Description Usage Arguments Value

This function integrates the basic ABA-RSS analysis, including RSS calculation, dimension reduction for visualization using tSNE, sample (cell) clustering based on the RSS matrix, progenitor/neuron classification with potential intermediate progenitor clusters identified.

1 2 3 4 5 6 7 | ```
wrapper_ABA_RSS(input, onlyFetal = TRUE, highVar = TRUE,
tsneMethod = c("pca", "cor_dist"), tsne_pcaDim = 100,
tsne_perplexity = 50, clustMethod = c("pam", "kmeans", "pca-kmeans"),
numClust = 20, maxCells = 50000, seedset = NULL,
progenitorScores = NULL, nameMap = NULL, progenitorModel = NULL,
forceRetrain = TRUE, returnModel = TRUE, progenitorThres = 0.5,
threads = 1, verbose = TRUE)
``` |

`input` |
The input matrix of sample (cell) transcriptome profiles. Should be properly normalized and log-transformed. Its rows representing genes should be named by ENSEMBL IDs, gene symbols or Entrez IDs. |

`onlyFetal` |
Whether only considering the fetal ABA reference samples. |

`highVar` |
Whether only considering the highly variable genes across the ABA reference samples. |

`tsneMethod` |
The method used for tSNE (Rtsne). |

`tsne_pcaDim` |
When pca method is used for tSNE, it defines the initial dimension used by PCA. |

`tsne_perplexity` |
The perplexity parameter of tSNE. |

`clustMethod` |
The method used to do cell clustering. |

`numClust` |
The expected number of clusters |

`maxCells` |
The maximum number of cells selected for clustering. NULL or NA for unlimitation. |

`progenitorScores` |
The pre-calculated progenitor scores. When it is NULL, the score calculation is involved in the pipeline. |

`nameMap` |
A matrix/data.frame showing the gene name mappings. It is expected to be of multiple columns, one of which is for gene symbols. |

`progenitorModel` |
The model used for progenitor scores estimation. It is expected to be a list with at least two components: 'gene' for the list of genes to be ranked; 'coefficients' for the model coefficients. When it is NULL, either the default or a re-trained model is used. |

`forceRetrain` |
When it is TRUE, the progenitor model is always retrained using only genes appears in the input matrix. |

`returnModel` |
Whether to return the retrained model for progenitor score estimation. |

`progenitorThres` |
The progenitor score threshold to distinct progenitors and neurons |

`threads` |
The number of threads to run. |

`verbose` |
Whether to output the progress information. |

`seedIdx` |
The indices of samples (cells) used for clustering. The remaining samples will be assigned to clusters based on the SVM-classification model. |

A list with all the results involved

maplesword/RefSimSpec documentation built on May 23, 2019, 1:47 p.m.

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