https://hdl.handle.net/10481/32290 2026-04-13T20:54:30Z https://hdl.handle.net/10481/111304 Prediction of CpG Islands as an Intrinsic Clustering Property Found in Many Eukaryotic DNA Sequences and Its Relation to DNA Methylation Gómez Martín, Cristina; Lebrón, Ricardo; Oliver Jiménez, José Lutgardo; Hackenberg, Michael The promoter region of around 70% of all genes in the human genome is overlapped by a CpG island (CGI). CGIs have known functions in the transcription initiation and outstanding compositional features like high GþC content and CpG ratios when compared to the bulk DNA. We have shown before that CGIs manifest as clusters of CpGs in mammalian genomes and can therefore be detected using clustering methods. These techniques have several advantages over sliding window approaches which apply compositional properties as thresholds. In this protocol we show how to determine local (CpG islands) and global (distance distribution) clustering properties of CG dinucleotides and how to generalize this analysis to any k-mer or combinations of it. In addition, we illustrate how to easily cross the output of a CpG island prediction algorithm with our methylation database to detect differentially methylated CGIs. The analysis is given in a step-by-step protocol and all necessary programs are implemented into a virtual machine or, alternatively, the software can be downloaded and easily installed. https://hdl.handle.net/10481/111211 sRNAtoolboxVM: Small RNA Analysis in a Virtual Machine Gómez Martín, Cristina; Lebrón, Ricardo; Rueda, Antonio; Oliver Jiménez, José Lutgardo; Hackenberg, Michael High-throughput sequencing (HTS) data for small RNAs (noncoding RNA molecules that are 20–250 nucleotides in length) can now be routinely generated by minimally equipped wet laboratories; however, the bottleneck in HTS-based research has shifted now to the analysis of such huge amount of data. One of the reasons is that many analysis types require a Linux environment but computers, system administrators, and bioinformaticians suppose additional costs that often cannot be afforded by small to mid-sized groups or laboratories. Web servers are an alternative that can be used if the data is not subjected to privacy issues (what very often is an important issue with medical data). However, in any case they are less flexible than stand-alone programs limiting the number of workflows and analysis types that can be carried out. We show in this protocol how virtual machines can be used to overcome those problems and limitations. sRNAtoolboxVM is a virtual machine that can be executed on all common operating systems through virtualization programs like VirtualBox or VMware, providing the user with a high number of preinstalled programs like sRNAbench for small RNA analysis without the need to maintain additional servers and/or operating systems. https://hdl.handle.net/10481/32291 DNA methylation profiling from high-throughput sequencing data Hackenberg , Michael; Barturen, Guillermo; Oliver, José Luis In this chapter we will review the common steps in the analysis of whole genome singlebase-pair resolution methylation data including the pre-processing of the reads, the alignment and the read out of the methylation information of individual cytosines. We will specially focus on the possible error sources which need to be taken into account in order to generate high quality methylation maps. Several tools have been already developed to convert the sequencing data into knowledge about the methylation levels. We will review the most used tools discussing both technical aspects like user-friendliness and speed, but also biologically relevant questions as the quality control. For one of these tools, NGSmethPipe, we will give a step by step tutorial including installation and methylation profiling for different data types and species. We will conclude the chapter with a brief discussion of NGSmethDB, a database for the storage of single-base resolution methylation maps that can be used to further analyze the obtained methylation maps.