Dataset Information

ANDES: Statistical tools for the ANalyses of DEep Sequencing.

ABSTRACT: BACKGROUND:The advancements in DNA sequencing technologies have allowed researchers to progress from the analyses of a single organism towards the deep sequencing of a sample of organisms. With sufficient sequencing depth, it is now possible to detect subtle variations between members of the same species, or between mixed species with shared biomarkers, such as the 16S rRNA gene. However, traditional sequencing analyses of samples from largely homogeneous populations are often still based on multiple sequence alignments (MSA), where each sequence is placed along a separate row and similarities between aligned bases can be followed down each column. While this visual format is intuitive for a small set of aligned sequences, the representation quickly becomes cumbersome as sequencing depths cover loci hundreds or thousands of reads deep. FINDINGS:We have developed ANDES, a software library and a suite of applications, written in Perl and R, for the statistical ANalyses of DEep Sequencing. The fundamental data structure underlying ANDES is the position profile, which contains the nucleotide distributions for each genomic position resultant from a multiple sequence alignment (MSA). Tools include the root mean square deviation (RMSD) plot, which allows for the visual comparison of multiple samples on a position-by-position basis, and the computation of base conversion frequencies (transition/transversion rates), variation (Shannon entropy), inter-sample clustering and visualization (dendrogram and multidimensional scaling (MDS) plot), threshold-driven consensus sequence generation and polymorphism detection, and the estimation of empirically determined sequencing quality values. CONCLUSIONS:As new sequencing technologies evolve, deep sequencing will become increasingly cost-efficient and the inter and intra-sample comparisons of largely homogeneous sequences will become more common. We have provided a software package and demonstrated its application on various empirically-derived datasets. Investigators may download the software from Sourceforge at https://sourceforge.net/projects/andestools.

SUBMITTER: Li K

PROVIDER: S-EPMC2921379 | biostudies-literature | 2010 Jul

REPOSITORIES: biostudies-literature

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ANDES: Statistical tools for the ANalyses of DEep Sequencing.

Li Kelvin K Venter Eli E Yooseph Shibu S Stockwell Timothy B TB Eckerle Lance D LD Denison Mark R MR Spiro David J DJ Methé Barbara A BA

BMC research notes 20100715

<h4>Background</h4>The advancements in DNA sequencing technologies have allowed researchers to progress from the analyses of a single organism towards the deep sequencing of a sample of organisms. With sufficient sequencing depth, it is now possible to detect subtle variations between members of the same species, or between mixed species with shared biomarkers, such as the 16S rRNA gene. However, traditional sequencing analyses of samples from largely homogeneous populations are often still base ...[more]

PMID: 20633290

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Project description:Induced pluripotent stem cells (iPSCs) are regarded as a central tool to understand human biology in health and disease. Similarly, iPSCs from closely related species should be a central tool to understand human evolution and to identify conserved and variable patterns of iPSC disease models. Here, we have generated human, gorilla, bonobo and cynomolgus monkey iPSCs. We show that these cells are well comparable in their differentiation potential and generally similar to human, cynomolgus and rhesus monkey embryonic stem cells (ESCs). RNA sequencing reveals that expression differences among clones, individuals and stem cell type are all of very similar magnitude within a species. In contrast, expression differences between closely related primate species are three times larger and most genes show significant expression differences among the analysed species. However, pseudogenes differ more than twice as much, suggesting that evolution of expression levels in primate stem cells is rapid, but constrained. These patterns in pluripotent stem cells are comparable to those found in other tissues except testis. Hence, primate iPSCs reveal insights into general primate gene expression evolution and should provide a rich source to identify conserved and species-specific gene expression patterns for cellular phenotypes. Contributors: Leibniz Research Laboratories for Biotechnology and Artificial Organs (LEBAO), Department of Cardiothoracic, Transplantation and Vascular Surgery, Hannover Medical School, 30625 Hannover, Germany Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, D-04103 Leipzig, Germany We used expression profiling to characterize five gorilla, two bonobo and three macaque iPS clones as well as three iPS clones from two human individuals, three human embryonic stem (ES) cell lines and three macaque ES cell lines. We generated tagged RNA-Seq libraries from these 19 samples including four technical replicates (23 samples). Over 100 million single end reads were generated on the Illumina platform.

Dataset Information

ANDES: Statistical tools for the ANalyses of DEep Sequencing.

Publications

ANDES: Statistical tools for the ANalyses of DEep Sequencing.

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