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

ACCESS DATA

Publications

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

Similar Datasets

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.

Project description:BackgroundThe sequencing platform BGISEQ-500 is based on DNBSEQ technology and provides high throughput with low costs. This sequencer has been widely used in various areas of scientific and clinical research. A better understanding of the sequencing process and performance of this system is essential for stabilizing the sequencing process, accurately interpreting sequencing results and efficiently solving sequencing problems. To address these concerns, a comprehensive database, SEQdata-BEACON, was constructed to accumulate the run performance data in BGISEQ-500.ResultsA total of 60 BGISEQ-500 instruments in the BGI-Wuhan lab were used to collect sequencing performance data. Lanes in paired-end 100 (PE100) sequencing using 10 bp barcode were chosen, and each lane was assigned a unique entry number as its identification number (ID). From November 2018 to April 2019, 2236 entries were recorded in the database containing 65 metrics about sample, yield, quality, machine state and supplies information. Using a correlation matrix, 52 numerical metrics were clustered into three groups signifying yield-quality, machine state and sequencing calibration. The distributions of the metrics also delivered information about patterns and rendered clues for further explanation or analysis of the sequencing process. Using the data of a total of 200 cycles, a linear regression model well simulated the final outputs. Moreover, the predicted final yield could be provided in the 15th cycle of the early stage of sequencing, and the corresponding R2 of the 200th and 15th cycle models were 0.97 and 0.81, respectively. The model was run with the test sets obtained from May 2019 to predict the yield, which resulted in an R2 of 0.96. These results indicate that our simulation model was reliable and effective.ConclusionsData sources, statistical findings and application tools provide a constantly updated reference for BGISEQ-500 users to comprehensively understand DNBSEQ technology, solve sequencing problems and optimize run performance. These resources are available on our website http://seqBEACON.genomics.cn:443/home.html.

Dataset Information

ANDES: Statistical tools for the ANalyses of DEep Sequencing.

Publications

ANDES: Statistical tools for the ANalyses of DEep Sequencing.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets