Browsing by Subject "Exome sequencing"

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    Bias correction in finding copy number variation with using read depth-based methods in exome sequencing data
    (2014) Balcı, Fatma
    Medical research has striven for identifying the causes of disorders with the ultimate goal of establishing therapeutic treatments and finding cures since its early years. This aim is now becoming a reality thanks to recent developments in whole genome (WGS) and whole exome sequencing (WES). Despite the decrease in the cost of sequencing, WGS is still a very costly approach because of the need to evaluate large number of populations for more concise results. Therefore, sequencing only the protein coding regions (WES) is a more cost effective alternative. With the help of WES approach, most of the functionally important variants can be detected. Additionally, single nucleotide polymorphisms (SNPs) that are located within coding regions are the most common causes for Mendelian diseases (i.e. diseases caused by a single mutation). Moreover, WES approaches require less analysis effort compared to whole genome sequencing approaches since only 1% of whole genome is sequenced. Besides the advantages, there are also some shortcomings that need to be addressed such as biases in GC−content and probe efficiency. Although there are some previous studies on correcting GC−content related issues, there are no studies on correcting probe efficiency effect. In this thesis, we provide a formal study on the effects of both GC−content and probe efficiency on the distribution of read depth in exome sequencing data. The correction of probe efficiency will make it possible to develop new CNV discovery methods using exome sequencing data.
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    Large-scale exome sequencing study implicates both developmental and functional changes in the neurobiology of autism
    (Elsevier, 2020-02-06) Satterstrom, F. K.; Kosmicki, J. A.; Wang, J.; Breen, M. S.; De Rubeis, S.; An, J. - Y.; Peng, M.; Collins, R.; Grove, J.; Klei, L.; Stevens, C.; Reichert, J.; Mulhern, M. S.; Artomov, M.; Gerges, S.; Sheppard, B.; Xu, X.; Bhaduri, A.; Norman, Utku; Brand, H.; Schwartz, G.; Nguyen, R.; Guerrero, E. E.; Dias, C.; Autism Sequencing Consortium; iPSYCH-Broad Consortium; Betancur, C; Cook, E; Gallagher, L; Gill, M; Sutcliffe, J; Thurm, A; Zwick, M; State, M; Çicek, A. Ercüment; Talkowski, M; Cutler, D; Devlin, B.; Sanders, S; Roeder, K.; Daly, M; Buxbaum, J.
    We present the largest exome sequencing study ofautism spectrum disorder (ASD) to date (n = 35,584total samples, 11,986 with ASD). Using an enhancedanalytical framework to integratedenovoand case-control rare variation, we identify 102 risk genes at afalse discovery rate of 0.1 or less. Of these genes, 49show higher frequencies of disruptivedenovovari-ants in individuals ascertained to have severe neuro-developmental delay, whereas 53 show higher fre-quencies in individuals ascertained to have ASD;comparing ASD cases with mutations in thesegroups reveals phenotypic differences. Expressedearly in brain development, most risk genes haveroles in regulation of gene expression or neuronal communication (i.e., mutations effect neurodevelop-mental and neurophysiological changes), and 13 fallwithin loci recurrently hit by copy number variants.In cells from the human cortex, expression of riskgenes is enriched in excitatory and inhibitoryneuronal lineages, consistent with multiple paths toan excitatory-inhibitory imbalance underlying ASD.