Teresa Webster, Bioinformatics, Affymetrix.Automated clustering and calling of ""Off-Target Variants,"" atypical cluster patterns caused by secondary variants in the probe hybridization region.
Best practices for genotyping analysis of plant and animal genomes with Affym...Affymetrix
This document describes best practices for analyzing genotyping data from Affymetrix Axiom arrays for plant and animal genomes. It discusses an analysis workflow that combines standard practices for human genotyping with new steps tailored to complex non-human genomes. The workflow uses the SNPolisher R package to generate quality control metrics, classify SNPs, visualize clusters, and identify off-target variants. The overall goal is to maximize high-quality genotype calls while flagging SNPs that require further examination.
This document discusses how microarrays and RNA sequencing (RNA-Seq) are complementary approaches for genomics research. It notes that while RNA-Seq is useful for discovering unknown transcripts, microarrays allow researchers to quickly and cost-effectively profile known pathways and genes. The document also highlights how microarrays can generate data from limited or degraded RNA samples not amenable to RNA-Seq, and can validate potential RNA-Seq hits simultaneously. It concludes by emphasizing the robust, cost-effective, and proven nature of microarray technology as a complement to emerging NGS approaches.
This document provides a summary of a training seminar on the use of molecular markers in apple and peach breeding. The one-day seminar will cover topics including sampling procedures, utilizing markers for parental selection and hybrid selection in various breeding programs, markers available for different traits, and cost comparisons. Speakers will discuss examples from breeding programs at IRTA, Agroscope, FEM, and INRA. The afternoon will focus on the FruitBreedomics molecular breeding services and interface. The seminar aims to demonstrate how molecular markers can help breeders in tasks such as selecting for disease resistance, fruit quality traits, and verifying pedigrees.
A systematic, data driven approach to the combined analysis of microarray and...Laurence Dawkins-Hall
The use of gene expression data from Micro arrays coupled with WT QTL's linked to Tryp resistance phenotypes in Cattle to elucidate pertinent genetic changes underpinning phenotype in putative candidate genes
A choice of population-optimized GWAS imputation grids, combined with exome, loss-of-function, ADME, and eQTL markers in one high-coverage, high-value, customizable design.
This document discusses NIST's work in developing genomic reference materials and methods to evaluate microbial genomics measurements. It describes three projects: 1) assessing genomic purity by detecting low levels of contaminants using sequencing and classification, 2) evaluating SNP calling methods using reference materials and replicates to establish confidence, and 3) developing characterized genomic reference materials for public health pathogens. The overall aim is to build an infrastructure to support genome-based characterization of microbial samples.
Best practices for genotyping analysis of plant and animal genomes with Affym...Affymetrix
This document describes best practices for analyzing genotyping data from Affymetrix Axiom arrays for plant and animal genomes. It discusses an analysis workflow that combines standard practices for human genotyping with new steps tailored to complex non-human genomes. The workflow uses the SNPolisher R package to generate quality control metrics, classify SNPs, visualize clusters, and identify off-target variants. The overall goal is to maximize high-quality genotype calls while flagging SNPs that require further examination.
This document discusses how microarrays and RNA sequencing (RNA-Seq) are complementary approaches for genomics research. It notes that while RNA-Seq is useful for discovering unknown transcripts, microarrays allow researchers to quickly and cost-effectively profile known pathways and genes. The document also highlights how microarrays can generate data from limited or degraded RNA samples not amenable to RNA-Seq, and can validate potential RNA-Seq hits simultaneously. It concludes by emphasizing the robust, cost-effective, and proven nature of microarray technology as a complement to emerging NGS approaches.
This document provides a summary of a training seminar on the use of molecular markers in apple and peach breeding. The one-day seminar will cover topics including sampling procedures, utilizing markers for parental selection and hybrid selection in various breeding programs, markers available for different traits, and cost comparisons. Speakers will discuss examples from breeding programs at IRTA, Agroscope, FEM, and INRA. The afternoon will focus on the FruitBreedomics molecular breeding services and interface. The seminar aims to demonstrate how molecular markers can help breeders in tasks such as selecting for disease resistance, fruit quality traits, and verifying pedigrees.
A systematic, data driven approach to the combined analysis of microarray and...Laurence Dawkins-Hall
The use of gene expression data from Micro arrays coupled with WT QTL's linked to Tryp resistance phenotypes in Cattle to elucidate pertinent genetic changes underpinning phenotype in putative candidate genes
A choice of population-optimized GWAS imputation grids, combined with exome, loss-of-function, ADME, and eQTL markers in one high-coverage, high-value, customizable design.
This document discusses NIST's work in developing genomic reference materials and methods to evaluate microbial genomics measurements. It describes three projects: 1) assessing genomic purity by detecting low levels of contaminants using sequencing and classification, 2) evaluating SNP calling methods using reference materials and replicates to establish confidence, and 3) developing characterized genomic reference materials for public health pathogens. The overall aim is to build an infrastructure to support genome-based characterization of microbial samples.
This document provides an overview of the use of molecular markers in plant breeding and crop improvement. It discusses different types of genetic markers including morphological, biochemical, and DNA markers. DNA markers such as RFLPs, AFLPs, RAPDs, SSRs, and SNPs are now widely used due to their abundance. Molecular markers can be used to construct linkage maps, assess genetic diversity, identify cultivars, and facilitate marker-assisted selection by breeders to transfer genes controlling important traits from one plant variety to another. The document highlights several examples of genes for traits like disease resistance being tagged and mapped using molecular markers to accelerate plant breeding efforts.
Marker assisted selection (MAS) uses DNA markers linked to traits of interest to assist plant breeders in selecting desirable plants. MAS can increase the efficiency and precision of plant breeding by allowing selection at early generations or at the seedling stage before phenotypic selection. It also reduces the influence of environmental effects and allows selection of homozygous plants. While MAS has advantages over conventional breeding, its use in actual breeding programs remains limited due to technical and cost constraints. Further optimization and integration of molecular genetics with plant breeding is needed to fully realize the potential of MAS.
Marker assisted selection for complex traits in agricultural cropsAparna Veluru
Marker-assisted selection (MAS) uses DNA markers linked to traits of interest to assist plant breeders in selecting desirable plants. MAS has advantages over phenotypic selection like enabling selection at early stages. MAS breeding schemes include marker-assisted backcrossing to introgress traits while minimizing linkage drag, and pyramiding to combine multiple genes/QTLs. Case studies demonstrate using MAS to develop rice varieties with submergence tolerance and improve yield traits. However, limitations include inconsistent QTL-marker associations across environments and difficulties evaluating complex trait genetics like epistasis. Future work aims to optimize MAS efficiency and integration with plant breeding.
