calculate_autocorrelation {PrInCE} | R Documentation

## Calculate the autocorrelation for each protein between a pair of co-elution experiments.

### Description

For a given protein, the correlation coefficient to all other proteins in the first condition is calculated, yielding a vector of correlation coefficients. The same procedure is repeated for the second condition, and the two vectors of correlation coefficients are themselves correlated, yielding a metric whereby higher values reflect proteins with unchanging interaction profiles between conditions, while lower values reflect proteins with substantially changing interaction profiles.

### Usage

    calculate_autocorrelation(
      profile1,
      profile2,
      cor_method = c("pearson", "spearman", "kendall"),
      min_replicates = 1,
      min_fractions = 1,
      min_pairs = 0
    )

### Arguments

`profile1` | a numeric matrix or data frame with proteins in rows and fractions in columns, or a `MSnSet` object, representing the first co-elution condition
`profile2` | a numeric matrix or data frame with proteins in rows and fractions in columns, or a `MSnSet` object, representing the second co-elution condition
`cor_method` | the correlation method to use; one of `"pearson"`, `"spearman"`, or `"kendall"`).
`min_fractions` | filter proteins not quantified in at least this many fractions
`min_pairs` | remove correlations between protein pairs not co-occuring in at least this many fractions from the autocorrelation calculation

### Details

Note that all of zero, `NA`, `NaN`, and infinite values are all treated equivalently as missing values when applying the `min_fractions` and `min_pairs` filters, but different handling of missing values will produce different autocorrelation scores.

### Value

a named vector of autocorrelation scores for all proteins found in both matrices.

[Package PrInCE version 1.10.0 Index]