Artykuły w czasopismach: „Unique molecular identifiers”

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Schmierer, Bernhard, Sandeep K. Botla, Jilin Zhang, Mikko Turunen, Teemu Kivioja i Jussi Taipale. "CRISPR/Cas9 screening using unique molecular identifiers". Molecular Systems Biology 13, nr 10 (październik 2017): 945. http://dx.doi.org/10.15252/msb.20177834.

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Islam, Saiful, Amit Zeisel, Simon Joost, Gioele La Manno, Pawel Zajac, Maria Kasper, Peter Lönnerberg i Sten Linnarsson. "Quantitative single-cell RNA-seq with unique molecular identifiers". Nature Methods 11, nr 2 (22.12.2013): 163–66. http://dx.doi.org/10.1038/nmeth.2772.

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Liu, Daniel. "Algorithms for efficiently collapsing reads with Unique Molecular Identifiers". PeerJ 7 (16.12.2019): e8275. http://dx.doi.org/10.7717/peerj.8275.

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Background Unique Molecular Identifiers (UMI) are used in many experiments to find and remove PCR duplicates. There are many tools for solving the problem of deduplicating reads based on their finding reads with the same alignment coordinates and UMIs. However, many tools either cannot handle substitution errors, or require expensive pairwise UMI comparisons that do not efficiently scale to larger datasets. Results We reformulate the problem of deduplicating UMIs in a manner that enables optimizations to be made, and more efficient data structures to be used. We implement our data structures and optimizations in a tool called UMICollapse, which is able to deduplicate over one million unique UMIs of length 9 at a single alignment position in around 26 s, using only a single thread and much less than 10 GB of memory. Conclusions We present a new formulation of the UMI deduplication problem, and show that it can be solved faster, with more sophisticated data structures.

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Kivioja, Teemu, Anna Vähärautio, Kasper Karlsson, Martin Bonke, Martin Enge, Sten Linnarsson i Jussi Taipale. "Counting absolute numbers of molecules using unique molecular identifiers". Nature Methods 9, nr 1 (20.11.2011): 72–74. http://dx.doi.org/10.1038/nmeth.1778.

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Johansson, Gustav, Melita Kaltak, Cristiana Rîmniceanu, Avadhesh K. Singh, Jan Lycke, Clas Malmeström, Michael Hühn, Outi Vaarala, Susanna Cardell i Anders Ståhlberg. "Ultrasensitive DNA Immune Repertoire Sequencing Using Unique Molecular Identifiers". Clinical Chemistry 66, nr 9 (20.08.2020): 1228–37. http://dx.doi.org/10.1093/clinchem/hvaa159.

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Abstract Background Immune repertoire sequencing of the T-cell receptor can identify clonotypes that have expanded as a result of antigen recognition or hematological malignancies. However, current sequencing protocols display limitations with nonuniform amplification and polymerase-induced errors during sequencing. Here, we developed a sequencing method that overcame these issues and applied it to γδ T cells, a cell type that plays a unique role in immunity, autoimmunity, homeostasis of intestine, skin, adipose tissue, and cancer biology. Methods The ultrasensitive immune repertoire sequencing method used PCR-introduced unique molecular identifiers. We constructed a 32-panel assay that captured the full diversity of the recombined T-cell receptor delta loci in γδ T cells. The protocol was validated on synthetic reference molecules and blood samples of healthy individuals. Results The 32-panel assay displayed wide dynamic range, high reproducibility, and analytical sensitivity with single-nucleotide resolution. The method corrected for sequencing-depended quantification bias and polymerase-induced errors and could be applied to both enriched and nonenriched cells. Healthy donors displayed oligoclonal expansion of γδ T cells and similar frequencies of clonotypes were detected in both enrichment and nonenriched samples. Conclusions Ultrasensitive immune repertoire sequencing strategy enables quantification of individual and specific clonotypes in a background that can be applied to clinical as well as basic application areas. Our approach is simple, flexible, and can easily be implemented in any molecular laboratory.

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Pflug, Florian G., i Arndt von Haeseler. "TRUmiCount: correctly counting absolute numbers of molecules using unique molecular identifiers". Bioinformatics 34, nr 18 (16.04.2018): 3137–44. http://dx.doi.org/10.1093/bioinformatics/bty283.

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Clement, Kendell, Rick Farouni, Daniel E. Bauer i Luca Pinello. "AmpUMI: design and analysis of unique molecular identifiers for deep amplicon sequencing". Bioinformatics 34, nr 13 (27.06.2018): i202—i210. http://dx.doi.org/10.1093/bioinformatics/bty264.

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Babnigg, György, i Carol S. Giometti. "A database of unique protein sequence identifiers for proteome studies". PROTEOMICS 6, nr 16 (sierpień 2006): 4514–22. http://dx.doi.org/10.1002/pmic.200600032.

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Jin, Huan, Joshua M. Mitchell i Hunter N. B. Moseley. "Atom Identifiers Generated by a Neighborhood-Specific Graph Coloring Method Enable Compound Harmonization across Metabolic Databases". Metabolites 10, nr 9 (11.09.2020): 368. http://dx.doi.org/10.3390/metabo10090368.

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Metabolic flux analysis requires both a reliable metabolic model and reliable metabolic profiles in characterizing metabolic reprogramming. Advances in analytic methodologies enable production of high-quality metabolomics datasets capturing isotopic flux. However, useful metabolic models can be difficult to derive due to the lack of relatively complete atom-resolved metabolic networks for a variety of organisms, including human. Here, we developed a neighborhood-specific graph coloring method that creates unique identifiers for each atom in a compound facilitating construction of an atom-resolved metabolic network. What is more, this method is guaranteed to generate the same identifier for symmetric atoms, enabling automatic identification of possible additional mappings caused by molecular symmetry. Furthermore, a compound coloring identifier derived from the corresponding atom coloring identifiers can be used for compound harmonization across various metabolic network databases, which is an essential first step in network integration. With the compound coloring identifiers, 8865 correspondences between KEGG (Kyoto Encyclopedia of Genes and Genomes) and MetaCyc compounds are detected, with 5451 of them confirmed by other identifiers provided by the two databases. In addition, we found that the Enzyme Commission numbers (EC) of reactions can be used to validate possible correspondence pairs, with 1848 unconfirmed pairs validated by commonality in reaction ECs. Moreover, we were able to detect various issues and errors with compound representation in KEGG and MetaCyc databases by compound coloring identifiers, demonstrating the usefulness of this methodology for database curation.

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Egorov, Evgeny S., Ekaterina M. Merzlyak, Andrew A. Shelenkov, Olga V. Britanova, George V. Sharonov, Dmitriy B. Staroverov, Dmitriy A. Bolotin i in. "Quantitative Profiling of Immune Repertoires for Minor Lymphocyte Counts Using Unique Molecular Identifiers". Journal of Immunology 194, nr 12 (8.05.2015): 6155–63. http://dx.doi.org/10.4049/jimmunol.1500215.

