| 1. |
- Bengtsson-Palme, Johan, 1985, et al.
(författare)
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Strategies to improve usability and preserve accuracy in biological sequence databases
- 2016
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Ingår i: Proteomics. - : Wiley. - 1615-9853 .- 1615-9861. ; 16:18, s. 2454-2460
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Tidskriftsartikel (refereegranskat)abstract
- Biology is increasingly dependent on large-scale analysis, such as proteomics, creating a requirement for efficient bioinformatics. Bioinformatic predictions of biological functions rely upon correctly annotated database sequences, and the presence of inaccurately annotated or otherwise poorly described sequences introduces noise and bias to biological analyses. Accurate annotations are, for example, pivotal for correct identifications of polypeptide fragments. However, standards for how sequence databases are organized and presented are currently insufficient. Here, we propose five strategies to address fundamental issues in the annotation of sequence databases: (i) to clearly separate experimentally verified and unverified sequence entries; (ii) to enable a system for tracing the origins of annotations; (iii) to separate entries with high-quality, informative annotation from less useful ones; (iv) to integrate automated quality-control software whenever such tools exist; and (v) to facilitate post-submission editing of annotations and metadata associated with sequences. We believe that implementation of these strategies, for example as requirements for publication of database papers, would enable biology to better take advantage of large-scale data.
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| 2. |
- Wilzén, Annica, et al.
(författare)
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Malignant pheochromocytomas/paragangliomas harbor mutations in transport and cell adhesion genes.
- 2016
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Ingår i: International Journal of Cancer. - : Wiley. - 0020-7136 .- 1097-0215. ; 138:9, s. 2201-11
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Tidskriftsartikel (refereegranskat)abstract
- One out of ten patients with pheochromocytoma (PCC) and paraganglioma (PGL) develop malignant disease. Today there are no reliable pathological methods to predict malignancy at the time of diagnosis. Tumors harboring mutations in the succinate dehydrogenase subunit B (SDHB) gene often metastasize but the sequential genetic events resulting in malignant progression are not fully understood. The aim of this study was to identify somatic mutations that contribute to the malignant transformation of PCC/PGL. We performed pair-wise (tumor-normal) whole-exome sequencing to analyze the somatic mutational landscape in five malignant and four benign primary PCC/sympathetic PGL (sPGL), including two biological replicates from each specimen. In total, 225 unique somatic mutations were identified in 215 genes, with an average mutation rate of 0.54 mutations/megabase. Malignant tumors had a significantly higher number of mutations compared to benign tumors (p
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| 3. |
- Rehammar, Anna, 1978
(författare)
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Statistical assessment of somatic mutations and genomic variability using DNA sequence data
- 2016
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- The development of new DNA sequencing techniques have made it possible to generate high-resolution genomic data at an unprecedented pace. However, the high dimensionality in combination with the substantial levels of technical errors and biological variability make the analysis challenging. Tailored statistical methods need therefore to be developed and applied in order to facilitate correct biological interpretation. The first two papers in this thesis are focused on finding tumor-specific (somatic) mutations in cancer, while in the third paper a new method to assess genomic variability in microbial communities is developed. In paper I, the aim was to characterize somatic mutations in pheochromocytoma/paraganglioma, and to identify mutations that contribute to malignancy. Statistical analysis of exome sequencing data from nine replicated paired normal--tumor samples revealed 225 unique somatic mutations. A significantly higher rate of mutations was found in malignant compared to benign tumors. In addition, three genes with recurrent somatic mutations, exclusively located in malignant tumors, were identified. In paper II, exome sequencing data was used to detect somatic mutations in 17 patients with acute myeloid leukemia. The identified mutations were evaluated as markers in a more sensitive analysis of remaining cancer cell levels after treatment. All but one of the studied patients were found to have potential markers in their somatic mutation profiles. In paper III, a hierarchical Bayesian model for detecting genetic differences on nucleotide level between groups of microbial communities is proposed. The model is based on a Dirichlet-multinomial distribution and takes both within- and between-sample variability into account. The evaluation of the performance show that the model has a high sensitivity and maintains a low false positive rate even when the between-sample variability is high. The thesis demonstrates the importance of dedicated statistical analysis and understanding of the error structure in DNA sequence data, in order to assure accurate identification of mutations and differences in genomic variability.
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