| Sleipnir::CBayesNetFN | Implements IBayesNet for networks using custom node types |
| Sleipnir::CBayesNetMinimal | Implements a heavily optimized discrete naive Bayesian classifier |
| Sleipnir::CBayesNetSmile | Implements IBayesNet for networks using the SMILE library from the U. Pittsburgh Decision Systems Lab |
| Sleipnir::CBinaryMatrix | A special symmetric matrix in which each entry consumes exactly one bit |
| Sleipnir::CClustHierarchical | Utility class containing static hierarchical clustering methods |
| Sleipnir::CClustKMeans | Utility class containing static k-means clustering methods |
| Sleipnir::CClustPivot | Utility class containing static pivot clustering methods |
| Sleipnir::CClustQTC | Utility class containing static quality threshold clustering methods |
| Sleipnir::CCoalesce | Performs regulatory module prediction (gene expression biclustering plus de novo sequence motif discovery) using the COALESCE algorithm of Huttenhower et al. 2009 |
| Sleipnir::CCoalesceCluster | Manages a single converging regulatory module for CCoalesce |
| Sleipnir::CCoalesceMotifLibrary | Manages a set of kmer, reverse complement, and probabilistic suffix tree motifs for CCoalesce |
| Sleipnir::CColor | Simple representation of a color triple in RGB space |
| Sleipnir::CCompactFullMatrix | Store a discrete matrix using the fewest possible bytes |
| Sleipnir::CCompactMatrix | Store a discrete symmetric matrix using the fewest possible bytes |
| Sleipnir::CDat | Stores a continuously valued half matrix paired with a list of names for matrix elements |
| Sleipnir::CDatabase | Encapsulates a simple indexless database allowing rapid per-gene access to values from many datasets |
| Sleipnir::CDataFilter | Augments a dataset with a dynamically calculated gene set filter |
| Sleipnir::CDataMask | Augments a dataset with a mask to dynamically exclude specific gene pairs |
| Sleipnir::CDataPair | Encapsulates a CDat paired with a quantization file |
| Sleipnir::CDataset | A simple implementation of IDataset directly loading unmodified CDats for each non-hidden data node |
| Sleipnir::CDatasetCompact | An implementation of IDataset optimized for compactly storying discrete data |
| Sleipnir::CDatasetCompactMap | Augments a compact dataset with a mask to dynamically exclude specific gene pairs |
| Sleipnir::CDataSubset | An IDataset implementation that loads subsets of continuous data in serial to conserve memory |
| Sleipnir::CDatFilter | Augments a CDat with a dynamically calculated gene set filter |
| Sleipnir::CFASTA | Encapsulates a standard FASTA file or a modified ENCODE-style wiggle (WIG) file |
| Sleipnir::CFullMatrix< tType > | An asymmetric two-dimensional matrix |
| Sleipnir::CGene | Represents a gene with a single primary unique identifier, zero or more synonyms, and zero or more functional annotations |
| Sleipnir::CGenes | Represents a simple set of unique genes |
| Sleipnir::CGenome | Organizes a collection of unique genes representing a background or maximum gene set for some situation |
| Sleipnir::CHalfMatrix< tType > | A symmetric two-dimensional matrix |
| Sleipnir::CHierarchy | Represents a simple node in a binary tree |
| Sleipnir::CHMM | Extremely simple Hidden Markov Model (HMM) implementation allowing learning and generation from the model |
| Sleipnir::CMath | Utility class containing static basic math functions |
| Sleipnir::CMeasureAutocorrelate | Autocorrelates an underlying measure by rotating input vectors and returning the minimum result |
| Sleipnir::CMeasureBinaryInnerProduct | Calculates the number of positions in which both vectors have nonzero elements (centering and weights ignored) |
| Sleipnir::CMeasureEuclidean | Calculates the Euclidean distance between the two vectors |
| Sleipnir::CMeasureHypergeometric | Calculate the hypergeometric p-value of overlap between two boolean vectors (centering and weights ignored) |
| Sleipnir::CMeasureInnerProduct | Calculates the inner product of two vectors (centering ignored, weights used in pairwise products) |