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Smith, Tom, Andreas Heger i Ian Sudbery. "UMI-tools: modeling sequencing errors in Unique Molecular Identifiers to improve quantification accuracy". Genome Research 27, nr 3 (18.01.2017): 491–99. http://dx.doi.org/10.1101/gr.209601.116.

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Hu, Yu, Kai Wang i Mingyao Li. "Detecting differential alternative splicing events in scRNA-seq with or without Unique Molecular Identifiers". PLOS Computational Biology 16, nr 6 (5.06.2020): e1007925. http://dx.doi.org/10.1371/journal.pcbi.1007925.

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Karst, Søren M., Ryan M. Ziels, Rasmus H. Kirkegaard, Emil A. Sørensen, Daniel McDonald, Qiyun Zhu, Rob Knight i Mads Albertsen. "High-accuracy long-read amplicon sequences using unique molecular identifiers with Nanopore or PacBio sequencing". Nature Methods 18, nr 2 (11.01.2021): 165–69. http://dx.doi.org/10.1038/s41592-020-01041-y.

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Xu, Chang, Xiujing Gu, Raghavendra Padmanabhan, Zhong Wu, Quan Peng, John DiCarlo i Yexun Wang. "smCounter2: an accurate low-frequency variant caller for targeted sequencing data with unique molecular identifiers". Bioinformatics 35, nr 8 (6.09.2018): 1299–309. http://dx.doi.org/10.1093/bioinformatics/bty790.

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Robinson, Jacob E., i Christine E. Cutucache. "Unique molecular identifiers of indolent versus aggressive phenotyping in non-Hodgkin lymphoma: spotlight on SMZL." Journal of Immunology 200, nr 1_Supplement (1.05.2018): 123.6. http://dx.doi.org/10.4049/jimmunol.200.supp.123.6.

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Abstract Splenic marginal zone lymphoma (SMZL) is an indolent, non-Hodgkin’s lymphoma that lacks clear genotypic classification. While most cases progress slowly, approximately 30% of cases will become aggressive or undergo transformation to a more lethal lymphoma. The purpose of this study was to characterize the molecular profiles of SMZL cases compared with healthy B-cells and other B-cell lymphomas (BCL) in an effort to delineate indolent versus aggressive presentations. We conducted a meta-analysis of previously published gene expression data in order to identify genes most dysregulated in SMZL. We compared gene expression datasets among SMZL, similar B-cell neoplasms (all B-cell lymphomas), and healthy B-cell controls in order to extract a SMZL-specific, indolent phenotype profile. As a result, we observed a unique profile of genes upregulated in SMZL that are involved in immune defense (inclusive of leukocyte chemotaxis), motility (inclusive of lamellipodium assembly), cell proliferation, as well as other mechanisms. Of these, the most upregulated genes in SMZL were CXCL6, KAZN, NTN4, CD5L, AIF1L, and CD36. Additionally, 20 key markers of potential indolence were identified, with the largest expression differences seen in ABI3BP, GPNMB, CCL19, and ZC3H7B. Further investigation of these genes and their resultant impacted pathways will be evaluated for diagnostic and prognostic significance using immunohistochemistry, and hypothesized targets evaluated in vitro. Ultimately, we expect that the translation of these results will assist with patient staging in SMZL.

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Kou, Ruqin, Ham Lam, Hairong Duan, Li Ye, Narisra Jongkam, Weizhi Chen, Shifang Zhang i Shihong Li. "Benefits and Challenges with Applying Unique Molecular Identifiers in Next Generation Sequencing to Detect Low Frequency Mutations". PLOS ONE 11, nr 1 (11.01.2016): e0146638. http://dx.doi.org/10.1371/journal.pone.0146638.

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Amstler, S., L. Forer, G. Streiter, S. Di Maio, B. Paulweber, F. Kronenberg, S. Schönherr i S. Coassin. "Nanopore sequencing with unique molecular identifiers preserves SNP haplotypes of the LPA KIV-2 copy number variation". Atherosclerosis 379 (sierpień 2023): S47. http://dx.doi.org/10.1016/j.atherosclerosis.2023.06.202.

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Yesmin, Nusrat, Sabrina M. Elias, Md Sazzadur Rahman, Taslima Haque, A. K. M. Mahbub Hasan i Zeba I. Seraj. "Unique Genotypic Differences Discovered among Indigenous Bangladeshi Rice Landraces". International Journal of Genomics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/210328.

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Bangladesh is a reservoir of diverse rice germplasm and is home to many landraces with unique, important traits. Molecular characterization of these landraces is of value for their identification, preservation, and potential use in breeding programs. Thirty-eight rice landraces from different regions of Bangladesh including some high yielding BRRI varieties were analyzed by 34 polymorphic microsatellite markers yielding a total of 258 reproducible alleles. The analysis could locate 34 unique identifiers for 21 genotypes, making the latter potentially amenable to identity verification. An identity map for these genotypes was constructed with all the 12 chromosomes of the rice genome. Polymorphism information content (PIC) scores of the 34 SSR markers were 0.098 to 0.89 where on average 7.5 alleles were observed. A dendogram constructed using UPGMA clustered the varieties into two major groups and five subgroups. In some cases, the clustering matched with properties like aromaticity, stickiness, salt tolerance, and photoperiod insensitivity. The results will help breeders to work towards the proper utilization of these landraces for parental selection and linkage map construction for discovery of useful alleles.

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Mao, Ruifang, Shanshan Xiao, Rui Lin, Yuchen Wang i Tao Wang. "Technical validation of a high-sensitivity target capture NGS assay using unique molecular identifier approach." Journal of Clinical Oncology 38, nr 15_suppl (20.05.2020): e13657-e13657. http://dx.doi.org/10.1200/jco.2020.38.15_suppl.e13657.

