The ability to decipher the genetic code of different species would lead to significant future scientific achievements in important areas, including medicine and agriculture. The importance of DNA sequencing necessita...The ability to decipher the genetic code of different species would lead to significant future scientific achievements in important areas, including medicine and agriculture. The importance of DNA sequencing necessitated a need for efficient automation of identification of base sequences from traces generated by existing sequencing machines, a process referred to as DNA base-calling. In this paper, a pattern recognition technique was adopted to minimize the inaccuracy in DNA base-calling. Two new frameworks using Artificial Neural Networks and Polynomial Classifiers are proposed to model electropherogram traces belonging to Homo sapiens, Saccharomyces mikatae and Drosophila melanogaster. De-correlation, de-convolution and normalization were implemented as part of the pre-processing stage employed to minimize data imperfections attributed to the nature of the chemical reactions involved in DNA sequencing. Discriminative features that characterize each chromatogram trace were subsequently extracted and subjected to the chosen classifiers to categorize the events to their respective base classes. The models are trained such that they are not restricted to a specific species or to a specific chemical procedure of sequencing. The base- calling accuracy achieved is compared with the exist- ing standards, PHRED (Phil’s Read Editor) and ABI (Applied Biosystems, version2.1.1) KB base-callers in terms of deletion, insertion and substitution errors. Experimental evidence indicates that the proposed models achieve a higher base-calling accuracy when compared to PHRED and a comparable performance when compared to ABI. The results obtained demon- strate the potential of the proposed models for efficient and accurate DNA base-calling.展开更多
Human identification using forensic DNA profiling has made enormous advancement over the past two‑and‑half decades.Forensic DNA profiling provides enormous genetic data from a variety of biological materials and indiv...Human identification using forensic DNA profiling has made enormous advancement over the past two‑and‑half decades.Forensic DNA profiling provides enormous genetic data from a variety of biological materials and individualsto help solve many important criminal and civil cases that confront society.Under certain environmental conditions,the total deterioration of soft-tissue leaves skeletal remains as the only available sample for DNA testing to identify missing persons,victims of natural disasters,or exonerate suspect(s)in a criminal case.We report the findings of a case involving the human remains of a missing person submitted to the Forensic Science Laboratory of the Ghana Police Service for forensic DNA profiling in comparison to an alleged living relative of the deceased.DNA from the femur bone and buccal swabs of alleged relative of the deceased were extracted,quantified,and short tandem repeat(STR)profiled using Qiagen’s Investigator kit,Applied Biosystem’s Quantifiler trio,and GlobalFiler kits.Full STR profiles were generated for both the femur bone from the salty environment and the buccal swabs from the alleged relative.The femur bone was genetically identified to be that of the missing person.The remains were thus handed over to the relatives for final funeral rites and burial to bring closure to the long search for the missing person.展开更多
文摘The ability to decipher the genetic code of different species would lead to significant future scientific achievements in important areas, including medicine and agriculture. The importance of DNA sequencing necessitated a need for efficient automation of identification of base sequences from traces generated by existing sequencing machines, a process referred to as DNA base-calling. In this paper, a pattern recognition technique was adopted to minimize the inaccuracy in DNA base-calling. Two new frameworks using Artificial Neural Networks and Polynomial Classifiers are proposed to model electropherogram traces belonging to Homo sapiens, Saccharomyces mikatae and Drosophila melanogaster. De-correlation, de-convolution and normalization were implemented as part of the pre-processing stage employed to minimize data imperfections attributed to the nature of the chemical reactions involved in DNA sequencing. Discriminative features that characterize each chromatogram trace were subsequently extracted and subjected to the chosen classifiers to categorize the events to their respective base classes. The models are trained such that they are not restricted to a specific species or to a specific chemical procedure of sequencing. The base- calling accuracy achieved is compared with the exist- ing standards, PHRED (Phil’s Read Editor) and ABI (Applied Biosystems, version2.1.1) KB base-callers in terms of deletion, insertion and substitution errors. Experimental evidence indicates that the proposed models achieve a higher base-calling accuracy when compared to PHRED and a comparable performance when compared to ABI. The results obtained demon- strate the potential of the proposed models for efficient and accurate DNA base-calling.
文摘Human identification using forensic DNA profiling has made enormous advancement over the past two‑and‑half decades.Forensic DNA profiling provides enormous genetic data from a variety of biological materials and individualsto help solve many important criminal and civil cases that confront society.Under certain environmental conditions,the total deterioration of soft-tissue leaves skeletal remains as the only available sample for DNA testing to identify missing persons,victims of natural disasters,or exonerate suspect(s)in a criminal case.We report the findings of a case involving the human remains of a missing person submitted to the Forensic Science Laboratory of the Ghana Police Service for forensic DNA profiling in comparison to an alleged living relative of the deceased.DNA from the femur bone and buccal swabs of alleged relative of the deceased were extracted,quantified,and short tandem repeat(STR)profiled using Qiagen’s Investigator kit,Applied Biosystem’s Quantifiler trio,and GlobalFiler kits.Full STR profiles were generated for both the femur bone from the salty environment and the buccal swabs from the alleged relative.The femur bone was genetically identified to be that of the missing person.The remains were thus handed over to the relatives for final funeral rites and burial to bring closure to the long search for the missing person.