This presentation discusses marker assisted selection (MAS) for herbicide resistance. MAS uses DNA markers linked to target genes to predict phenotypes, allowing selection earlier than phenotypic screening. The presentation provides advantages of MAS like simpler screening and selection at seedling stage. A case study of MAS for herbicide resistance in sunflower is described, where different markers like SSRs, CAPS and SNPs were developed for alleles conferring resistance. Transgenic approaches for herbicide resistance using selectable marker genes like pat/bar for phosphinothricin and epsps/aroA for glyphosate resistance are also summarized.
The document describes the development of a QTL map for Egyptian durum wheat using an F2 mapping population derived from a cross between two parental varieties, Baniswif-1 and Souhag-2. A variety of DNA markers including SSRs, RAPDs, AFLPs, ESTs and SCoTs were used to genotype the mapping population. Traits related to yield and drought tolerance such as root length, plant height, spike characteristics, and biomass were measured. Linkage analysis was performed to construct a genetic linkage map, which was then used to detect QTLs associated with the traits of interest.
This document summarizes three case studies on using marker-assisted breeding techniques:
1) Introgressing rice QTLs controlling root traits from donor Azucena into recipient Kalinga III. Five target QTLs were introgressed over three backcrosses using foreground, background, and recombinant selection with RFLPs and SSRs.
2) Introgressing the submergence tolerance Sub1 QTL from donor IR49830 into popular rice variety Swarna. The QTL was introgressed over three backcrosses and a BC3F2 line identified with minimal donor DNA.
3) Introgressing drought tolerance QTLs from donor CML247 into
The document discusses marker-assisted breeding and the services provided by the Sequencing and Genotyping Platform. It outlines the steps in marker-assisted selection, from laying out seedlings and collecting samples to running analyses. It also lists the facilities and equipment available, including robotic platforms for liquid handling and DNA/RNA extraction, real-time PCR systems, capillary sequencers, and Illumina platforms for high-throughput genotyping. The platform provides support for marker-assisted breeding programs through services like whole genome sequencing, targeted resequencing, and protocol development for next-generation sequencing applications.
Genomic gene expression changes resulting from Trypanosomiasis: a horizontal study Examining expression changes elucidated by micro arrays in seminal tissues associated with the pathophysiology of Trypanosomiasis during disease progression
IRJET- Analysis of Hybrid Purity in Watermelon using Microsatellite Marker in...IRJET Journal
This document analyzes the genetic purity of a watermelon hybrid variety ("CL-Hy-01") using microsatellite markers, and compares it to an analysis using field grow-out tests. One polymorphic microsatellite marker ("WMU4702") was identified that distinguished the two parental inbred lines. Analysis of 98 F1 hybrid seeds using this marker found 96.9% genetic purity. A field grow-out test of 100 F1 seeds found 97% purity based on morphological traits. The results of the microsatellite and field tests were comparable, demonstrating that microsatellite analysis can accurately assess hybrid purity in a shorter time than conventional field testing.
Genetics, structure, and prevalence of FP967 T-DNA in flaxJamille McLeod
The document summarizes research into the genetics, structure, and prevalence of the FP967 (CDC Triffid) T-DNA found in genetically modified flax. Key points:
- The FP967 T-DNA is thought to be inserted at a single locus in the flax genome. Quantitative PCR assays were developed to test this.
- The FP967 T-DNA was found at low levels (0.01-0.1%) in some breeder seed lots from 2009-2010 but was not detected in lines selected for advancement in the flax breeding program in 2010-2011.
- Cloning and sequencing of the FP967 T-DNA revealed an internal 3,720 bp duplication between
Marker assisted selection( mas) and its application in plant breedingHemantkumar Sonawane
Marker Types,Prerequisites for efficient marker-assisted breeding programmes,Advantages of MAS,Limitations of MAS ,Marker Assisted Breeding Schemes,• 1. Marker- assisted backcrossing,2. Marker- Assisted evaluation of breeding material,3 Gene pyramiding,4. Early generation selection ,Combined approaches,MAB: I level of Selection – FOREGROUND SELECTION,Second level of selection: Recombinant Selection,MAB: III Level of Selection BACKGROUND SELECTION,
MARKER-ASSISTED BREEDING FOR RICE IMPROVEMENTFOODCROPS
This document discusses marker-assisted breeding for rice improvement. It begins with an outline of the topics to be covered, which include the theory and practice of marker-assisted selection, marker-assisted breeding schemes, and a case study of marker-assisted backcrossing done at IRRI. The first section defines marker-assisted selection and describes its advantages over phenotypic selection, such as earlier selection and greater reliability. Subsequent sections discuss specific marker-assisted breeding schemes like backcrossing, pyramiding traits, and early generation selection. The document concludes with details of IRRI's case study using markers to backcross a submergence tolerance gene into popular rice varieties.
Systemic analysis of data combined from genetic qtl's and gene expression dat...Laurence Dawkins-Hall
Elucidating changes in gene expression by Micro array genomic sweeps of genetic QTLs linked to Tryp resistance in WT cattle to identify putative candidates underpinning pathophysiology
Trophectoderm dna fingerprinting by quantitative real time pcr successfully d...t7260678
This study validated a novel method of quantitative real-time PCR (qPCR) to distinguish sibling human embryos using DNA fingerprinting of trophectoderm biopsies. The study analyzed cell lines and excess DNA from trophectoderm biopsies of sibling human blastocysts using qPCR of 40 SNPs. Results showed the method accurately assigned relationship between samples, with sibling relationships averaging 57.2% similarity compared to 95.1% for self relationships. This qPCR-based DNA fingerprinting technique can unequivocally discriminate between sibling human embryos and will enable research on markers of embryonic reproductive potential.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
Identification and verification of QTL associated with frost tolerance using ...PGS
This lecture was a part of Plant Genetics Seminars - PGS 2017/2018 at Assiut University. These seminars organized by Dr. Ahmed Sallam, Department of Genetics, Faculty of Agriculture, Assiut University
Abstract
Frost stress is one of the abiotic stresses that causes a significant reduction in winter faba bean yield in Europe. The main objective of this work is to genetically improve frost tolerance in winter faba bean by identifying and validating QTL associated with frost tolerance to be used in marker-assisted selection (MAS). Two different genetic backgrounds were used: a biparental population (BPP) consisting of 101 inbred lines, and 189 genotypes from single seed descent (SSD) from the Gottingen Winter bean Population (GWBP). All experiments were conducted in a frost growth chamber under controlled conditions. The symptoms of frost stress were scored. In addition, leaf fatty acid composition (FAC) was analyzed as a physiological trait in both populations. Five common QTLs for frost tolerance and FAC were found in both populations. Moreover, synteny analysis between Medicago truncatula (a model legume) and faba bean genomes was performed to identify candidate genes for the validated QTLs.