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e13657 Background: Identification of a broad spectrum of somatic mutations is crucial to guide targeted therapy such as for non-small cell lung cancer (NSCLC) patients. In the clinical environment, it requires well validated NGS workflow both for the wet-lab and dry-lab procedures. Here we describe a high sensitivity target NGS assay to accurately capture single nucleotide variants (SNVs), short insertions and deletions (indels), copy number alterations and gene rearrangements for formalin-fixed paraffin-embedded (FFPE) NSCLC patient samples. Extensive analytical validation was performed following the checklists of College of American Pathologists. Methods: Next generation sequencing (NGS) libraries were prepared using extracted DNA from FFPE tissue NSCLC patient samples. The protocol for library generation was optimized in several steps and incorporated 10bp unique molecular identifiers (UMIs). The libraries were sequenced on Illumina HiSeq X-Ten platform. The sequence data was analyzed by an in-house bioinformatics pipeline to call somatic mutations at an average depth of 4000X. Results: We tested the accuracy of 68 clinical tumor samples that were also validated by conventional or alternative methods in the third party CAP accredited labs. We observed 100% sensitivity and 100% specificity compared with the other lab¡¯s validation results. To define the limit of detection (LOD) for different mutation types, clinical DNA samples containing different variants were diluted with normal DNA. The LODs for SNV (as in EGFR L858R) and indel (as in EGFR 19del) were 0.5% and 1%, respectively. Addressing the LOD of fusion and copy number alteration is usually challenging. Our NGS assay was able to achieve 2% LOD for gene rearrangement (fusion) and 3.5 copies for copy number amplification. The high reproducibility was also achieved by inter- and intra- replicate experiments. Our NGS assay showed better performance than other widely used commercial NGS assay panels. Conclusions: We have validated an NGS based approach with UMI technology that is able to achieve high accuracy and sensitivity as low as 0.5% for detection of somatic mutations, which will improve the clinical testing performance for NSCLC FFPE samples with low allele frequencies of driver mutations.

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Bürckert, Jean-Philippe, William J. Faison, Danielle E. Mustin, Axel R. S. X. Dubois, Regina Sinner, Oliver Hunewald, Anke Wienecke-Baldacchino, Anne Brieger i Claude P. Muller. "High-throughput sequencing of murine immunoglobulin heavy chain repertoires using single side unique molecular identifiers on an Ion Torrent PGM". Oncotarget 9, nr 54 (13.07.2018): 30225–39. http://dx.doi.org/10.18632/oncotarget.25493.

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Gligoric, Nenad, Srdjan Krco, Liisa Hakola, Kaisa Vehmas, Suparna De, Klaus Moessner, Kristoffer Jansson, Ingmar Polenz i Rob van Kranenburg. "SmartTags: IoT Product Passport for Circular Economy Based on Printed Sensors and Unique Item-Level Identifiers". Sensors 19, nr 3 (30.01.2019): 586. http://dx.doi.org/10.3390/s19030586.

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In this paper, we present a method that facilitates Internet of Things (IoT) for building a product passport and data exchange enabling the next stage of the circular economy. SmartTags based on printed sensors (i.e., using functional ink) and a modified GS1 barcode standard enable unique identification of objects on a per item-level (including Fast-Moving Consumer Goods—FMCG), collecting, sensing, and reading of parameters from environment as well as tracking a products’ lifecycle. The developed ontology is the first effort to define a semantic model for dynamic sensors, including datamatrix and QR codes. The evaluation of decoding and readability of identifiers (QR codes) showed good performance for detection of sensor state printed over and outside the QR code data matrix, i.e., the recognition ability with image vision algorithm was possible. The evaluation of the decoding performance of the QR code data matrix printed with sensors was also efficient, i.e., the QR code ability to be decoded with the reader after reversible and irreversible process of ink (dis)appearing was preserved, with slight drop in performance if ink density is low.

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Yang, Yang, Di Zheng, Chunyan Wu, Analyn Lizaso, Junyi Ye, Shannon Chuai, Jian Ni, Jianfang Xu i Gening Jiang. "Detecting Ultralow Frequency Mutation in Circulating Cell‐Free DNA of Early‐Stage Nonsmall Cell Lung Cancer Patients with Unique Molecular Identifiers". Small Methods 3, nr 10 (26.04.2019): 1900206. http://dx.doi.org/10.1002/smtd.201900206.

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Adenipekun, C. O., L. A. Ogunkanmi i O. Onibonoje. "Morphological and molecular assessment of mushroom (Lentinus Squarrosulus) (mont.) Singer". Ife Journal of Science 23, nr 2 (17.11.2021): 43–52. http://dx.doi.org/10.4314/ijs.v23i2.5.

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Lentinus squarrosulus is a popular mushroom in Nigeria used for traditional medicine apart from food. The identification of those high-quality fungal species is not only necessary but has great economic significance as it will allow product distributors to verify the material they are selling. Hence, this study investigated the morphological and molecular relationship among L. squarrosulus samples from different locations in Ibadan. Ten samples of L. squarrosulus were collected from nine different natural habitats in Ibadan, Oyo State, Nigeria, from which pure cultures were prepared. Isolation of DNA was done from fruiting bodies of fresh samples evaluated. Ten primers were designed from ITS sequences of the Family Agariceae and used for the study. The ten mushrooms evaluated in the study showed diverse morphological features such as colour of cap and pileus, size of stipe and pileus. A total of 50 amplicons were generated of which 31 bands (62%) were polymorphic. The RAPD variety-specific products were generated in some of the genotypes evaluated which can serve as unique identifiers. The study showed mean values for marker gene diversity of 0.27, Polymorphism Information Content (PIC) of 0.25 and 63.81% polymorphism. Both morphological and molecular analyses revealed two clustered groups. Number and types of samples in each group were not the same in both studies. The presence of unique band pattern among sampled fungi evaluated showed the discriminating power of the primer Ast-F in the study. Keywords: Polymorphism, DNA, RAPD, Fungi, Gene diversity characterization

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Choi, Ashley, Samuel Meier, Silvia Fenoglio, Tianshu Feng, Justin Engel, Binzhang Shen, Shangtao Liu i in. "Abstract 1224: UMIBB: A novel nonparametric Bayesian method improves robustness and sensitivity of analysis in pooled CRISPR-Cas9 screens leveraging unique molecular identifiers". Cancer Research 82, nr 12_Supplement (15.06.2022): 1224. http://dx.doi.org/10.1158/1538-7445.am2022-1224.

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Abstract CRISPR-based functional genomics screens are a powerful tool for identifying synthetically lethal cancer drug targets. Current strategies for analyzing pooled CRISPR screens usually rely on signals from single guide RNAs (sgRNA) with differential relative abundance between two experimental conditions. However, conventional approaches are susceptible to false positives and false negatives driven by outlier cell clones, since the sgRNA abundance does not account for the heterogeneous phenotypes resulting from different editing outcomes of the same sgRNA. To overcome this, we added DNA barcodes to each sgRNA to create unique molecular identifiers (UMIs) for CRISPR libraries and developed a companion analytical platform that enables robust, industry-scale CRISPR screens. Here, we present UMIBB, a novel nonparametric Bayesian approach for analyzing UMI-CRISPR data. The number of UMIs with normalized count depletion or enrichment compared to the control experimental condition for each sgRNA is modeled by a beta-binomial distribution. The gene level statistics are derived by combining z-scores of the sgRNAs level posterior probabilities weighted by the number of UMIs in each sgRNA. This approach minimizes the impact of outlier cell clones on statistics and prioritizes genes with consistent count differentials across multiple UMIs in each gene. To assess the power of UMIBB, we benchmarked it on a low coverage (200X) genome-scale negative-selection screen, comparing with results from a high coverage (1000X) screen. These screens were conducted on KRAS mutant cancer celllines (A549) treated with trametinib or vehicle control. Despite the high noise level usually observed in lower coverage screens, our method was able to uncover most of the validated sensitizer genes for trametinib and achieved the highest sensitivity compared to conventional methods. Furthermore, we applied UMIBB on a genome-scale positive-selection screen and successfully identified novel genes (RAD18 and UBE2K) as key mediators of USP1 dependency in BRCA1 mutant cell lines. Our studies demonstrate that UMIBB is highly robust against false positives due to clonal heterogeneity and is more likely to identify true genetic interactions. Citation Format: Ashley Choi, Samuel Meier, Silvia Fenoglio, Tianshu Feng, Justin Engel, Binzhang Shen, Shangtao Liu, Teng Teng, Tenzing Khendu, Alan Huang, Jannik Andersen, Xuewen Pan, Yi Yu. UMIBB: A novel nonparametric Bayesian method improves robustness and sensitivity of analysis in pooled CRISPR-Cas9 screens leveraging unique molecular identifiers [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1224.

