JMPer Cable

Latest Posts

• Cross Evaluation and Progeny Simulation with JMP Genomics, Part 1: BLUP for Breeding Trial Data

  For this example, we have a set of 309 barley lines, which have been genotyped for ~3,500 markers each. We also have a set of measurements of four phenotypes taken from field trials from two separate locations over a two-year period. The phenotypes measured are protein content, test weight, ergosterol content, and protein yield. Before evaluating crosses and simulating progeny, we must capture the...

  Daniel_Genung

  JMPer Cable |

  Aug 28, 2019 9:36 AM

  8100 views | 0 replies
  

• Cross Evaluation and Progeny Simulation with JMP Genomics, Part 2: Predictive Modeling for Breeding Values

  In last week’s post, we consolidated breeding trial data into a single table using Best Linear Unbiased Prediction. The table below shows ~300 barley lines with phenotypic values for four traits and ~7000 genetic markers. In this post, we will use the Predictive Modeling Review tool in JMP Genomics to create multiple models and compare them via cross validation. After cross validation, we will sel...

  Daniel_Genung

  JMPer Cable |

  Aug 28, 2019 9:35 AM

  6442 views | 0 replies
  

• Navigating your reports using XPath

  Another way to navigate JMP reports? Yes, please!

  Wendy_Murphrey

  JMPer Cable |

  Aug 7, 2019 11:51 AM

  7724 views | 3 replies
  

• Expression Analysis with JMP Genomics, Part 3: Basic Expression Workflow

  JMP Genomics has analytical pipelines or Workflows to perform a series of analyses on a data set. The Basic Expression Workflow automates a series of quality control and normalization methods, followed by ANOVA, to perform a basic expression analysis. For this workflow, we will inspect data from an experiment in which MCF7 cells, cells which cause tumors, are exposed to estrogen at three different...

  Daniel_Genung

  JMPer Cable |

  Jul 16, 2019 8:56 AM

  6747 views | 2 replies
  

• Expression Analysis with JMP Genomics, Part 1: Experimental Design

  To perform expression analysis in JMP Genomics, an Experimental Design File (EDF) is required.  The EDF contains sample annotation information and/or phenotype information for a related expression data set. There are a few different ways to create this file but the best method for creating an EDF is dependent upon how your data is organized. For this guide, we create an EDF for a series of data fi...

  Daniel_Genung

  JMPer Cable |

  Jul 11, 2019 3:21 PM

  5284 views | 0 replies
  

• Expression Analysis with JMP Genomics, Part 2: Importing Expression Data from Text Files

  In last week’s blog post, we created an Experimental Design File (EDF) using JMP Genomics for a set of gene expression files corresponding to 18 different experimental groups. Now that the experimental design is organized into a SAS data set, the data files (in txt format) can be imported and concatenated into a single table using the Import a Designed Experiment from Text, CSV, or Excel Files too...

  Daniel_Genung

  JMPer Cable |

  Jul 5, 2019 12:03 PM

  4649 views | 0 replies
  

• 如何運用JMP進行可靠度(Reliability)分析

  合理應用可靠度分析，可以幫助研發、工程、品質等部門的技術人員提高產品品質的穩定性，降低產品全壽命週期費用和售後服務成本，改善顧客的滿意度和忠誠度。

  Ritalv

  JMPer Cable |

  Jul 2, 2019 6:44 PM

  6878 views | 0 replies
  

• Expression Analysis with JMP Genomics

  JMP Genomics is a specialized yet broad tool for analyzing genetic, genomic and other “-omic” data. Whether it's expression analysis, GWAS, predictive modeling, or plant breeding, JMP Genomics has a tool to meet the need.

  Daniel_Genung

  JMPer Cable |

  Jul 2, 2019 2:09 PM

  5074 views | 2 replies
  

• Genetic Association with JMP Genomics

  JMP Genomics is a specialized yet broad tool for analyzing genetic, genomic and other “-omic” data. Whether it's expression analysis, GWAS, predictive modeling, or plant breeding, JMP Genomics has a tool to meet the need. This blog series (the first in a set of four series) will handle genetic association beginning with the data import and continuing through several analytical pipelines.

  Daniel_Genung

  JMPer Cable |

  Jun 26, 2019 7:50 AM

  7360 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 6: SNP-Trait Association

  JMP Genomics has an array of tools to associate genetic variants with traits. One of the most straightforward of these tools is SNP-Trait Association. By performing this analysis, you can quickly identify significant markers for multiple categorical or quantifiable traits. In this example, we explore ~22,000 markers for histiocytic sarcomas (tumors) in a sample of 474 Bernese Mountain Dogs. The ph...