This is a lecture for Bio4025, a graduate class at Washington University in St. Louis. Some slides are derived from Julin Maloof (University of California, Davis), some of which were altered.
This document discusses the use of DNA markers and microsatellite markers (SSRs) to identify plant varieties and assess the genetic purity of hybrid seeds. [1] SSR markers were able to differentiate parental lines of 5 rice hybrids. [2] The SSR marker RM234 identified a single off-type seed (2% impurity) in a sample of CORH3 hybrid seeds. [3] SSR markers allow for reliable, reproducible, and cost-effective identification of plant varieties and assessment of seed purity compared to other marker techniques.
The document describes the development of a focused microarray to assess dopaminergic and glial cell differentiation derived from human stem cells. Specifically:
1) Researchers designed a microarray of 281 genes to detect markers of dopaminergic neurons, oligodendrocytes, astrocytes, embryonic stem cells, and progenitor cells.
2) They validated that the microarray could distinguish RNA samples from human adult brain, embryonic stem cells, and neural stem cells based on gene expression patterns.
3) As an application, they used the microarray to monitor differentiation of human embryonal carcinoma stem cells toward dopaminergic neurons and found it could distinguish differentiation stages and cell purity.
The document describes a study that aimed to validate insertions and deletions (INDELs) identified in the Genome in a Bottle (GIAB) reference standard by comparing calls made by FreeBayes and GATK variant callers. Researchers analyzed sequencing data from the NA12878 genome using the two callers and GIAB, generating 7 variant lists. They selected 150 random INDELs from each list and designed primers to amplify the regions, then validated the variants using MiSeq sequencing. The results helped improve understanding of the variant callers and the GIAB standard for INDEL calls.
A Novel High Accuracy Algorithm for Reference Assembly in Colour SpaceCSCJournals
Although numerous algorithms exist for genome alignment using Next Generation Sequencing tags, assembly of colour coded reads remains a challenge. We present a novel pairwise sequence aligner algorithm derived from Smith-Waterman method. Original feature of the algorithm is that it translates the reference sequence into colour code and performs the alignment in colour space. While operating on this base it can prevent most read error-derived assembly errors. Based on dynamic programming it gives the optimal alignment in colour space. Further, validation on empirical dataset with capillary sequencing proved high mapping accuracy. The algorithm can be implemented into any reference assembly software thereby improving mapping accuracy while maintaining high speed mapping.
This document provides an overview of the use of molecular markers in plant breeding and crop improvement. It discusses different types of genetic markers including morphological, biochemical, and DNA markers. DNA markers such as RFLPs, AFLPs, RAPDs, SSRs, and SNPs are now widely used due to their abundance. Molecular markers can be used to construct linkage maps, assess genetic diversity, identify cultivars, and facilitate marker-assisted selection by breeders to transfer genes controlling important traits from one plant variety to another. The document highlights several examples of genes for traits like disease resistance being tagged and mapped using molecular markers to accelerate plant breeding efforts.
Marker assisted selection (MAS) uses DNA markers linked to traits of interest to assist plant breeders in selecting desirable plants. MAS can increase the efficiency and precision of plant breeding by allowing selection at early generations or at the seedling stage before phenotypic selection. It also reduces the influence of environmental effects and allows selection of homozygous plants. While MAS has advantages over conventional breeding, its use in actual breeding programs remains limited due to technical and cost constraints. Further optimization and integration of molecular genetics with plant breeding is needed to fully realize the potential of MAS.
Marker assisted selection for complex traits in agricultural cropsAparna Veluru
Marker-assisted selection (MAS) uses DNA markers linked to traits of interest to assist plant breeders in selecting desirable plants. MAS has advantages over phenotypic selection like enabling selection at early stages. MAS breeding schemes include marker-assisted backcrossing to introgress traits while minimizing linkage drag, and pyramiding to combine multiple genes/QTLs. Case studies demonstrate using MAS to develop rice varieties with submergence tolerance and improve yield traits. However, limitations include inconsistent QTL-marker associations across environments and difficulties evaluating complex trait genetics like epistasis. Future work aims to optimize MAS efficiency and integration with plant breeding.
This presentation discusses marker assisted selection (MAS) for herbicide resistance. MAS uses DNA markers linked to target genes to predict phenotypes, allowing selection earlier than phenotypic screening. The presentation provides advantages of MAS like simpler screening and selection at seedling stage. A case study of MAS for herbicide resistance in sunflower is described, where different markers like SSRs, CAPS and SNPs were developed for alleles conferring resistance. Transgenic approaches for herbicide resistance using selectable marker genes like pat/bar for phosphinothricin and epsps/aroA for glyphosate resistance are also summarized.
The document describes the development of a QTL map for Egyptian durum wheat using an F2 mapping population derived from a cross between two parental varieties, Baniswif-1 and Souhag-2. A variety of DNA markers including SSRs, RAPDs, AFLPs, ESTs and SCoTs were used to genotype the mapping population. Traits related to yield and drought tolerance such as root length, plant height, spike characteristics, and biomass were measured. Linkage analysis was performed to construct a genetic linkage map, which was then used to detect QTLs associated with the traits of interest.
This document summarizes three case studies on using marker-assisted breeding techniques:
1) Introgressing rice QTLs controlling root traits from donor Azucena into recipient Kalinga III. Five target QTLs were introgressed over three backcrosses using foreground, background, and recombinant selection with RFLPs and SSRs.
2) Introgressing the submergence tolerance Sub1 QTL from donor IR49830 into popular rice variety Swarna. The QTL was introgressed over three backcrosses and a BC3F2 line identified with minimal donor DNA.