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Baer, Constance Regina, Niroshan Nadarajah, Claudia Haferlach, Wolfgang Kern i Torsten Haferlach. "The Use of Unique Molecular Identifiers (UMIs) Strongly Improves Sequencing Detection Limits Allowing Earlier Detection of Small TP53 Mutated Clones in Leukemias". Blood 128, nr 22 (2.12.2016): 2027. http://dx.doi.org/10.1182/blood.v128.22.2027.2027.

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Abstract Background: TP53 mutations arise in a broad set of hematologic diseases and are associated with poor prognosis and therapy failure. Even small TP53 mutated clones were demonstrated to be of clinical relevance and therefore their early detection is mandatory. Mutations can occur throughout the entire gene (mainly exons 4-10) and include base exchanges, deletions and insertions. Next generation sequencing (NGS) generally detects mutations, which are present in at least 3% of sequences. The detection of mutations at burdens below 3% is still hampered by polymerase and sequencing errors. Especially true mutations caused by single base exchanges (missense-, nonsense- and splice site mutations) are difficult to distinguish from non-specific background. To overcome this limitation, individual molecules can be tagged by unique molecular identifiers (UMIs). UMIs are small random sequences added to each individual molecule before amplification. Building a consensus sequence out of all amplified products derived from one original DNA template, allows reconstructing the sequence of the initial molecule and thereby eliminates amplification errors in silico. Aim: 1) To evaluate reduction of non-specific background in NGS assays after using UMIs to build consensus sequences. 2) To use consensus sequencing to identify early subclones by backtracking of known TP53 mutations in CLL patients. Methods: We added eight random nucleotides as UMI to all reverse primers (design adapted from Peng, et al. 2015) and performed an initial primer extension step. In a subsequent PCR, regions of interest including UMIs were amplified and adapters were added for MiSeq sequencing (Illumina, San Diego, CA). We performed 119 sequencing assays, and analyzed results with a 1% detection limit. Consensus sequences were built using SeqNext 4.3 (JSI Medical Systems, Kippenheim, Germany). A median number of 6 (range: 2-115) reads/consensus read was obtained. Samples contained 66 previously identified mutations (47 single base exchanges; 14 small deletions; 5 small insertions), of which 29 had a burden of 3% or lower. These had been confirmed to be specific by independently repeated sequencing analysis or known in patients at multiple time points during follow-up. Results: We evaluated background signal at each position before consensus read building. On average 97.5% of bases had low-level non-specific background. At each individual position, 0.01-0.87% of reads deviated from the reference sequence (Figure A). Building consensus reads by combining all sequences derived from one original DNA molecule reduced the number of bases with low-level non-specific signal to an average of 18% (Figure B). We performed 119 sequencing analysis with a 1% detection limit, aiming to identify 66 known mutations and no non-specific deviations from the reference sequence. With both approaches, 63/66 mutations were detected and correlation of mutation burdens was high (R2=0.99; P<0.001, calculated by linear regression). Two mutations (1% and 2%) only reached the detection cutoff without consensus read building and one mutation only after consensus read building. Importantly, without using UMIs for consensus reads, in sum 88 non-specific deviations from the reference sequence (likely artifacts) were detectable with the 1% cutoff, while only two likely artifacts remained after consensus sequences building. Thus, the reduction of sequencing artifacts should allow using a 1% cutoff for mutation detection in future routine settings. Therefore, we conducted a backtracking using 31 of the above identified TP53 mutations detected in 15 CLL patients. Samples covered a median timeframe of 26 (range: 2-68) months. Using the previous 3% cutoff for mutation burden, we identified 8/31 (26%) mutations 2-55 months earlier (median: 4 months). Even more, using the adjusted 1% cutoff with UMIs allowed detecting 18/31 (58%) TP53 mutations earlier (2-55 months; median: 18 months). Conclusion: Including UMIs and building consensus sequences, 1) reduced background signal in silico and 2) allowed improving NGS detection limits. This is crucial for the identification of low burden mutations in TP53 and other genes, where small subclones can rapidly expand and have been shown to require early treatment intervention. Disclosures Baer: MLL Munich Leukemia Laboratory: Employment. Nadarajah:MLL Munich Leukemia Laboratory: Employment. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Kern:MLL Munich Leukemia Laboratory: Employment, Equity Ownership. Haferlach:MLL Munich Leukemia Laboratory: Employment, Equity Ownership.

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Xie, Hongyu, Yaxi Zhang, Pei Zhihua, Jianing Yu, Yiqian Liu, Shiqi Zheng, Geng Chen, Weizhi Chen i Ji He. "A unique molecular identifier-based and clonal hematopoiesis-aware approach for accurate mutation calling in cell-free DNA assays." Journal of Clinical Oncology 39, nr 15_suppl (20.05.2021): e22515-e22515. http://dx.doi.org/10.1200/jco.2021.39.15_suppl.e22515.

