolution

Molina, R. S., Rix, G., Mengiste, A. A., Álvarez, B., Seo, D., Chen, H., Hurtado, J. E., Zhang, Q., García-García, J. D., Heins, Z., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-022-00119-5 · Cited by 144 · see citing works

PBSIM2: a simulator for long-read sequencers with a novel generative model of quality scores

Ono, Y., Asai, K., & Hamada, M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa835 · Cited by 140 · see citing works

Evolutionary and functional genomics of DNA methylation in maize domestication and improvement

Xu, G., Lyu, J., Li, Q., Liu, H., Wang, D.-F., Zhang, M., Springer, N., Ross-Ibarra, J., & Yang, J.-L. (2020) · Nature Communications · doi:10.1038/s41467-020-19333-4 · Cited by 109 · see citing works

EnvRtype : a software to interplay enviromics and quantitative genomics in agriculture

Costa‐Neto, G., Galli, G., Carvalho, H. F., Crossa, J. L., & Fritsche‐Neto, R. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab040 · Cited by 138 · see citing works

SARS-CoV-2 growth, furin-cleavage-site adaptation and neutralization using serum from acutely infected hospitalized COVID-19 patients

Klimstra, W. B., Tilston-Lunel, N. L., Nambulli, S., Boslett, J., McMillen, C. M., Gilliland, T., Dunn, M. D., Sun, C., Wheeler, S. E., Wells, A., et al. (2020) · Journal of General Virology · doi:10.1099/jgv.0.001481 · Cited by 137 · see citing works

Metatranscriptomics for the Human Microbiome and Microbial Community Functional Profiling

Zhang, Y., Thompson, K. N., Branck, T. A., Yan, Y., Nguyen, L. H., Franzosa, E. A., & Huttenhower, C. (2021) · Annual Review of Biomedical Data Science · doi:10.1146/annurev-biodatasci-031121-103035 · Cited by 137 · see citing works

Genetic testing and counseling for the unexplained epilepsies: An evidence‐based practice guideline of the National Society of Genetic Counselors

Smith, L. A., Malinowski, J. R., Ceulemans, S., Peck, K., Walton, N., Sheidley, B. R., & Lippa, N. C. (2022) · Journal of Genetic Counseling · doi:10.1002/jgc4.1646 · Cited by 133 · see citing works

Integrating multi-omics data for crop improvement

Scossa, F., Alseekh, S., & Fernie, A. R. (2020) · Journal of Plant Physiology · doi:10.1016/j.jplph.2020.153352 · Cited by 132 · see citing works

An Introduction to Nanopore Sequencing: Past, Present, and Future Considerations

Mackenzie, M. E., & Argyropoulos, C. (2023) · Micromachines · doi:10.3390/mi14020459 · Cited by 133 · see citing works

A survey of k-mer methods and applications in bioinformatics

Moeckel, C., Mareboina, M., Konnaris, M. A., Chan, C. S. Y., Mouratidis, I., Montgomery, A., Chantzi, N., Pavlopoulos, G. A., & Georgakopoulos-Soares, I. (2024) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2024.05.025 · Cited by 131 · see citing works

Unraveling metagenomics through long-read sequencing: a comprehensive review

Kim, C., Pongpanich, M., & Porntaveetus, T. (2024) · Journal of Translational Medicine · doi:10.1186/s12967-024-04917-1 · Cited by 129 · see citing works

Integrated multi-omics analyses of microbial communities: a review of the current state and future directions

Arıkan, M., & Muth, T. (2023) · Molecular Omics · doi:10.1039/d3mo00089c · Cited by 128 · see citing works

Advances in optical mapping for genomic research

Yuan, Y., Chung, C., & Chan, T. (2020) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2020.07.018 · Cited by 125 · see citing works

Population-level integration of single-cell datasets enables multi-scale analysis across samples

Donno, C. D., Hediyeh-zadeh, S., Moinfar, A. A., Wagenstetter, M., Zappia, L., Lotfollahi, M., & Theis, F. J. (2023) · Nature Methods · doi:10.1038/s41592-023-02035-2 · Cited by 125 · see citing works

Multi-omic integration of microbiome data for identifying disease-associated modules

Muller, E., Shiryan, I., & Borenstein, E. (2024) · Nature Communications · doi:10.1038/s41467-024-46888-3 · Cited by 132 · see citing works

Computational analysis of cancer genome sequencing data

Cortés‐Ciriano, I., Gulhan, D., Lee, J. J.-K., Melloni, G. E. M., & Park, P. J. (2021) · Nature Reviews Genetics · doi:10.1038/s41576-021-00431-y · Cited by 116 · see citing works

Systematic comparison of tools used for m6A mapping from nanopore direct RNA sequencing

Zhong, Z.-D., Xie, Y.-Y., Chen, H.-X., Lan, Y.-L., Liu, X., Ji, J.-Y., Wu, F., Jin, L., Chen, J., Mak, D. W., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-37596-5 · Cited by 120 · see citing works

Genome-wide detection of cytosine methylations in plant from Nanopore data using deep learning

Ni, P., Huang, N., Nie, F., Zhang, J., Zhang, Z., Wu, B. M., Bai, L., Liu, W., Xiao, C., Luo, F., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26278-9 · Cited by 120 · see citing works

GenASM: A High-Performance, Low-Power Approximate String Matching Acceleration Framework for Genome Sequence Analysis

Cali, D. S., Kalsi, G. S., Bingöl, Z., Fırtına, C., Subramanian, L., Kim, J. S., Ausavarungnirun, R., Alser, M., Gómez-Luna, J., Boroumand, A., et al. (2020) · IEEE/ACM International Symposium on Microarchitecture (MICRO) · doi:10.1109/micro50266.2020.00081 · Cited by 25 · see citing works

