similarity {similaRpeak} | R Documentation

## Calculate metrics which estimate the level of similarity between two ChIP-Seq profiles

### Description

It returns a list containing information about both ChIP-Seq profiles and a `list` of all similarity metrics: the ratio of the maximum values, the ratio of the areas, the ratio between the intersection area and the total area (for normalized and non-normalized profiles), the difference between two profiles maximal peaks positions and the Spearman's rho statistic.

### Usage

    similarity(profile1, profile2, ratioAreaThreshold = 1,
      ratioMaxMaxThreshold = 1, ratioIntersectThreshold = 1,
      ratioNormalizedIntersectThreshold = 1, diffPosMaxThresholdMinValue = 1,
      diffPosMaxThresholdMaxDiff = 100, diffPosMaxTolerance = 0.01,
      spearmanCorrSDThreashold = 1e-08)

### Arguments

`profile1` | Vector containing the RPM values of the first ChIP-Seq profile for each position of the selected region.
`profile2` | Vector containing the RPM values of the second ChIP-Seq profile for each position of the selected region.
`ratioAreaThreshold` | The minimum denominator accepted to calculate the ratio of the area between both profiles. The value has to be positive. Default = 1.
`ratioMaxMaxThreshold` | The minimum denominator accepted to calculate the ratio of the maximal peaks values between both profiles. The value has to be positive. Default = 1.
`ratioIntersectThreshold` | The minimum denominator accepted to calculate the ratio of the intersection area of both profiles over the total area. The value has to be positive. Default = 1.
`ratioNormalizedIntersectThreshold` | The minimum denominator accepted to calculate the ratio of the intersection area of both normalized profiles over the total area. The value has to be positive. Default = 1.
`diffPosMaxThresholdMinValue` | The minimum peak accepted to calculate the metric. The value has to be positive. Default = 1.
`diffPosMaxThresholdMaxDiff` | The maximum distance accepted between 2 peaks positions in one profile to calculate the metric. The value has to be positive. Default=100.
`diffPosMaxTolerance` | The maximum of variation accepted on the maximum value to consider a position as a peak position. The value can be between 0 and 1. Default=0.01.
`spearmanCorrSDThreashold` | The minimum standard deviation accepted on both profiles to calculate the metric. Default=1e-8.

### Details

`similarity` uses the two vectors passed as arguments to calculate the metrics. When the metric is a ratio, it always verify that the threshold for the denominator is respected. If the threshold is not respected, the metric is assigned the `NA` value.

### Value

A `list` containing :

- `nbrPosition` The number of positions included in each profile.

- `areaProfile1` The area of the first profile.

- `areaProfile2` The area of the second profile.

- `maxProfile1` The maximum value in the first profile.

- `maxProfile2` The maximum value in the second profile.

- `maxPositionProfile1` The list of positions of the maximum value in the first profile.

- `maxPositionProfile2` The list of positions of the maximum value in the second profile.

- `metrics` A `list` with thefollowing items:

  - `RATIO_AREA` The ratio between the areas. The larger value is always divided by the smaller value.`NA` if minimal threshold is not respected.

  - `DIFF_POS_MAX` The difference between the maximal peaks positions. The difference is always the first profile value minus the second profile value. `NA` is returned if minimal peak value is not respected. A profile can have more than one position with the maximum value. In that case, the median position is used. A threshold argument can be set to consider all positions within a certain range of the maximum value. A threshold argument can also be set to ensure that the distance between two maximum values is not too wide. When this distance is not respected, it is assumed that more than one peak is present in the profile and `NA` is returned.

  - `RATIO_MAX_MAX` The ratio between the maximal peaks values. The first profile is always divided by the second profile. `NA` if minimal threshold is not respected.

  - `RATIO_INTERSECT` The ratio between the intersection area and the total area. `NA` if minimal threshold is not respected.

  - `RATIO_NORMALIZED_INTERSECT` The ratio between the intersection area and the total area of normalized profiles. `NA` if minimal threshold is not respected.

  - `SPEARMAN_CORRELATION` The Spearman's rho statistic between profiles. `NA` if minimal threshold is not respected or when no complete element pair is present between both profiles.

### Author(s)

Astrid Deschenes, Elsa Bernatchez

### See Also

- `MetricFactory` for using a interface to calculate all available metrics separately or togheter.

- `demoProfiles` for more informations about ChIP-Seq profiles present in the demoProfiles data.

### Examples

    ## Defining two CHiP-Seq profiles
    profile1<-c(3,59,6,24,65,34,15,4,53,22,21,12,11)
    profile2<-c(15,9,46,44,9,39,27,34,34,4,3,4,2)

    ## Example usign default thresholds
    similarity(profile1, profile2)

    ## Example using customised thresholds
    similarity(profile1, profile2,
        ratioAreaThreshold=5,
        ratioMaxMaxThreshold=5,
        ratioIntersectThreshold=12,
        ratioNormalizedIntersectThreshold=2.2,
        diffPosMaxThresholdMinValue=2,
        diffPosMaxThresholdMaxDiff=130,
        diffPosMaxTolerance=0.03,
        spearmanCorrSDThreashold=1e-3)

    ## Example using ChIP-Seq profiles of H3K27ac (DCC accession: ENCFF000ASG)
    ## and H3K4me1 (DCC accession: ENCFF000ARY) from the Encyclopedia of DNA
    ## Elements (ENCODE) for the region
    data(demoProfiles)

    ## Visualize ChIP-Seq profiles
    plot(demoProfiles$chr2.70360770.70361098$H3K27ac,
        type="l", col="blue", xlab="", ylab="", ylim=c(0, 25),
        main="chr2:70360770-70361098")
    par(new=TRUE)
    plot(demoProfiles$chr2.70360770.70361098$H3K4me1,
        type="l", col="darkgreen", xlab="Position",
        ylab="Coverage in reads per million (RPM)",  ylim=c(0, 25))
    legend("topright", c("H3K27ac","H3K4me1"), cex=1.2,
        col=c("blue","darkgreen"), lty=1)

    # Calculate metrics
    similarity(demoProfiles$chr2.70360770.70361098$H3K4me1,
        demoProfiles$chr2.70360770.70361098$H3K27ac,
        ratioAreaThreshold=15,
        ratioMaxMaxThreshold=5,
        ratioIntersectThreshold=12,
        ratioNormalizedIntersectThreshold=2.2,
        diffPosMaxThresholdMinValue=2,
        diffPosMaxThresholdMaxDiff=130,
        diffPosMaxTolerance=0.03,
        spearmanCorrSDThreashold=0.1)

    ## You can refer to the vignette to see more examples using ChIP-Seq profiles
    ## extracted from the Encyclopedia of DNA Elements (ENCODE) data.

[Package similaRpeak version 1.16.0 Index]