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e22515 Background: Given peripheral blood cells (PBCs) matched cell-free DNA (cfDNA), accurate mutation calling in next generation sequencing (NGS)-based assays relies on discriminating artifacts and clonal hematopoiesis mutations from tissue originated somatic mutations. Although clonal hematopoiesis has been considered in previous overall error modeling, it has not been adapted to PBCs without using unique molecular identifiers (UMIs). Moreover, previous studies on background error profiling were mainly based on healthy controls without matched PBC gDNA, which may lead to potential overestimation of the error rates on those sites with clonal hematopoiesis mutations. Additionally, the fraction of tissue cells is also an important influencing factor but is usually ignored. Methods: We performed UMI-assisted capture-based DNA assays on cfDNA samples, matched PBCs, and oral epithelium cells from 150 healthy donors. A site-specific and subtype-specific background error model was first built for PBCs using the SNVs called from PBCs with matched oral epithelium cells to exclude potential clonal hematopoiesis mutations. Then a similar background model was established for cfDNA with the SNVs inferred from cfDNA to exclude clonal hematopoiesis. The SNVs identified in cfDNA and matched PBCs were separately filtered with the cfDNA and PBC background error models. In this study, we used the ultrasensitive liquid biopsy approach to evaluate paired with tissue and blood samples from 56 early-stage NSCLC patients. All samples are sequenced using NGS target-capture panels covering 29 genes. Results: The mutations were detected in 91.1% of tissue and 67.9% were discovered in plasma. The coincidence rate between tissue and plasma of the 56 early-stage NSCLC patients was 66.1%. Conclusions: We have developed a novel method tailored for UMI-assisted capture-based targeted DNA assays, which outperforms currently available methods in terms of modeling background errors and filtering clonal hematopoietic mutations.

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Koelling, Nils, Marie Bernkopf, Eduardo Calpena, Geoffrey J. Maher, Kerry A. Miller, Hannah K. Ralph, Anne Goriely i Andrew O. M. Wilkie. "amplimap: a versatile tool to process and analyze targeted NGS data". Bioinformatics 35, nr 24 (26.07.2019): 5349–50. http://dx.doi.org/10.1093/bioinformatics/btz582.

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Abstract Summary amplimap is a command-line tool to automate the processing and analysis of data from targeted next-generation sequencing experiments with PCR-based amplicons or capture-based enrichment systems. From raw sequencing reads, amplimap generates output such as read alignments, annotated variant calls, target coverage statistics and variant allele counts and frequencies for each target base pair. In addition to its focus on user-friendliness and reproducibility, amplimap supports advanced features such as consensus base calling for read families based on unique molecular identifiers and filtering false positive variant calls caused by amplification of off-target loci. Availability and implementation amplimap is available as a free Python package under the open-source Apache 2.0 License. Documentation, source code and installation instructions are available at https://github.com/koelling/amplimap.

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Hauck, Nastasja, Josiane Kirpach, Christina Kiefer, Sophie Farinelle, Sophie Maucourant, Stephen Morris, William Rosenberg, Feng He, Claude Muller i I.-Na Lu. "Applying Unique Molecular Identifiers in Next Generation Sequencing Reveals a Constrained Viral Quasispecies Evolution under Cross-Reactive Antibody Pressure Targeting Long Alpha Helix of Hemagglutinin". Viruses 10, nr 4 (25.03.2018): 148. http://dx.doi.org/10.3390/v10040148.

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Zhou, Shuntai, i Ronald Swanstrom. "Fact and Fiction about 1%: Next Generation Sequencing and the Detection of Minor Drug Resistant Variants in HIV-1 Populations with and without Unique Molecular Identifiers". Viruses 12, nr 8 (4.08.2020): 850. http://dx.doi.org/10.3390/v12080850.

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Next generation sequencing (NGS) platforms have the ability to generate almost limitless numbers of sequence reads starting with a PCR product. This gives the illusion that it is possible to analyze minor variants in a viral population. However, including a PCR step obscures the sampling depth of the viral population, the key parameter needed to understand the utility of the data set for finding minor variants. Also, these high throughput sequencing platforms are error prone at the level where minor variants are of interest, confounding the interpretation of detected minor variants. A simple strategy has been applied in multiple applications of NGS to solve these problems. Prior to PCR, individual molecules are “tagged” with a unique molecular identifier (UMI) that can be used to establish the actual sample size of viral genomes sequenced after PCR and sequencing. In addition, since PCR generates many copies of each sequence tagged to a specific UMI, a template consensus sequence (TCS) can be created from the many reads of each template, removing virtually all of the method error. From this perspective we examine our own use of a UMI, called Primer ID, in the detection of minor drug resistant variants in HIV-1 populations.

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Gu, Xiaolin, Wenjia Wu, Xiaodan Gu, Zhen Ling, Ming Yang i Aibo Song. "Probe Request Based Device Identification Attack and Defense". Sensors 20, nr 16 (17.08.2020): 4620. http://dx.doi.org/10.3390/s20164620.

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Wi-Fi network has an open nature so that it needs to face greater security risks compared to wired network. The MAC address represents the unique identifier of the device, and is easily obtained by an attacker. Therefore MAC address randomization is proposed to protect the privacy of devices in a Wi-Fi network. However, implicit identifiers are used by attackers to identify user’s device, which can cause the leakage of user’s privacy. We propose device identification based on 802.11ac probe request frames. Here, a detailed analysis on the effectiveness of 802.11ac fields is given and a novel device identification method based on deep learning whose average f1-score exceeds 99% is presented. With a purpose of preventing attackers from obtaining relevant information by the device identification method above, we design a novel defense mechanism based on stream cipher. In that case, the original content of probe request frame is hidden by encrypting probe request frames and construction of probe request is reserved to avoid the finding of attackers. This defense mechanism can effectively reduce the performance of the proposed device identification method whose average f1-score is below 30%. In general, our research on attack and defense mechanism can preserve device privacy better.

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YU, GONG-XIN. "RULEMINER: A KNOWLEDGE SYSTEM FOR SUPPORTING HIGH-THROUGHPUT PROTEIN FUNCTION ANNOTATIONS". Journal of Bioinformatics and Computational Biology 02, nr 04 (grudzień 2004): 595–617. http://dx.doi.org/10.1142/s0219720004000752.

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In this paper, we present RuleMiner, a knowledge system to facilitate a seamless integration of multi-sequence analysis tools and define profile-based rules for supporting high-throughput protein function annotations. This system consists of three essential components, Protein Function Groups (PFGs), PFG profiles and rules. The PFGs, established from an integrated analysis of current knowledge of protein functions from Swiss-Prot database and protein family-based sequence classifications, cover all possible cellular functions available in the database. The PFG profiles illustrate detailed protein features in the PFGs as in sequence conservations, the occurrences of sequence-based motifs, domains and species distributions. The rules, extracted from the PFG profiles, describe the clear relationships between these PFGs and all possible features. As a result, the RuleMiner is able to provide an enhanced capability for protein function analysis, such as results from the integrated sequence analysis tools for given proteins can be comparatively analyzed due to the clear feature-PFG relationships. Also, much needed guidance is readily available for such analysis. If the rules describe one-to-one (unique) relationships between the protein features and the PFGs, then these features can be utilized as unique functional identifiers and cellular functions of unknown proteins can be reliably determined. Otherwise, additional information has to be provided.

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Yang, Xiao, Yasushi Saito, Arjun Rao, Hyunsung John Kim, Pranav Singh, Eric Scott, Matthew Larson, Wenying Pan, Mohini Desai i Earl Hubbell. "Alignment-free filtering for cfNA fusion fragments". Bioinformatics 35, nr 14 (lipiec 2019): i225—i232. http://dx.doi.org/10.1093/bioinformatics/btz346.