  Daniel_Genung

  JMPer Cable |

  Jun 24, 2019 2:17 PM

  8762 views | 10 replies
  

• Genetic Association with JMP Genomics, Part 5: QTL Single Marker Analysis

  The QTL Single Marker Analysis tool in JMP Genomics performs a simple regression to correlate quantitative traits with markers within a genome. This tool is a great way to scan an entire set of markers and quickly identify loci of interest for a trait. In this example we will analyze 90 recombinant inbred lines of oat for their mean differential scanning calorimetry (DSC). Note that the two data s...

  Daniel_Genung

  JMPer Cable |

  Jun 18, 2019 1:42 PM

  5041 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 4: Basic Linkage Mapping

  The Basic Linkage Mapping Workflow in JMP Genomics creates linkage maps using genetic marker data. The workflow includes output from the Recombination and Linkage Groups, Linkage Map Order, and Linkage Map Viewer. This includes calculation of recombination frequencies, testing for segregation distortion, assigning linkage groups to sets of markers, generating visualized linkage maps, and reorderin...

  Daniel_Genung

  JMPer Cable |

  Jun 18, 2019 1:01 PM

  5188 views | 0 replies
  

• Saving graphs, tables and reports in JMP

  Saving and sharing your output from JMP is easy. Here are some simple ways to save both tabular output and/or graphs in JMP.

  MaryLoveless

  JMPer Cable |

  Jun 14, 2019 5:41 AM

  95733 views | 19 replies
  

• How to make Harvey Balls in JMP in 3 ways

  OK, let's get something out of the way right from the start. There are so many jokes... so very many jokes... that I could make about this topic. But, I'm not going to make them. I'm going to take the high road. Not because I want to, if you've read any of my other articles, you'll know I revel in wordplay and corny jokes. No, I'm going to take the high road because I'm reasonably sure my editors ...

  MikeD_Anderson

  JMPer Cable |

  Jun 13, 2019 12:04 PM

  9256 views | 1 replies
  

• Genetic Association with JMP Genomics, Part 1: Importing and Cleaning Data

  In the Genetic Association with JMP Genomics series, we will discover numerous methods for associating genetic markers with traits of interest. Before starting any analyses, we need to import and clean our data. In this guide, we download a data set from GEO, bring it into JMP, and transform it into an ideal form for analysis. In this example, we explore ~22,000 genetic markers in a sample of 474 ...

  Daniel_Genung

  JMPer Cable |

  Jun 13, 2019 7:54 AM

  5496 views | 2 replies
  

• Genetic Association with JMP Genomics, Part 2: Basic Genetics Workflow (Case-Control)

  JMP Genomics has analytical pipelines or Workflows to perform a series of analyses on a data set. The Basic Genetics Workflow is a quick and easy method for gaining a deeper understanding of your data before beginning a more in-depth analysis. This workflow recodes marker data to a numeric format, imputes missing genotypic data, and creates data subsets based on minor allele frequency (MAF), missi...

  Daniel_Genung

  JMPer Cable |

  Jun 12, 2019 9:24 AM

  5418 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 3a: Marker Based Relationship Matrix

  In JMP Genomics, the Relationship Matrix analysis is used for computing and displaying relatedness among lines. The Relationship Matrix tool estimates the relationships among the lines using marker data, rather than pedigree information (Kinship Matrix tool), and computes the relationship measures directly while also accounting for selection and genetic drift. The Relationship Matrix computes one ...

  Daniel_Genung

  JMPer Cable |

  Jun 12, 2019 9:21 AM

  6797 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 3b: Population Structure Matrix

  Population structure is genetic similarity across large groups of individuals or lines. In preparation for association mapping, population structure should be assessed. Like familial relatedness, population structure can be incorporated into an association mapping analysis. In QK association analysis, population structure is modeled with a Q matrix, and familial relatedness is modeled with a K mat...

  Daniel_Genung

  JMPer Cable |

  Jun 12, 2019 9:18 AM

  6104 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 3c: Q-K Mixed Model

  Q-K association analysis was developed to perform association mapping while controlling for population structure and/or familial relatedness. The “Q-K” in this name refers to the two kinds of information that get included in the model. The Q matrix contains information about population structure (See Part 3b: Population Structure Matrix). The K matrix contains more fine-grained information about r...

  Daniel_Genung

  JMPer Cable |

  Jun 12, 2019 9:17 AM

  7114 views | 0 replies
  

• Genetic Association with JMP Genomics, Part 3d: Q-K Mixed Model Workflow for Genetic Association

  There two ways to run a Q-K analysis in JMP Genomics. One example uses the Q-K Mixed Model process, which was outlined in the Genetic Association with JMP Genomics, Part 3c: Q-K Mixed Model, and is a general tool that has a great deal of flexibility, but requires you to construct the input data set yourself. A simpler option is the Genetics Q-K Analysis Workflow, which performs all the steps for t...

  Daniel_Genung

  JMPer Cable |

  Jun 12, 2019 9:16 AM

  4800 views | 0 replies