Single-cell transcriptomes of developing and adult olfactory receptor neurons in Drosophila

McLaughlin, C. N., Brbić, M., Xie, Q., Li, T., Horns, F., Kolluru, S. S., Kebschull, J. M., Vacek, D., Xie, A., Li, J., et al. (2021) · eLife · doi:10.7554/elife.63856 · Cited by 111 · see citing works

Long Reads Are Revolutionizing 20 Years of Insect Genome Sequencing

Hotaling, S., Sproul, J. S., Heckenhauer, J., Powell, A., Larracuente, A. M., Pauls, S. U., Kelley, J. L., & Frandsen, P. B. (2021) · Genome Biology and Evolution · doi:10.1093/gbe/evab138 · Cited by 117 · see citing works

Nanopore sequencing of single-cell transcriptomes with scCOLOR-seq

Philpott, M., Watson, J., Thakurta, A., Brown, T., Brown, T. P., Oppermann, U. C. T., & Cribbs, A. P. (2021) · Nature Biotechnology · doi:10.1038/s41587-021-00965-w · Cited by 111 · see citing works

Debugging and consolidating multiple synthetic chromosomes reveals combinatorial genetic interactions

Zhao, Y., Coelho, C., Hughes, A. L., Lazar‐Stefanita, L., Yang, S., Brooks, A. N., Walker, R. S. K., Zhang, W., Lauer, S. L., Hernandez, C., et al. (2023) · Cell · doi:10.1016/j.cell.2023.09.025 · Cited by 115 · see citing works

Utility of long-read sequencing for All of Us

Mahmoud, M., Huang, Y., Garimella, K. V., Audano, P. A., Wan, W., Prasad, N., Handsaker, R. E., Hall, S., Pionzio, A., Schatz, M. C., et al. (2024) · Nature Communications · doi:10.1038/s41467-024-44804-3 · Cited by 115 · see citing works

Reference flow: reducing reference bias using multiple population genomes

Chen, N.-C., Solomon, B., Mun, T., Iyer, S., & Langmead, B. (2021) · Genome biology · doi:10.1186/s13059-020-02229-3 · Cited by 113 · see citing works

Hybracter: enabling scalable, automated, complete and accurate bacterial genome assemblies

Bouras, G. S., Houtak, G., Wick, R. R., Mallawaarachchi, V., Roach, M. J., Papudeshi, B. N., Judd, L. M., Sheppard, A. E., Edwards, R. A., & Vreugde, S. (2024) · Microbial Genomics · doi:10.1099/mgen.0.001244 · Cited by 115 · see citing works

Sequencing and characterizing short tandem repeats in the human genome

Tanudisastro, H., Deveson, I. W., Dashnow, H., & MacArthur, D. G. (2024) · Nature reviews genetics · doi:10.1038/s41576-024-00692-3 · Cited by 108 · see citing works

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Ni, P., Nie, F., Zhong, Z., Xu, J., Huang, N., Zhang, J., Zhao, H., Zou, Y. F., Huang, Y., Li, J., et al. (2023) · Nature Communications · doi:10.1038/s41467-023-39784-9 · Cited by 114 · see citing works

Transcriptomics in the era of long-read sequencing

Monzó, C., Liu, T., & Conesa, A. (2025) · Nature Reviews Genetics · doi:10.1038/s41576-025-00828-z · Cited by 118 · see citing works

Genomics and multiomics in the age of precision medicine

Mani, S., Lalani, S., & Pammi, M. (2025) · Pediatric Research · doi:10.1038/s41390-025-04021-0 · Cited by 114 · see citing works

scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured

Sun, T., Song, D., Li, W. V., & Li, J. J. (2021) · Genome biology · doi:10.1186/s13059-021-02367-2 · Cited by 110 · see citing works

Alevin-fry unlocks rapid, accurate and memory-frugal quantification of single-cell RNA-seq data

He, D., Zakeri, M., Sarkar, H., Soneson, C., Srivastava, A., & Patro, R. (2022) · Nature Methods · doi:10.1038/s41592-022-01408-3 · Cited by 106 · see citing works

miQC: An adaptive probabilistic framework for quality control of single-cell RNA-sequencing data

Hippen, A. A., Falco, M. M., Weber, L. M., Erkan, E. P., Zhang, K., Doherty, J. A., Vähärautio, A., Greene, C. S., & Hicks, S. C. (2021) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1009290 · Cited by 106 · see citing works

The genus Serratia revisited by genomics

Williams, D. J., Grimont, P. A. D., Cazares, A., Grimont, F., Ageron, E., Pettigrew, K. A., Cazares, D., Njamkepo, E., Weill, F., Heinz, E., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-32929-2 · Cited by 108 · see citing works

A high-quality, chromosome-level genome assembly of the Black Soldier Fly ( Hermetia illucens L.)

Generalovic, T. N., McCarthy, S., Warren, I. A., Wood, J. M. D., Torrance, J., Sims, Y., Quail, M. A., Howe, K., Pipan, M., Durbin, R. M., et al. (2021) · G3 Genes Genomes Genetics · doi:10.1093/g3journal/jkab085 · Cited by 109 · see citing works

Underwater CAM photosynthesis elucidated by Isoetes genome

Wickell, D., Kuo, L., Yang, H., Ashok, A. D., Irisarri, I., Dadras, A., de Vries, S., de Vries, J., Huang, Y., Li, Z., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-26644-7 · Cited by 107 · see citing works

Manifold alignment for heterogeneous single-cell multi-omics data integration using Pamona

Cao, K., Hong, Y., & Wan, L. (2021) · Bioinformatics · doi:10.1093/bioinformatics/btab594 · Cited by 106 · see citing works

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 · see citing works

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 14 · see citing works

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