3) Introgressing drought tolerance QTLs from donor CML247 into
The document discusses marker-assisted breeding and the services provided by the Sequencing and Genotyping Platform. It outlines the steps in marker-assisted selection, from laying out seedlings and collecting samples to running analyses. It also lists the facilities and equipment available, including robotic platforms for liquid handling and DNA/RNA extraction, real-time PCR systems, capillary sequencers, and Illumina platforms for high-throughput genotyping. The platform provides support for marker-assisted breeding programs through services like whole genome sequencing, targeted resequencing, and protocol development for next-generation sequencing applications.
Genomic gene expression changes resulting from Trypanosomiasis: a horizontal study Examining expression changes elucidated by micro arrays in seminal tissues associated with the pathophysiology of Trypanosomiasis during disease progression
IRJET- Analysis of Hybrid Purity in Watermelon using Microsatellite Marker in...IRJET Journal
This document analyzes the genetic purity of a watermelon hybrid variety ("CL-Hy-01") using microsatellite markers, and compares it to an analysis using field grow-out tests. One polymorphic microsatellite marker ("WMU4702") was identified that distinguished the two parental inbred lines. Analysis of 98 F1 hybrid seeds using this marker found 96.9% genetic purity. A field grow-out test of 100 F1 seeds found 97% purity based on morphological traits. The results of the microsatellite and field tests were comparable, demonstrating that microsatellite analysis can accurately assess hybrid purity in a shorter time than conventional field testing.
Genetics, structure, and prevalence of FP967 T-DNA in flaxJamille McLeod
The document summarizes research into the genetics, structure, and prevalence of the FP967 (CDC Triffid) T-DNA found in genetically modified flax. Key points:
- The FP967 T-DNA is thought to be inserted at a single locus in the flax genome. Quantitative PCR assays were developed to test this.
- The FP967 T-DNA was found at low levels (0.01-0.1%) in some breeder seed lots from 2009-2010 but was not detected in lines selected for advancement in the flax breeding program in 2010-2011.
- Cloning and sequencing of the FP967 T-DNA revealed an internal 3,720 bp duplication between
Marker assisted selection( mas) and its application in plant breedingHemantkumar Sonawane
Marker Types,Prerequisites for efficient marker-assisted breeding programmes,Advantages of MAS,Limitations of MAS ,Marker Assisted Breeding Schemes,• 1. Marker- assisted backcrossing,2. Marker- Assisted evaluation of breeding material,3 Gene pyramiding,4. Early generation selection ,Combined approaches,MAB: I level of Selection – FOREGROUND SELECTION,Second level of selection: Recombinant Selection,MAB: III Level of Selection BACKGROUND SELECTION,
MARKER-ASSISTED BREEDING FOR RICE IMPROVEMENTFOODCROPS
This document discusses marker-assisted breeding for rice improvement. It begins with an outline of the topics to be covered, which include the theory and practice of marker-assisted selection, marker-assisted breeding schemes, and a case study of marker-assisted backcrossing done at IRRI. The first section defines marker-assisted selection and describes its advantages over phenotypic selection, such as earlier selection and greater reliability. Subsequent sections discuss specific marker-assisted breeding schemes like backcrossing, pyramiding traits, and early generation selection. The document concludes with details of IRRI's case study using markers to backcross a submergence tolerance gene into popular rice varieties.
Systemic analysis of data combined from genetic qtl's and gene expression dat...Laurence Dawkins-Hall
Elucidating changes in gene expression by Micro array genomic sweeps of genetic QTLs linked to Tryp resistance in WT cattle to identify putative candidates underpinning pathophysiology
Trophectoderm dna fingerprinting by quantitative real time pcr successfully d...t7260678
This study validated a novel method of quantitative real-time PCR (qPCR) to distinguish sibling human embryos using DNA fingerprinting of trophectoderm biopsies. The study analyzed cell lines and excess DNA from trophectoderm biopsies of sibling human blastocysts using qPCR of 40 SNPs. Results showed the method accurately assigned relationship between samples, with sibling relationships averaging 57.2% similarity compared to 95.1% for self relationships. This qPCR-based DNA fingerprinting technique can unequivocally discriminate between sibling human embryos and will enable research on markers of embryonic reproductive potential.
Marker assisted whole genome selection in crop improvementSenthil Natesan
Mapping and tagging of agriculturally important genes have been greatly facilitated by an array of molecular markers in crop plants. Marker-assisted selection (MAS) is gaining considerable importance as it would improve the efficiency of plant breeding through precise transfer of genomic regions of interest (foreground selection) and accelerating the recovery of the recurrent parent genome (background selection). MAS has been more widely employed for simply inherited traits than for polygenic traits, although there are a few success stories in improving quantitative traits through MAS
Identification and verification of QTL associated with frost tolerance using ...PGS
This lecture was a part of Plant Genetics Seminars - PGS 2017/2018 at Assiut University. These seminars organized by Dr. Ahmed Sallam, Department of Genetics, Faculty of Agriculture, Assiut University
Abstract
Frost stress is one of the abiotic stresses that causes a significant reduction in winter faba bean yield in Europe. The main objective of this work is to genetically improve frost tolerance in winter faba bean by identifying and validating QTL associated with frost tolerance to be used in marker-assisted selection (MAS). Two different genetic backgrounds were used: a biparental population (BPP) consisting of 101 inbred lines, and 189 genotypes from single seed descent (SSD) from the Gottingen Winter bean Population (GWBP). All experiments were conducted in a frost growth chamber under controlled conditions. The symptoms of frost stress were scored. In addition, leaf fatty acid composition (FAC) was analyzed as a physiological trait in both populations. Five common QTLs for frost tolerance and FAC were found in both populations. Moreover, synteny analysis between Medicago truncatula (a model legume) and faba bean genomes was performed to identify candidate genes for the validated QTLs.
This is a lecture for Bio4025, a graduate class at Washington University in St. Louis. Some slides are derived from Julin Maloof (University of California, Davis), some of which were altered.
This document discusses the use of DNA markers and microsatellite markers (SSRs) to identify plant varieties and assess the genetic purity of hybrid seeds. [1] SSR markers were able to differentiate parental lines of 5 rice hybrids. [2] The SSR marker RM234 identified a single off-type seed (2% impurity) in a sample of CORH3 hybrid seeds. [3] SSR markers allow for reliable, reproducible, and cost-effective identification of plant varieties and assessment of seed purity compared to other marker techniques.
