small RNA-seq

Download BIB format:


  • Tsuji J, Weng Z. (2016) DNApi: A De Novo Adapter Prediction Algorithm for Small RNA Sequencing Data. 11(10):e0164228.
  • Andrews, S. (2010). FastQC: A quality control tool for high throughput sequence data. Bioinformatics. doi:citeulike-article-id:11583827
  • Martin, M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, 17(1), 10. doi:10.14806/ej.17.1.200
  • Dale, R. K., Pedersen, B. S., & Quinlan, A. R. (2011). Pybedtools: A flexible Python library for manipulating genomic datasets and annotations. Bioinformatics, 27(24), 3423–3424. doi:10.1093/bioinformatics/btr539
  • Quinlan, A. R., & Hall, I. M. (2010). BEDTools: A flexible suite of utilities for comparing genomic features. Bioinformatics, 26(6), 841–842. doi:10.1093/bioinformatics/btq033
  • Tarasov, A., Vilella, A. J., Cuppen, E., Nijman, I. J., & Prins, P. (2015). Sambamba: Fast processing of NGS alignment formats. Bioinformatics, 31(12), 2032–2034. doi:10.1093/bioinformatics/btv098
  • Heger, A. (2009). Pysam. Retrieved from
  • Li, H. (2011). A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics, 27(21), 2987–2993. doi:10.1093/bioinformatics/btr509
  • Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., … Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics, 25(16), 2078–2079. doi:10.1093/bioinformatics/btp352
  • Pantano, L., Estivill, X., & Martí, E. (2010). SeqBuster, a bioinformatic tool for the processing and analysis of small RNAs datasets, reveals ubiquitous miRNA modifications in human embryonic cells. Nucleic Acids Research, 38(5), e34. Retrieved from
  • Pantano, L., Friedlander, M. R., Escaramis, G., Lizano, E., Pallares-Albanell, J., Ferrer, I., … Marti, E. (2015). Specific small-RNA signatures in the amygdala at premotor and motor stages of Parkinson’s disease revealed by deep sequencing analysis. Bioinformatics (Oxford, England). doi:10.1093/bioinformatics/btv632

For the alignment, add what you have used:

  • Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., … Gingeras, T. R. (2013). STAR: Ultrafast universal RNA-seq aligner. Bioinformatics, 29(1), 15–21. doi:10.1093/bioinformatics/bts635
  • Langmead, B., Trapnell, C., Pop, M., & Salzberg, S. L. (2009). Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol, 10, R25. doi:10.1186/gb-2009-10-3-r25

If you have in the output novel miRNA discovering, add:

  • Friedlander, M. R., MacKowiak, S. D., Li, N., Chen, W., & Rajewsky, N. (2012). MiRDeep2 accurately identifies known and hundreds of novel microRNA genes in seven animal clades. Nucleic Acids Research, 40(1), 37–52. doi:10.1093/nar/gkr688

If you have tRNA mapping output, add:

  • Selitsky, S. R., & Sethupathy, P. (2015). tDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing data. BMC Bioinformatics, 16(1), 354. doi:10.1186/s12859-015-0800-0


  • Griffiths-Jones, S. (2004). The microRNA Registry. Nucleic Acids Research, 32(Database issue), D109–11. doi:10.1093/nar/gkh023
  • Griffiths-Jones, S. (2006). miRBase: the microRNA sequence database. Methods in Molecular Biology (Clifton, N.J.), 342, 129–38. doi:10.1385/1-59745-123-1:129
  • Griffiths-Jones, S., Saini, H. K., Van Dongen, S., & Enright, A. J. (2008). miRBase: Tools for microRNA genomics. Nucleic Acids Research, 36(SUPPL. 1). doi:10.1093/nar/gkm952
  • Kozomara, A., & Griffiths-Jones, S. (2011). MiRBase: Integrating microRNA annotation and deep-sequencing data. Nucleic Acids Research, 39(SUPPL. 1). doi:10.1093/nar/gkq1027
  • Kozomara, A., & Griffiths-Jones, S. (2014). MiRBase: Annotating high confidence microRNAs using deep sequencing data. Nucleic Acids Research, 42(D1). doi:10.1093/nar/gkt1181