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Abstract Motivation Cell-free nucleic acid (cfNA) sequencing data require improvements to existing fusion detection methods along multiple axes: high depth of sequencing, low allele fractions, short fragment lengths and specialized barcodes, such as unique molecular identifiers. Results AF4 was developed to address these challenges. It uses a novel alignment-free kmer-based method to detect candidate fusion fragments with high sensitivity and orders of magnitude faster than existing tools. Candidate fragments are then filtered using a max-cover criterion that significantly reduces spurious matches while retaining authentic fusion fragments. This efficient first stage reduces the data sufficiently that commonly used criteria can process the remaining information, or sophisticated filtering policies that may not scale to the raw reads can be used. AF4 provides both targeted and de novo fusion detection modes. We demonstrate both modes in benchmark simulated and real RNA-seq data as well as clinical and cell-line cfNA data. Availability and implementation AF4 is open sourced, licensed under Apache License 2.0, and is available at: https://github.com/grailbio/bio/tree/master/fusion.

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Klepikova, Anna V., Artem S. Kasianov, Mikhail S. Chesnokov, Natalia L. Lazarevich, Aleksey A. Penin i Maria Logacheva. "Effect of method of deduplication on estimation of differential gene expression using RNA-seq". PeerJ 5 (16.03.2017): e3091. http://dx.doi.org/10.7717/peerj.3091.

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BackgroundRNA-seq is a useful tool for analysis of gene expression. However, its robustness is greatly affected by a number of artifacts. One of them is the presence of duplicated reads.ResultsTo infer the influence of different methods of removal of duplicated reads on estimation of gene expression in cancer genomics, we analyzed paired samples of hepatocellular carcinoma (HCC) and non-tumor liver tissue. Four protocols of data analysis were applied to each sample: processing without deduplication, deduplication using a method implemented in samtools, and deduplication based on one or two molecular indices (MI). We also analyzed the influence of sequencing layout (single read or paired end) and read length. We found that deduplication without MI greatly affects estimated expression values; this effect is the most pronounced for highly expressed genes.ConclusionThe use of unique molecular identifiers greatly improves accuracy of RNA-seq analysis, especially for highly expressed genes. We developed a set of scripts that enable handling of MI and their incorporation into RNA-seq analysis pipelines. Deduplication without MI affects results of differential gene expression analysis, producing a high proportion of false negative results. The absence of duplicate read removal is biased towards false positives. In those cases where using MI is not possible, we recommend using paired-end sequencing layout.

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Yadav, Divya, Balwant Raj i Balwinder Raj. "Design and Simulation of Low Power Microcontroller for Internet of Things Applications". Sensor Letters 18, nr 5 (1.05.2020): 401–9. http://dx.doi.org/10.1166/sl.2020.4241.

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The Internet of Things (IoT) is an array of interrelated registering gadgets, mechanical and advanced electronics machines, articles, creatures or individuals that are given with unique identifiers and the ability to exchange data over a system without man to man or man to PC partnership. IoT created an expanded enthusiasm to research and industrial into points of view. This development is due to the availability of low-priced, low-powered diminutive elements like processors, communications and sensors that were integrated on a single chip. In this work we design the low power microcontroller for IoT application. There are various microcontrollers available in the market for IoT application, we have done the comparative study of different microcontroller and proposed a low power microcontroller architecture based on the requirement of IoT. The power analysis is carried out by calculating power consumed in the different digital circuits with ALU and without ALU.

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Prünte, Philipp, Daniel Schoepflin i Thorsten Schüppstuhl. "A Comparative Study of Visual Identification Methods for Highly Similar Engine Tubes in Aircraft Maintenance, Repair and Overhaul". Sensors 23, nr 15 (28.07.2023): 6779. http://dx.doi.org/10.3390/s23156779.

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Unique identification of machine parts is critical to production and maintenance, repair and overhaul (MRO) processes in the aerospace industry. Despite recent advances in automating these identification processes, many are still performed manually. This is time-consuming, labour-intensive and prone to error, particularly when dealing with visually similar objects that lack distinctive features or markings or when dealing with parts that lack readable identifiers due to factors such as dirt, wear and discolouration. Automation of these processes has the potential to alleviate these problems. However, due to the high visual similarity of components in the aerospace industry, commonly used object identifiers are not directly transferable to this domain. This work focuses on the challenging component spectrum engine tubes and aims to understand which identification method using only object-inherent properties can be applied to such problems. Therefore, this work investigates and proposes a comprehensive set of methods using 2D image or 3D point cloud data, incorporating digital image processing and deep learning approaches. Each of these methods is implemented to address the identification problem. A comprehensive benchmark problem is presented, consisting of a set of visually similar demonstrator tubes, which lack distinctive visual features or markers and pose a challenge to the different methods. We evaluate the performance of each algorithm to determine its potential applicability to the target domain and problem statement. Our results indicate a clear superiority of 3D approaches over 2D image analysis approaches, with PointNet and point cloud alignment achieving the best results in the benchmark.

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Imoto, Yusuke, Tomonori Nakamura, Emerson G. Escolar, Michio Yoshiwaki, Yoji Kojima, Yukihiro Yabuta, Yoshitaka Katou, Takuya Yamamoto, Yasuaki Hiraoka i Mitinori Saitou. "Resolution of the curse of dimensionality in single-cell RNA sequencing data analysis". Life Science Alliance 5, nr 12 (9.08.2022): e202201591. http://dx.doi.org/10.26508/lsa.202201591.

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Single-cell RNA sequencing (scRNA-seq) can determine gene expression in numerous individual cells simultaneously, promoting progress in the biomedical sciences. However, scRNA-seq data are high-dimensional with substantial technical noise, including dropouts. During analysis of scRNA-seq data, such noise engenders a statistical problem known as the curse of dimensionality (COD). Based on high-dimensional statistics, we herein formulate a noise reduction method, RECODE (resolution of the curse of dimensionality), for high-dimensional data with random sampling noise. We show that RECODE consistently resolves COD in relevant scRNA-seq data with unique molecular identifiers. RECODE does not involve dimension reduction and recovers expression values for all genes, including lowly expressed genes, realizing precise delineation of cell fate transitions and identification of rare cells with all gene information. Compared with representative imputation methods, RECODE employs different principles and exhibits superior overall performance in cell-clustering, expression value recovery, and single-cell–level analysis. The RECODE algorithm is parameter-free, data-driven, deterministic, and high-speed, and its applicability can be predicted based on the variance normalization performance. We propose RECODE as a powerful strategy for preprocessing noisy high-dimensional data.