| Sleipnir::CMeasureInvert | Inverts an underlying measure by inverting its result (dividing one by the value) |
| Sleipnir::CMeasureKendallsTau | Calculates the Kendall's Tau correlation between two vectors (centering as per EMap, weights used in pairwise products) |
| Sleipnir::CMeasureKolmogorovSmirnov | Calculates the Kolmogorov-Smirnov p-value of difference between two vectors (centering and weights ignored) |
| Sleipnir::CMeasureMutualInformation | Calculates the mutual information in bits between two integer vectors (centering and weights ignored) |
| Sleipnir::CMeasureNegate | Inverts an underlying measure by negating its result |
| Sleipnir::CMeasurePearNorm | Calculates the Fisher's z-transformed Pearson correlation between the two vectors |
| Sleipnir::CMeasurePearson | Calculates the Pearson correlation between the two vectors |
| Sleipnir::CMeasurePearsonSignificance | Calculates the p-value of Pearson correlation between two vectors (centering ignored, weights used for correlation) |
| Sleipnir::CMeasureQuickPearson | Calculates the Pearson correlation between the two vectors |
| Sleipnir::CMeasureRelativeAUC | Calculates the difference in relative absolute sums of two vectors (centering and weights ignored) |
| Sleipnir::CMeasureSigmoid | Inverts an underlying measure using a sigmoid function |
| Sleipnir::CMeasureSpearman | Calculates Spearman's rank correlation between two vectors (centering as per EMap, weights ignored) |
| Sleipnir::CMeta | Utility class containing static utility functions |
| Sleipnir::COntologyGO | Implements IOntology for the Gene Ontology |
| Sleipnir::COntologyKEGG | Implements IOntology for the KEGG orthology |
| Sleipnir::COntologyMIPS | Implements IOntology for the MIPS functional catalog |
| Sleipnir::COntologyMIPSPhenotypes | Extends COntologyMIPS to include the (apparently defunct) "phencat" phenotype hierarchy |
| Sleipnir::COrthology | An orthology is a collection of sets, each containing zero or more orthologous genes from any organism |
| Sleipnir::CPCL | Encapsulates a PCL (or, in a pinch, CDT) formatted microarray data file |
| Sleipnir::CPCLPair | Encapsulates a CPCL paired with a quantization file |
| Sleipnir::CPCLSet | A PCL set manages a collection of CPCL objects and aligns their gene indices |
| Sleipnir::CPST | Represents a probabilistic suffix tree (PST) containing zero or more overlapping strings in a weighted manner |
| Sleipnir::CServer | Provide a basic multithreaded TCP/IP server for simple communication tasks |
| Sleipnir::CSlim | Represents a set of ontology terms |
| Sleipnir::CSparseListMatrix< tType > | An asymmetric two-dimensional sparse matrix using linked lists for each row |
| Sleipnir::CSparseMapMatrix< tType > | An asymmetric two-dimensional sparse matrix using maps for each row |
| Sleipnir::CStatistics | Utility class containing static statistics functions |
| Sleipnir::CSVM | Provides an interface for learning and evaluating support vector machines using svm_perf |
| Sleipnir::CTrie< tType > | A simple prefix tree implementation |
| Sleipnir::CTrieIterator< tType > | Iterator for inorder traversal of trie keys |
| Sleipnir::IBayesNet | Encapsulates a Bayesian network with arbitrary structure and node types |
| Sleipnir::IDataset | An IDataset abstracts a collection of individual datasets, usually CDats, using various continuous and/or discrete encodings |
| Sleipnir::IMeasure | Encapsulates any similarity (or occasionally distance) measure operating over two vectors |
| Sleipnir::IOntology | Encapsulates a functional catalog/hierarchy/ontology such as GO, KEGG, or MIPS |
| Sleipnir::IServerClient | Provide a simple interface for objects handling network requests on a server thread |
| Sleipnir::SFASTABase | Base data associated with one entry in a FASTA/WIG file |
| Sleipnir::SFASTASequence | Data associated with one sequence entry in a FASTA file |
| Sleipnir::SFASTAWiggle | Data associated with one value entry in a WIG file |
| Sleipnir::STermFound | Encapsulates the hypergeometric functional enrichment of a query against one ontology term |
1.5.5