The document describes the development of a focused microarray to assess dopaminergic and glial cell differentiation derived from human stem cells. Specifically:
1) Researchers designed a microarray of 281 genes to detect markers of dopaminergic neurons, oligodendrocytes, astrocytes, embryonic stem cells, and progenitor cells.
2) They validated that the microarray could distinguish RNA samples from human adult brain, embryonic stem cells, and neural stem cells based on gene expression patterns.
3) As an application, they used the microarray to monitor differentiation of human embryonal carcinoma stem cells toward dopaminergic neurons and found it could distinguish differentiation stages and cell purity.
The document describes a study that aimed to validate insertions and deletions (INDELs) identified in the Genome in a Bottle (GIAB) reference standard by comparing calls made by FreeBayes and GATK variant callers. Researchers analyzed sequencing data from the NA12878 genome using the two callers and GIAB, generating 7 variant lists. They selected 150 random INDELs from each list and designed primers to amplify the regions, then validated the variants using MiSeq sequencing. The results helped improve understanding of the variant callers and the GIAB standard for INDEL calls.
A Novel High Accuracy Algorithm for Reference Assembly in Colour SpaceCSCJournals
Although numerous algorithms exist for genome alignment using Next Generation Sequencing tags, assembly of colour coded reads remains a challenge. We present a novel pairwise sequence aligner algorithm derived from Smith-Waterman method. Original feature of the algorithm is that it translates the reference sequence into colour code and performs the alignment in colour space. While operating on this base it can prevent most read error-derived assembly errors. Based on dynamic programming it gives the optimal alignment in colour space. Further, validation on empirical dataset with capillary sequencing proved high mapping accuracy. The algorithm can be implemented into any reference assembly software thereby improving mapping accuracy while maintaining high speed mapping.
This document describes methods for classifying structural variants (SVs) identified from next-generation sequencing data as true positives or false positives. The authors use multiple sequencing datasets to identify over 2000 high-confidence deletions in the Genome in a Bottle NA12878 sample. They characterize reads near candidate SVs using their SVClassify tool and apply one-class and unsupervised machine learning methods to classify SVs based on the read characteristics. Hierarchical clustering and visualization with SVViz show clear distinctions between random regions and different types of validated deletions. Classification scores indicate the method effectively distinguishes true SVs from random regions.
June 2017: Biomedical applications of prototype-based classifiers and relevan...University of Groningen
A presentation of several biomedical applications of prototype-based machine learning and relevance learning. Invited talk at the AlCoB conference 2017 in Aveiro/Portugal.
This document summarizes the process used to benchmark large deletion calls from multiple sequencing technologies and bioinformatics pipelines. Researchers merged deletion calls from 14 datasets into regions and evaluated call size accuracy. Calls supported by two or more technologies were identified as draft benchmark calls. Sensitivity to these calls was calculated for each method. The results provide insight into strengths and weaknesses of different approaches to structural variant detection.
Microarray Data Classification Using Support Vector MachineCSCJournals
DNA microarrays allow biologist to measure the expression of thousands of genes simultaneously on a small chip. These microarrays generate huge amount of data and new methods are needed to analyse them. In this paper, a new classification method based on support vector machine is proposed. The proposed method is used to classify gene expression data recorded on DNA microarrays. It is found that the proposed method is faster than neural network and the classification performance is not less than neural network.
The document summarizes an in vitro high content screening platform for assessing drug-induced hepatotoxicity through multiple mechanisms. The platform utilizes HepG2 human hepatocellular carcinoma cells in assays to measure cell proliferation, apoptosis, phospholipidosis, steatosis, cell cycle effects, and inflammatory cytokine secretion. Assays are performed in a multiplexed format using automated fluorescent microscopy and xMAP technology. The platform provides quantitative data on toxicity mechanisms and allows ranking of compounds based on their hepatotoxic potential to help guide drug development.
SRGE Workshop on Intelligent system and Application, 27 Dec. 2017 in the framework of the int. conf of computer science, information systems, and operation research, ISSR, Cairo University
dual-event machine learning models to accelerate drug discoverySean Ekins
This document describes using dual-event machine learning models to accelerate drug discovery for tuberculosis (TB). Bayesian machine learning models were generated using molecular fingerprints and descriptors from large TB screening datasets. The models were able to retrospectively and prospectively predict active compounds from both internal and external datasets with good enrichment. A prospective virtual screen of an antimalarial library identified a hit with good efficacy and selectivity in vitro and in vivo. Overall, the dual-event models integrating phenotypic screening data with cytotoxicity were able to identify several novel TB drug leads and represent an approach to accelerate drug discovery.
PERFORMANCE ANALYSIS OF MULTICLASS SUPPORT VECTOR MACHINE CLASSIFICATION FOR ...ijcsa
Automatic diagnosis of coronary heart disease helps the doctor to support in decision making a diagnosis.
Coronary heart disease have some types or levels. Referring to the UCI Repository dataset, it divided into 4
types or levels that are labeled numbers 1-4 (low, medium, high and serious). The diagnosis models can be
analyzed with multi class classification approach. One of multi class classification approach used, one of
which is a support vector machine (SVM). The SVM use due to strong performance of SVM in binary classification. This research study multiclass performance classification support vector machine to diagnose the type or level of coronary heart disease. Coronary heart disease patient data taken from the
UCI Repository. Stages in this study is preprocessing, which consist of, to normalizing the data, divide the data into data training and testing. The next stage of multiclass classification and performance analysis.This study uses multiclass SVM algorithm, namely: Binary Tree Support Vector Machine (BTSVM), OneAgainst-One (OAO), One-Against-All (OAA), Decision Direct Acyclic Graph (DDAG) and Exhaustive
Output Error Correction Code ( ECOC). Performance parameter used is recall, precision, F-measure and
Overall accuracy. The experiment results showed that the multiclass SVM classification algorithm with the
algorithm BT-SVM, OAA-SVM and the ECOC-SVM,gave the highest Recall in the diagnosis of type or
healthy level with a value above 90%, precision 82.143% and 86.793% F-measure,. For all kinds of
algorithms, except binary OAA-SVM algorithm gave the highest recall 0.0% for the type or level of sickhigh
and sick-serious, and ECOC- SVM algorithm gave the highest recall 0.0% for sick-medium and sickserious.