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van Brug, Heather E., Frits R. Rosendaal, Liza N. van Steenbergen, Rob G. H. H. Nelissen i Maaike G. J. Gademan. "Data linkage of two national databases: Lessons learned from linking the Dutch Arthroplasty Register with the Dutch Foundation for Pharmaceutical Statistics". PLOS ONE 18, nr 3 (8.03.2023): e0282519. http://dx.doi.org/10.1371/journal.pone.0282519.

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Background To provide guidance on data linkage in case of non-unique identifiers, we present a case study linking the Dutch Foundation for Pharmaceutical Statistics and Dutch Arthroplasty Register to investigate opioid prescriptions before/after arthroplasty. Methods Deterministic data linkage was used. Records were linked on: sex, birthyear, postcode, surgery date, or thromboprophylaxis initiation as a proxy for the surgery date. Different postcodes were used, depending on availability: patient postcode (available from 2013 onwards), hospital postcode with codes for physicians/hospitals, and hospital postcode with catchment area. Linkage was assessed in several groups: linked arthroplasties, linked on patient postcode, linked on patient postcode, and low-molecular-weight heparin(LWMH). Linkage quality was assessed by checking prescriptions after death, antibiotics after revision for infection, and presence of multiple prostheses. Representativeness was assessed by comparing the patient-postcode-LMWH group with the remaining arthroplasties. External validation was performed by comparing our opioid prescription rates with those derived from datasets from Statistics Netherlands. Results We linked 317,899 arthroplasties on patient postcode/hospital postcode(48%). Linkage on the hospital postcode appeared insufficient. Linkage uncertainty ranged from roughly 30% in all arthroplasties to 10–21% in the patient-postcode-LMWH-group. This subset resulted in 166.357(42%) linked arthroplasties after 2013 with somewhat younger age, fewer females, and more often osteoarthritis than other indications compared to the other arthroplasties. External validation showed similar increases in opioid prescription rates. Conclusions After identifier selection, checking data availability and internal validity, assessing representativeness, and externally validating our results we found sufficient linkage quality in the patient-postcode-LMWH-group, which consisted of around 42% of the arthroplasties performed after 2013.

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Ali, Dema, Dana Alhattab, Hanan Jafar, Malak Alzubide, Nour Sharar, Salwa Bdour i Abdalla Awidi. "Differential Marker Expression between Keratinocyte Stem Cells and Their Progeny Generated from a Single Colony". International Journal of Molecular Sciences 22, nr 19 (6.10.2021): 10810. http://dx.doi.org/10.3390/ijms221910810.

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The stemness in keratinocyte stem cells (KSCs) is determined by their gene expression patterns. KSCs are crucial in maintaining epidermal homeostasis and wound repair and are widely used candidates for therapeutic applications. Although several studies have reported their positive identifiers, unique biomarkers for KSCs remain elusive. Here, we aim to identify potential candidate stem cell markers. Human epidermal keratinocytes (HEKs) from neonatal foreskin tissues were isolated and cultured. Single-cell clonal analysis identified and characterized three types of cells: KSCs (holoclones), transient amplifying cells (TACs; meroclones), and differentiated cells (DSCs; paraclones). The clonogenic potential of KSCs demonstrated the highest proliferation potential of KSCs, followed by TACs and DSCs, respectively. Whole-transcriptome analysis using microarray technology unraveled the molecular signatures of these cells. These results were validated by quantitative real-time polymerase chain reaction and flow cytometry analysis. A total of 301 signature upregulated and 149 downregulated differentially expressed genes (DEGs) were identified in the KSCs, compared to TACs and DSCs. Furthermore, DEG analyses revealed new sets of genes related to cell proliferation, cell adhesion, surface makers, and regulatory factors. In conclusion, this study provides a useful source of information for the identification of potential SC-specific candidate markers.

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Song, Chen, Ariel Erijman, Bradley W. Langhorst, Pingfang Liu, Eileen T. Dimalanta i Theodore B. Davis. "Abstract 5628: Immune repertoire sequencing facilitates gamma delta T cell clonal determination". Cancer Research 82, nr 12_Supplement (15.06.2022): 5628. http://dx.doi.org/10.1158/1538-7445.am2022-5628.

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Abstract Gamma-delta T cells are a small fraction of T lymphocytes with only 1-5% of the overall T cell population, but they are an important subset that have unique contributions to both innate and adaptive immunity. Gamma-delta T cells can recognize a broad range of antigens to provide rapid responses to pathogens, and can also interact with both immune cells and non-immune tissue cells triggering regulatory and cytotoxic responses. These unique features make them ideal candidates that could be targeted to induce durable immunity in the context of different pathologies. There has been growing interest in understanding the contributions of gamma-delta T cells to immunology and developing efficient gamma-delta T-cell-based therapies for cancer, infectious disease, and autoimmune disease. In this study, we have implemented T cell repertoire sequencing for high throughput characterization. Gamma-delta T cells were enriched from tissues and peripheral blood mononuclear cells (PBMCs). RNA was extracted and used to generate full length TCR libraries. Unique molecular identifiers (UMIs) were incorporated to discretely barcode each mRNA molecule, enabling absolute quantitative ranking of TCR clone abundance. Full length immune repertoire sequencing facilitates the detection of distinct and shared clones in tissue and blood samples, enabling the identification of disease specific clones to evaluate immunotherapy effects. In addition, RNA sequencing was performed for gene expression analysis of gamma-delta T cells to identify cell phenotypes. Citation Format: Chen Song, Ariel Erijman, Bradley W. Langhorst, Pingfang Liu, Eileen T. Dimalanta, Theodore B. Davis. Immune repertoire sequencing facilitates gamma delta T cell clonal determination [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 5628.

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Wilkins, Oscar G., Charlotte Capitanchik, Nicholas M. Luscombe i Jernej Ule. "Ultraplex: A rapid, flexible, all-in-one fastq demultiplexer". Wellcome Open Research 6 (7.06.2021): 141. http://dx.doi.org/10.12688/wellcomeopenres.16791.1.

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Background: The first step of virtually all next generation sequencing analysis involves the splitting of the raw sequencing data into separate files using sample-specific barcodes, a process known as “demultiplexing”. However, we found that existing software for this purpose was either too inflexible or too computationally intensive for fast, streamlined processing of raw, single end fastq files containing combinatorial barcodes. Results: Here, we introduce a fast and uniquely flexible demultiplexer, named Ultraplex, which splits a raw FASTQ file containing barcodes either at a single end or at both 5’ and 3’ ends of reads, trims the sequencing adaptors and low-quality bases, and moves unique molecular identifiers (UMIs) into the read header, allowing subsequent removal of PCR duplicates. Ultraplex is able to perform such single or combinatorial demultiplexing on both single- and paired-end sequencing data, and can process an entire Illumina HiSeq lane, consisting of nearly 500 million reads, in less than 20 minutes. Conclusions: Ultraplex greatly reduces computational burden and pipeline complexity for the demultiplexing of complex sequencing libraries, such as those produced by various CLIP and ribosome profiling protocols, and is also very user friendly, enabling streamlined, robust data processing. Ultraplex is available on PyPi and Conda and via Github.

