Zitieren

Anders S., Huber W. (2010): Differential expression analysis for sequence count data. Genome Biology 11(10): R106.10.1186/gb-2010-11-10-r106Search in Google Scholar

Auer P.L., Doerge R.W. (2011): A two-stage poisson model for testing rna-seq data. Statistical Applications in Genetics and Molecular Biology 10(1).10.2202/1544-6115.1627Search in Google Scholar

Auer P.L., Srivastava S., Doerge R. (2012): Differential expression—the next generation and beyond. Briefings in Functional Genomics 11(1): 57–62.10.1093/bfgp/elr04122210853Search in Google Scholar

Benjamini Y., Hochberg Y. (1995): Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing. Journal of the Royal Statistical Society. Series B (Methodological) 57(1): 289–300.10.1111/j.2517-6161.1995.tb02031.xSearch in Google Scholar

Birney E., Stamatoyannopoulos J.A., Dutta A., Guigó R., Gingeras T.R., Margulies E.H., Weng Z., Snyder M., Dermitzakis E.T., Thurman R.E. et al. (2007): Identification and analysis of functional elements in 1% of the human genome by the encode pilot project. Nature 447(7146): 799–816.10.1038/nature05874Search in Google Scholar

Cantu D., Pearce S.P., Distelfeld A., Christiansen M.W., Uauy C., Akhunov E., Fahima T., Dubcovsky J. (2011): Effect of the down-regulation of the high Grain Protein Content (GPC) genes on the wheat transcriptome during monocarpic senescence. BMC Genomics 12(1): 492.10.1186/1471-2164-12-492320947021981858Search in Google Scholar

Frąckowiak P., Wrzesińska B., Wieczorek P., Sanchez-Bel P., Kunz L., Dittmann A., Obrępalska-Stęplowska A. (2022): Deciphering of benzothiadiazole (bth)- induced response of tomato (solanum lycopersicum l.) and its effect on early response to virus infection through the multi-omics approach. Plant and Soil pages 1–24.10.1007/s11104-022-05651-7Search in Google Scholar

Garber M., Grabherr M.G., Guttman M., Trapnell C. (2011): Computational methods for transcriptome annotation and quantification using rna-seq. Nature Methods 8(6): 469–477.10.1038/nmeth.161321623353Search in Google Scholar

Hardcastle T.J., Kelly K.A. (2010): bayseq: empirical bayesian methods for identifying differential expression in sequence count data. BMC Bioinformatics 11(1): 1–14.10.1186/1471-2105-11-422292820820698981Search in Google Scholar

Li D., Zand M.S., Dye T.D., Goniewicz M.L., Rahman I., Xie Z. (2022): An evaluation of rna-seq differential analysis methods. PLOS ONE 17(9): 1–19.10.1371/journal.pone.0264246Search in Google Scholar

Li J., Tibshirani R. (2011): Finding consistent patterns: a nonparametric approach for identifying differential expression in rna-seq data. Statistical Methods in Medical Research 22(5): 519–536.10.1177/0962280211428386Search in Google Scholar

Lin Y., Golovnina K., Chen Z.X., Lee H.N., Negron Y.L.S., Sultana H., Oliver B., Harbison S.T. (2016): Comparison of normalization and differential expression analyses using rna-seq data from 726 individual drosophila melanogaster. BMC Genomics 17(1): 1–20.10.1186/s12864-015-2353-z470232226732976Search in Google Scholar

Liu S., Wang Z., Zhu R., Wang F., Cheng Y., Liu Y. (2021): Three differential expression analysis methods for rna sequencing: limma, edger, deseq2. Journal of Visualized Experiments (175): e62528.10.3791/6252834605806Search in Google Scholar

Love M.I., Huber W., Anders S. (2014): Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biology 15(12): 550.10.1186/s13059-014-0550-8430204925516281Search in Google Scholar

Marioni J.C., Mason C.E., Mane S.M., Stephens M., Gilad Y. (2008): Rna-seq: an assessment of technical reproducibility and comparison with gene expression arrays. Genome Research 18(9): 1509–1517.10.1101/gr.079558.108252770918550803Search in Google Scholar