While the type or level other, the performance of recall, precision and F-measure between 20% -
30%,. The conclusion that can be drawn is that the approach to the multiclass classification algorithm BTSVM,
OAO-SVM, DDAG-SVM to diagnosis the type or level of coronary heart disease provides better performance, than the binary classification approach.
This document compares five machine learning techniques for classifying medical data related to prostate cancer therapy changes. The techniques evaluated are Decision Trees (J48), Neural Networks (MLP), Naive Bayes, Radial Basis Function (RBF), and K-Nearest Neighbors (IBk). Medical data from 40 patients containing blood test parameters and therapy change decisions were analyzed using the WEKA toolkit. For the first quarter of data, Naive Bayes and RBF achieved the highest accuracy at 90% while IBk had the lowest at 82.5%. Naive Bayes also had the lowest error rates, indicating it had the best classification capabilities. Overall, RBF performed best in terms of accuracy, error rates, and time taken, suggesting
This document summarizes a research paper that proposes using a genetic algorithm to optimize the placement of Fiber Bragg Grating sensors for structural health monitoring. It begins by introducing FBG sensors and the need for sensor placement optimization when resources are limited. It then provides background on genetic algorithms and describes how they can be applied to the sensor placement problem by coding sensor locations into chromosomes, evaluating fitness, and using genetic operators like selection, crossover and mutation to evolve optimized sensor configurations. The document explains the genetic algorithm approach in detail through sections on coding, initial population, selection, crossover and mutation operations.
Similar to Statistical methods for off-target variant genotyping on Affymetrix' Axiom Arrays (12)
The Axiom Genome-Wide ASI 1 Array provides high genomic coverage of common and rare alleles in East Asian populations. It contains over 600,000 SNPs, including variants from important biological categories. Validation testing showed the array achieves over 99.5% concordance with HapMap samples and over 99.7% repeatability. The array offers greater coverage of rare Asian variants compared to competing products.
SNP genotyping using the Affymetrix® Axiom® Genome-Wide Pan-African (PanAFR) ...Affymetrix
The document describes the Axiom Genome-Wide PanAFR Array Set, which was designed to maximize coverage of common and rare genetic variants in populations of Yoruba ancestry. The array contains over 2.2 million markers selected from several genome projects to provide high coverage of the genome as well as specific regions and gene categories. Testing showed the array performs well with an average call rate over 99% and high concordance and reproducibility of calls.
A SNP array for human population genetics studiesAffymetrix
Yontao Lu, Teri Genschoreck, Swapan Mallick, Amy Ollmann, Nick Patterson, Yiping Zhan, Teresa Webster, David Reich Overview of the Human Origins Array, the first array developed with leading geneticists to enable rigorous population genetics studies.
Axiom® Genome-Wide LAT 1 Array World Array 4Affymetrix
Coverage-Optimized World Arrays: next-generation designs combining GWAS, replication, and fine-mapping into one array. Dense marker coverage of disease-associated SNPs, genes, and regions, plus whole-genome coverage of common and rare variants. Optimized for diverse ancestries including European, African and Native American.
Axiom® Genome-Wide AFR 1 Array World Array 3Affymetrix
The document describes the Axiom Genome-Wide AFR 1 Array, which provides high coverage of genetic variants associated with disease in African and African American populations. It was designed to maximize coverage of common and rare variants down to a minor allele frequency of 1% in specific gene regions and disease-associated areas. The array contains over 893,000 SNPs selected from genome-wide association studies and databases of disease-associated variants. It enables genome-wide association studies, replication, and fine mapping with one experiment.
Solutions for Personalized Medicine brochureAffymetrix
The document discusses personalized medicine and describes some of the tools and technologies used for biomarker discovery and validation to enable personalized medicine. Specifically, it discusses:
1) Affymetrix provides a portfolio of tools to detect and validate DNA and RNA biomarkers for diseases like cancer through microarrays, services, and assays that can interrogate genomes, transcriptomes, genes, pathways, and individual molecules.
2) RNA and DNA biomarkers like gene expressions levels, mutations, and other genomic alterations can serve as indicators of disease processes and therapeutic responses. Affymetrix tools allow analysis of whole genomes, transcriptomes, alternative splicing, and single-cell analysis.
3) These tools are used to discover and validate biomarkers which
Affymetrix OncoScan®* data analysis with Nexus Copy Number™Affymetrix
This document discusses the analysis of Affymetrix OncoScan data using Nexus Copy Number software. It outlines researchers' needs such as visualizing data, identifying common aberrations, comparing sample populations, and predictive analysis. It then describes the data processing in Nexus, including algorithms for identifying significant aberrations and dealing with heterogeneity. Finally, it shows examples of data visualization, analysis features for survival, enrichment, and comparing groups that Nexus provides to help researchers analyze and understand OncoScan data.
Allopolyploid Genotyping Algorithm on Affymetrix' Axiom ArraysAffymetrix
Hong Gao, Bioinformatics, Affymetrix.An automated algorithm that reduces genotype analysis to ~1 hour is described and applied to hexaploid wheat data.
SNP genotyping of markers with nearby secondary polymorphisms using Affymetri...Affymetrix
Laurent Bellon, Product Development, Affymetrix.Axiom® Genotyping Solution is uniquely suited to genotyping of highly polymorphic genomes as it is permissive to secondary variants as close as 10 bp from the target variant.
Development of a high-throughput high-density SNP genotyping array for bovineAffymetrix
This document summarizes the development of a high-density SNP genotyping array for cattle. Key points:
1) Researchers from Affymetrix and academic institutions combined efforts to sequence the genomes of 15 bovine breeds and identify over 3 million SNPs.
2) A set of 648,000 SNPs was selected from the 3 million to be included on the new AxiomTM Genome-Wide BOS 1 Array based on their ability to genetically represent linkage disequilibrium blocks across multiple breeds.
3) Testing of the new array showed over 99% call rate and genetic coverage of over 90% for many beef and dairy cattle breeds, demonstrating its effectiveness for applications like marker-assisted breeding.
SNP genotyping using Affymetrix' Axiom Genotyping SolutionAffymetrix
Michael Shapero, Product Development, Affymetrix.Outline of the development and performance of the new Axiom® 384 high-throughput format for low-cost genotyping of up to 50,000 SNPs.
