score_matrix {scone} | R Documentation

## SCONE Evaluation: Evaluate an Expression Matrix

### Description

This function evaluates a (normalized) expression matrix using SCONE criteria, producing 8 metrics based on i) Clustering, ii) Correlations and iii) Relative Expression.

### Usage

    score_matrix(
      expr,
      eval_pcs = 3,
      eval_proj = NULL,
      eval_proj_args = NULL,
      eval_kclust = NULL,
      bio = NULL,
      batch = NULL,
      qc_factors = NULL,
      uv_factors = NULL,
      wv_factors = NULL,
      is_log = FALSE,
      stratified_pam = FALSE,
      stratified_cor = FALSE,
      stratified_rle = FALSE
    )

### Arguments

`expr` | matrix. The expression data matrix (genes in rows, cells in columns).
`eval_pcs` | numeric. The number of principal components to use for evaluation (Default 3). Ignored if !is.null(eval_proj).
`eval_proj` | function. Projection function for evaluation (see Details). If NULL, PCA is used for projection
`eval_proj_args` | list. List of arguments passed to projection function as eval_proj_args (see Details).
`eval_kclust` | numeric. The number of clusters (> 1) to be used for pam tightness (PAM_SIL) evaluation. If an array of integers, largest average silhouette width (tightness) will be reported in PAM_SIL. If NULL, PAM_SIL will be returned NA.
`bio` | factor. A known biological condition (variation to be preserved), NA is allowed. If NULL, condition ASW, BIO_SIL, will be returned NA.
`batch` | factor. A known batch variable (variation to be removed), NA is allowed. If NULL, batch ASW, BATCH_SIL, will be returned NA.
`qc_factors` | Factors of unwanted variation derived from quality metrics. If NULL, qc correlations, EXP_QC_COR, will be returned NA.
`uv_factors` | Factors of unwanted variation derived from negative control genes (evaluation set). If NULL, uv correlations, EXP_UV_COR, will be returned NA.
`wv_factors` | Factors of wanted variation derived from positive control genes (evaluation set). If NULL, wv correlations, EXP_WV_COR, will be returned NA.
`is_log` | logical. If TRUE the expr matrix is already logged and log transformation will not be carried out prior to projection. Default FALSE.
`stratified_pam` | logical. If TRUE then maximum ASW is separately computed for each biological-cross-batch stratum (accepts NAs), and a weighted average silhouette width is returned as PAM_SIL. Default FALSE.
`stratified_cor` | logical. If TRUE then cor metrics are separately computed for each biological-cross-batch stratum (accepts NAs), and weighted averages are returned for EXP_QC_COR, EXP_UV_COR, & EXP_WV_COR. Default FALSE.
`stratified_rle` | logical. If TRUE then rle metrics are separately computed for each biological-cross-batch stratum (accepts NAs), and weighted averages are returned for RLE_MED & RLE_IQR. Default FALSE.

### Details

Users may specify their own eval_proj function that will be used to compute Clustering and Correlation metrics. This eval_proj() function must have 2 input arguments:

- e matrix. log-transformed (+ pseudocount) expression data (genes in rows, cells in columns).

- eval_proj_args list. additional function arguments, e.g. prior data weights.

and it must output a matrix representation of the original data (cells in rows, factors in columns). The value of eval_proj_args is passed to the user-defined function from the eval_proj_args argument of the main score_matrix() function call.

### Value

A list with the following metrics:

- BIO_SIL Average silhouette width by biological condition.

- BATCH_SIL Average silhouette width by batch condition.

- PAM_SIL Maximum average silhouette width from PAM clustering (see stratified_pam argument).

- EXP_QC_COR Coefficient of determination between expression pcs and quality factors (see stratified_cor argument).

- EXP_UV_COR Coefficient of determination between expression pcs and negative control gene factors (see stratified_cor argument).

- EXP_WV_COR Coefficient of determination between expression pcs and positive control gene factors (see stratified_cor argument).

- RLE_MED The mean squared median Relative Log Expression (RLE) (see stratified_rle argument).

- RLE_IQR The variance of the inter-quartile range (IQR) of the RLE (see stratified_rle argument).

### Examples

    set.seed(141)
    bio = as.factor(rep(c(1,2),each = 2))
    batch = as.factor(rep(c(1,2),2))
    log_expr = matrix(rnorm(20),ncol = 4)

    scone_metrics = score_matrix(log_expr,
       bio = bio, batch = batch,
       eval_kclust = 2, is_log = TRUE)

[Package scone version 1.18.0 Index]