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Casparie, M., A. T. M. G. Tiebosch, G. Burger, H. Blauwgeers, A. van de Pol, J. H. J. M. van Krieken i G. A. Meijer. "Pathology Databanking and Biobanking in The Netherlands, a Central Role for PALGA, the Nationwide Histopathology and Cytopathology Data Network and Archive". Analytical Cellular Pathology 29, nr 1 (1.01.2007): 19–24. http://dx.doi.org/10.1155/2007/971816.

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Since 1991, a nationwide histopathology and cytopathology network and archive is in operation in The Netherlands under the name PALGA, encompassing all sixty-four pathology laboratories in The Netherlands. The overall system comprises decentralized systems at the participating laboratories, a central databank, and a dedicated communication and information exchange tool. Excerpts of all histopathology and cytopathology reports are generated automatically at the participating laboratories and transferred to the central databank. Both the decentralized systems and the central system perform checks on the quality and completeness of excerpts. Currently, about 42 million records on almost 10 million patients are stored in the central databank. Each excerpt contains patient identifiers, including demographic data and the so-called PALGA diagnosis. The latter is structured along five classification axes: topography, morphology, function, procedure, and diseases. All data transfer and communication occurs electronically with encryption of patient and laboratory identifiers. All excerpts are continuously available to all participating pathology laboratories, thus contributing to the quality of daily patient care. In addition, external parties may obtain permission to use data from the PALGA system, either on an ongoing basis or on the basis of a specific permission. Annually, 40 to 60 applications for permission to use PALGA data are submitted. Among external users are the Dutch cancer registry, population-based screening programs for cancer of the uterine cervix and breast cancer in The Netherlands, and individual investigators addressing a range of research questions. Many scientific papers and theses incorporating PALGA data have been published already. In conclusion, the PALGA system is a unique system that requires a minimal effort on the part of the participating laboratories, while providing them a powerful tool in their daily practices.

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Kivioja, Teemu, Anna Vähärautio, Kasper Karlsson, Martin Bonke, Sten Linnarsson i Jussi Taipale. "Counting absolute number of molecules using unique molecular identifiers". Nature Precedings, 14.04.2011. http://dx.doi.org/10.1038/npre.2011.5903.1.

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Saunders, Klay, Andrew G. Bert, B. Kate Dredge, John Toubia, Philip A. Gregory, Katherine A. Pillman, Gregory J. Goodall i Cameron P. Bracken. "Insufficiently complex unique-molecular identifiers (UMIs) distort small RNA sequencing". Scientific Reports 10, nr 1 (3.09.2020). http://dx.doi.org/10.1038/s41598-020-71323-0.

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Zhu, Tao, Keyan Liao, Rongfang Zhou, Chunjiao Xia i Weibo Xie. "ATAC-seq with unique molecular identifiers improves quantification and footprinting". Communications Biology 3, nr 1 (13.11.2020). http://dx.doi.org/10.1038/s42003-020-01403-4.

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AbstractATAC-seq (Assay for Transposase-Accessible Chromatin with high-throughput sequencing) provides an efficient way to analyze nucleosome-free regions and has been applied widely to identify transcription factor footprints. Both applications rely on the accurate quantification of insertion events of the hyperactive transposase Tn5. However, due to the presence of the PCR amplification, it is impossible to accurately distinguish independently generated identical Tn5 insertion events from PCR duplicates using the standard ATAC-seq technique. Removing PCR duplicates based on mapping coordinates introduces increasing bias towards highly accessible chromatin regions. To overcome this limitation, we establish a UMI-ATAC-seq technique by incorporating unique molecular identifiers (UMIs) into standard ATAC-seq procedures. UMI-ATAC-seq can rescue about 20% of reads that are mistaken as PCR duplicates in standard ATAC-seq in our study. We demonstrate that UMI-ATAC-seq could more accurately quantify chromatin accessibility and significantly improve the sensitivity of identifying transcription factor footprints. An analytic pipeline is developed to facilitate the application of UMI-ATAC-seq, and it is available at https://github.com/tzhu-bio/UMI-ATAC-seq.

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Philpott, Martin, Jonathan Watson, Anjan Thakurta, Tom Brown, Tom Brown, Udo Oppermann i Adam P. Cribbs. "Nanopore sequencing of single-cell transcriptomes with scCOLOR-seq". Nature Biotechnology, 1.07.2021. http://dx.doi.org/10.1038/s41587-021-00965-w.

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AbstractHere we describe single-cell corrected long-read sequencing (scCOLOR-seq), which enables error correction of barcode and unique molecular identifier oligonucleotide sequences and permits standalone cDNA nanopore sequencing of single cells. Barcodes and unique molecular identifiers are synthesized using dimeric nucleotide building blocks that allow error detection. We illustrate the use of the method for evaluating barcode assignment accuracy, differential isoform usage in myeloma cell lines, and fusion transcript detection in a sarcoma cell line.

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Crysup, Benjamin, Sammed Mandape, Jonathan L. King, Melissa Muenzler, Kapema Bupe Kapema i August E. Woerner. "Using Unique Molecular Identifiers to Improve Allele Calling in Low-Template Mixtures". Forensic Science International: Genetics, listopad 2022, 102807. http://dx.doi.org/10.1016/j.fsigen.2022.102807.

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Girardot, Charles, Jelle Scholtalbers, Sajoscha Sauer, Shu-Yi Su i Eileen E. M. Furlong. "Je, a versatile suite to handle multiplexed NGS libraries with unique molecular identifiers". BMC Bioinformatics 17, nr 1 (8.10.2016). http://dx.doi.org/10.1186/s12859-016-1284-2.

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Fields, Bryden, Sara Moeskjær, Ville‐Petri Friman, Stig U. Andersen i J. Peter W. Young. "MAUI‐seq: Metabarcoding using amplicons with unique molecular identifiers to improve error correction". Molecular Ecology Resources, 29.11.2020. http://dx.doi.org/10.1111/1755-0998.13294.

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Woerner, August E., Sammed Mandape, Jonathan L. King, Melissa Muenzler, Benjamin Crysup i Bruce Budowle. "Reducing noise and stutter in short tandem repeat loci with unique molecular identifiers". Forensic Science International: Genetics, grudzień 2020, 102459. http://dx.doi.org/10.1016/j.fsigen.2020.102459.

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Townes, F. William, i Rafael A. Irizarry. "Quantile normalization of single-cell RNA-seq read counts without unique molecular identifiers". Genome Biology 21, nr 1 (3.07.2020). http://dx.doi.org/10.1186/s13059-020-02078-0.

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