HLAtools
Overview | 1. Reference Datasets | Atlas of Gene Feature Boundaries | Protein Sequence Atlases | Nucleotide Sequence Atlases | Genomic Sequence Atlases | Historical Catalogue of HLA Allele Names | Functional and Organizational Categories of Genes in the HLA Region | Molecular Characteristics of HLA Region Genes | Gazetteer of HLA Region Genes | Annotation of Pseudogene and Gene Fragment Features | Sequence Alignments | Protein (AA) Aligments | Codon and Individual Nucleotide (cDNA) Sequence Alignments | Genomic (gDNA) Sequence Alignments | Insertion-Deletion (Indel) Variant Representation | 2. Working with Sequence Alignments | Building Alignments | Working with Alignments in Past Releases | Caveats for Alignments from Previous Releases | 3. Trim, Search and Query Functions | Trimming HLA Allele Names by Digits or Fields | Identifying Differences Between Alleles at a Locus | Searching Allele Names Across IPD-IMGT/HLA Database Release Versions | Searching Alignments at Specific Positions | Identifying Sequence Variants at Specific Positions and their Frequencies Across all Alleles | Searching Alignments for Sequence Motifs | Building Custom Alignments | 4. Data Translation and Conversion Tools | Working with Genotype List String (GL String), GL String Code (GLSC), and UNIFORMAT Data | Translate GL String Codes Across IPD-IMGT/HLA Database Release Versions | updateGL | multiUpdateGL | Translate vectors and data frames of HLA allele name data across IPD-IMGT/HLA Database Release Versions | Convert GL String-formatted data to UNIFORMAT-formatted data | validateGLstring | GLStoUNI | multiGLStoUNI | Convert UNIFORMAT-formatted data to GL String-formatted data | validateUniformat | UNItoGLS | multiUNItoGLS | 5. Data Analysis Tools | Example Data | Calculating Relative Risk with BIGDAWG-formatted Datasets | relRisk | Division of BIGDAWG-formatted Datasets for Stratification Analyses | BDstrat: Multilocus Allele Stratification for BIGDAWG Datasets | Conversion of BIGDAWG-formatted Datasets to Python for Population Genetics (PyPop)-formatted Datasets | BDtoPyPop : Enabling Population Genetic Analyses of Case and Control Datasets