The use of Nauplii and metanauplii artemia in aquaculture (brine shrimp).pptxMAGOTI ERNEST
Although Artemia has been known to man for centuries, its use as a food for the culture of larval organisms apparently began only in the 1930s, when several investigators found that it made an excellent food for newly hatched fish larvae (Litvinenko et al., 2023). As aquaculture developed in the 1960s and ‘70s, the use of Artemia also became more widespread, due both to its convenience and to its nutritional value for larval organisms (Arenas-Pardo et al., 2024). The fact that Artemia dormant cysts can be stored for long periods in cans, and then used as an off-the-shelf food requiring only 24 h of incubation makes them the most convenient, least labor-intensive, live food available for aquaculture (Sorgeloos & Roubach, 2021). The nutritional value of Artemia, especially for marine organisms, is not constant, but varies both geographically and temporally. During the last decade, however, both the causes of Artemia nutritional variability and methods to improve poorquality Artemia have been identified (Loufi et al., 2024).
Brine shrimp (Artemia spp.) are used in marine aquaculture worldwide. Annually, more than 2,000 metric tons of dry cysts are used for cultivation of fish, crustacean, and shellfish larva. Brine shrimp are important to aquaculture because newly hatched brine shrimp nauplii (larvae) provide a food source for many fish fry (Mozanzadeh et al., 2021). Culture and harvesting of brine shrimp eggs represents another aspect of the aquaculture industry. Nauplii and metanauplii of Artemia, commonly known as brine shrimp, play a crucial role in aquaculture due to their nutritional value and suitability as live feed for many aquatic species, particularly in larval stages (Sorgeloos & Roubach, 2021).
Deep Behavioral Phenotyping in Systems Neuroscience for Functional Atlasing a...Ana Luísa Pinho
Functional Magnetic Resonance Imaging (fMRI) provides means to characterize brain activations in response to behavior. However, cognitive neuroscience has been limited to group-level effects referring to the performance of specific tasks. To obtain the functional profile of elementary cognitive mechanisms, the combination of brain responses to many tasks is required. Yet, to date, both structural atlases and parcellation-based activations do not fully account for cognitive function and still present several limitations. Further, they do not adapt overall to individual characteristics. In this talk, I will give an account of deep-behavioral phenotyping strategies, namely data-driven methods in large task-fMRI datasets, to optimize functional brain-data collection and improve inference of effects-of-interest related to mental processes. Key to this approach is the employment of fast multi-functional paradigms rich on features that can be well parametrized and, consequently, facilitate the creation of psycho-physiological constructs to be modelled with imaging data. Particular emphasis will be given to music stimuli when studying high-order cognitive mechanisms, due to their ecological nature and quality to enable complex behavior compounded by discrete entities. I will also discuss how deep-behavioral phenotyping and individualized models applied to neuroimaging data can better account for the subject-specific organization of domain-general cognitive systems in the human brain. Finally, the accumulation of functional brain signatures brings the possibility to clarify relationships among tasks and create a univocal link between brain systems and mental functions through: (1) the development of ontologies proposing an organization of cognitive processes; and (2) brain-network taxonomies describing functional specialization. To this end, tools to improve commensurability in cognitive science are necessary, such as public repositories, ontology-based platforms and automated meta-analysis tools. I will thus discuss some brain-atlasing resources currently under development, and their applicability in cognitive as well as clinical neuroscience.
The binding of cosmological structures by massless topological defectsSérgio Sacani
Assuming spherical symmetry and weak field, it is shown that if one solves the Poisson equation or the Einstein field
equations sourced by a topological defect, i.e. a singularity of a very specific form, the result is a localized gravitational
field capable of driving flat rotation (i.e. Keplerian circular orbits at a constant speed for all radii) of test masses on a thin
spherical shell without any underlying mass. Moreover, a large-scale structure which exploits this solution by assembling
concentrically a number of such topological defects can establish a flat stellar or galactic rotation curve, and can also deflect
light in the same manner as an equipotential (isothermal) sphere. Thus, the need for dark matter or modified gravity theory is
mitigated, at least in part.
ANAMOLOUS SECONDARY GROWTH IN DICOT ROOTS.pptxRASHMI M G
Abnormal or anomalous secondary growth in plants. It defines secondary growth as an increase in plant girth due to vascular cambium or cork cambium. Anomalous secondary growth does not follow the normal pattern of a single vascular cambium producing xylem internally and phloem externally.
EWOCS-I: The catalog of X-ray sources in Westerlund 1 from the Extended Weste...Sérgio Sacani
Context. With a mass exceeding several 104 M⊙ and a rich and dense population of massive stars, supermassive young star clusters
represent the most massive star-forming environment that is dominated by the feedback from massive stars and gravitational interactions
among stars.
Aims. In this paper we present the Extended Westerlund 1 and 2 Open Clusters Survey (EWOCS) project, which aims to investigate
the influence of the starburst environment on the formation of stars and planets, and on the evolution of both low and high mass stars.
The primary targets of this project are Westerlund 1 and 2, the closest supermassive star clusters to the Sun.
Methods. The project is based primarily on recent observations conducted with the Chandra and JWST observatories. Specifically,
the Chandra survey of Westerlund 1 consists of 36 new ACIS-I observations, nearly co-pointed, for a total exposure time of 1 Msec.
Additionally, we included 8 archival Chandra/ACIS-S observations. This paper presents the resulting catalog of X-ray sources within
and around Westerlund 1. Sources were detected by combining various existing methods, and photon extraction and source validation
were carried out using the ACIS-Extract software.
Results. The EWOCS X-ray catalog comprises 5963 validated sources out of the 9420 initially provided to ACIS-Extract, reaching a
photon flux threshold of approximately 2 × 10−8 photons cm−2
s
−1
. The X-ray sources exhibit a highly concentrated spatial distribution,
with 1075 sources located within the central 1 arcmin. We have successfully detected X-ray emissions from 126 out of the 166 known
massive stars of the cluster, and we have collected over 71 000 photons from the magnetar CXO J164710.20-455217.
The debris of the ‘last major merger’ is dynamically youngSérgio Sacani
The Milky Way’s (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the
‘last major merger.’ Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor
collided with the MW proto-disc 8–11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor collided with the
MW disc within the last 3 Gyr. These two scenarios make different predictions about observable structure in local phase space,
because the morphology of debris depends on how long it has had to phase mix. The recently identified phase-space folds in Gaia
DR3 have positive caustic velocities, making them fundamentally different than the phase-mixed chevrons found in simulations
at late times. Roughly 20 per cent of the stars in the prograde local stellar halo are associated with the observed caustics. Based
on a simple phase-mixing model, the observed number of caustics are consistent with a merger that occurred 1–2 Gyr ago.