Martin J., Bruno V.M., Fang Z., Meng X., Blow M., Zhang T., Sherlock G., Snyder M., Wang Z. (2010): Rnnotator: an automated de novo transcriptome assembly pipeline from stranded rna-seq reads. BMC Genomics 11(1): 1–8.10.1186/1471-2164-11-663315278221106091Search in Google Scholar

Metzker M.L. (2010): Sequencing technologies—the next generation. Nature Reviews Genetics 11(1): 31–46.10.1038/nrg262619997069Search in Google Scholar

Oshlack A., Robinson M.D., Young M.D. (2010): From rna-seq reads to differential expression results. Genome Biology 11(12): 1–10.10.1186/gb-2010-11-12-220304647821176179Search in Google Scholar

Pass D.A., Sornay E., Marchbank A., Crawford M.R., Paszkiewicz K., Kent N.A., Murray J.A.H. (2017): Genome-wide chromatin mapping with size resolution reveals a dynamic sub-nucleosomal landscape in Arabidopsis. PLOS Genetics 13(9): e1006988.10.1371/journal.pgen.1006988559717628902852Search in Google Scholar

Pepke S., Wold B., Mortazavi A. (2009): Computation for chip-seq and rna-seq studies. Nature Methods 6(11): S22–S32.10.1038/nmeth.1371412105619844228Search in Google Scholar

R Core Team (2020): R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing Vienna, Austria.Search in Google Scholar

Robinson M.D., McCarthy D.J., Smyth G.K. (2010): edgeR: A Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics 26(1): 139–140.10.1093/bioinformatics/btp616279681819910308Search in Google Scholar

Robinson M.D., Oshlack A. (2010): A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biology 11(3): R25.10.1186/gb-2010-11-3-r25286456520196867Search in Google Scholar

Robinson M.D., Smyth G.K. (2008): Small-sample estimation of negative binomial dispersion, with applications to SAGE data. Biostatistics 9(2): 321–332.10.1093/biostatistics/kxm030Search in Google Scholar

Sanger F., Coulson A.R. (1975): A rapid method for determining sequences in dna by primed synthesis with dna polymerase. Journal of Molecular Biology 94(3): 441–448.10.1016/0022-2836(75)90213-21100841Search in Google Scholar

Sanger F., Nicklen S., Coulson A.R. (1977): Dna sequencing with chain-terminating inhibitors. Proceedings of the National Academy of Sciences 74(12): 5463–5467.10.1073/pnas.74.12.5463431765271968Search in Google Scholar

Shahjaman M., Manir Hossain Mollah M., Rezanur Rahman M., Islam S.S., Nurul Haque Mollah M. (2020): Robust identification of differentially expressed genes from rna-seq data. Genomics 112(2): 2000–2010.10.1016/j.ygeno.2019.11.01231756426Search in Google Scholar

Van Vliet A.H. (2010): Next generation sequencing of microbial transcriptomes: challenges and opportunities. FEMS Microbiology Letters 302(1): 1–7.10.1111/j.1574-6968.2009.01767.x19735299Search in Google Scholar

Wang Z., Gerstein M., Snyder M. (2009): Rna-seq: a revolutionary tool for transcriptomics. Nature Reviews Genetics 10(1): 57–63.10.1038/nrg2484294928019015660Search in Google Scholar

Wielkopolan B., Frąckowiak P., Wieczorek P., Obrępalska-Stęplowska A. (2022): The Impact of Oulema melanopus—Associated Bacteria on the Wheat Defense Response to the Feeding of Their Insect Hosts. Cells 11(15): 2342.10.3390/cells11152342936762535954184Search in Google Scholar

eISSN:
2199-577X
Sprache:
Englisch
Zeitrahmen der Veröffentlichung:
2 Hefte pro Jahr
Fachgebiete der Zeitschrift:
Biologie, Bioinformatik, andere, Mathematik, Wahrscheinlichkeitstheorie und Statistik, Angewandte Mathematik