We also compare the observed phase-space distribution to FIRE-2 Latte simulations of GSE-like mergers, using a quantitative
measurement of phase mixing (2D causticality). The observed local phase-space distribution best matches the simulated data
1–2 Gyr after collision, and certainly not later than 3 Gyr. This is further evidence that the progenitor of the ‘last major merger’
did not collide with the MW proto-disc at early times, as is thought for the GSE, but instead collided with the MW disc within
the last few Gyr, consistent with the body of work surrounding the VRM.
ESPP presentation to EU Waste Water Network, 4th June 2024 “EU policies driving nutrient removal and recycling
and the revised UWWTD (Urban Waste Water Treatment Directive)”
Nucleophilic Addition of carbonyl compounds.pptxSSR02
Nucleophilic addition is the most important reaction of carbonyls. Not just aldehydes and ketones, but also carboxylic acid derivatives in general.
Carbonyls undergo addition reactions with a large range of nucleophiles.
Comparing the relative basicity of the nucleophile and the product is extremely helpful in determining how reversible the addition reaction is. Reactions with Grignards and hydrides are irreversible. Reactions with weak bases like halides and carboxylates generally don’t happen.
Electronic effects (inductive effects, electron donation) have a large impact on reactivity.
Large groups adjacent to the carbonyl will slow the rate of reaction.
Neutral nucleophiles can also add to carbonyls, although their additions are generally slower and more reversible. Acid catalysis is sometimes employed to increase the rate of addition.
Statistical methods for off-target variant genotyping on Affymetrix' Axiom Arrays
1. Statistical methods for off-target variant
genotyping on Affymetrix’Axiom® Arrays
Teresa A. Webster, Ali Pirani, Mei-mei Shen, Laurent Bellon, and Hong Gao
Affymetrix, Inc. Santa Clara, CA 95051 USA
Algorithm for OTV genotyping
We developed a statistical approach called “OTVCaller” to genotype the
OTV SNPs. This algorithm uses the posterior genotyping information
generated by the automated clustering algorithm AxiomGT1 to initiate the
2D Baum-Welch algorithm in order to search for the optimal clustering in
both intensity strength and contrast dimensions. It then iteratively
updates sample assignments and cluster centers until convergence is
reached. The detailed workflow of the OTVCaller algorithm is shown in
Figure 3 and is implemented in SNPolisher R package.
Figure 3: The workflow of the OTVCaller algorithm. Two models are considered,
including a three-genotype model (AA, BB, and OTV) and a four genotype model
(AA, AB, BB, and OTV). The last step is to select the best-fit model.
ABSTRACT
Background: Off-target variants (OTVs) (Didion, et al., BMC Genomics
13:34, 2012) are genomic markers with sequences that are significantly
different from the sequences of hybridization probes used in microarray-based
genotyping. This dissimilarity between probe and target can lower
hybridization intensities such that genotypes of the subpopulation are often
incorrectly called as heterozygotes by genotyping algorithms that cluster
intensities into three expected genotypes, namely AA, AB, and BB. OTVs tend
to group members of the divergent subpopulation into a fourth cluster
denoted as the OTV cluster. Therefore, correct identification of this OTV
cluster, a process described as OTV genotyping, is a critical step.
Results: We have developed a statistical method called “OTVCaller” to
genotype all OTVs based on the posterior genotyping information generated
by the automated clustering algorithm AxiomGT1, which is used by Axiom®
Genotyping Console™ Software. OTVCaller uses posterior genotypes as the
prior information to initiate the Baum-Welch algorithm to iteratively search for
the optimal locations of the four clusters AA, AB, BB, and OTV. It then derives
genotypes and OTV types when convergence is reached. We applied OTVCaller
to genotype data from multiple species and demonstrate OTVCaller can
successfully identify the OTV cluster in the presence of all three genotypes
(AA, AB, and BB) or in the presence of only two genotypes (AA and BB).
OTVCaller is available from Affymetrix in a SNP data analysis post-processing
R package “SNPolisher™” and is applicable to Axiom® genotyping arrays.
Background
Off-target variant (OTV) probes (Didion, et al., 2012)1 usually demonstrate
substantially low hybridization intensity and center at zero in contrast
dimension, due to double deletion or sequence nonhomology. Thus they tend
to confound the genotype calling of heterozygotes. Therefore, there is a critical
need for statistical methods to distinguish OTVs from true heterozygotes.
Application to wheat OTV genotypes
We applied the OTVCaller algorithm implemented in SNPolisher™ R package
to bread wheat genotyping data generated with Affymetrix’ Axiom® custom
array. OTVCaller accurately corrected miscalled heterozygotes, as shown in
Figure 4 where OTVs had been miscalled as heterozygotes and true
heterozygotes had been miscalled as null calls before OTV genotyping. They
are all corrected after OTV genotyping.
Figure 4: Three examples of OTV clusters before and after OTV genotyping by
OTVCaller algorithm. OTV clusters are represented by cyan diamonds.
OTV
AABBBB AA
AB
OTV
Figure 1: Two
examples of
OTV genotypes.
Left has four
genotypes, AA,
AB, BB, and OTV.
Right has three
genotypes, AA,
BB, and OTV.
Diamonds in cyan
represent off-
target variants.
Figure 2: Two examples of genotype clusters with low HetSO values. They are
identified as OTV genotypes as their HetSO values are below -0.3.
Before OTV Genotyping
Identification of OTV genotypes
We internally developed a metric for SNP quality control called heterozygote
strength offset (HetSO). It is defined as the vertical distance (as measured by
[A+B]/2 or signal size) from the center of the heterozygote cluster to the line
connecting the centers of the homozygote clusters.
Large negative values are usually associated with OTV clusters. Therefore, we
define OTVs as genotypes with good cluster resolution but with HetSO < -0.3,
which is a customizable threshold. Identification of OTV genotypes is executed
automatically by SNPolisher R package.
After OTV Genotyping
1. Didion, J.P., Yang, H., Sheppard, K., Fu, C., McMillan, L., Villena, F.P., and Churchill, G.A. Discovery of novel variants in
genotyping arrays improves genotype retention and reduces ascertainment bias. BMC Genomics 13:34 (2012).
HetSO
=‐2.24 HetSO=
‐0.72