Metabolite Transcript Correlation

Build a metabolite-by-transcript Pearson correlation matrix.

Description

Profile correlation compares metabolite and transcript variation across the same observations.

Profile correlation compares metabolite and transcript variation across the same observations. Pearson coefficients describe linear association after centering each profile.^[1]

Build a metabolite-by-transcript Pearson correlation matrix.

When to use Metabolite Transcript Correlation

Use this tool to build a metabolite-by-transcript Pearson correlation matrix.

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.

How to use Metabolite Transcript Correlation and understand its results

Prepare the measured profile, formula counts, upstream model outputs or caller-defined reference criteria requested. Keep paired entries aligned and units, sample basis and preprocessing consistent.
Enter metaboliteProfiles, transcriptProfiles using the field table and calculation rules, then run the tool.
Read pearsonMatrix. The explanation below defines the units, signs, ordering and any flags or placeholder values.
If the tool reports an input issue, correct the values and run it again. Apply the stated assumptions when interpreting a successfully returned result.

Input field	Meaning	Value type; see rules below	Requirement
metaboliteProfiles	Metabolite profiles	list of list of number	Required
transcriptProfiles	Transcript profiles	list of list of number	Required

Enter nonempty metabolite and transcript matrices with equal observation widths of at least two and variation in every row. Return the matrix with metabolite rows and transcript columns. Coefficients within 1e−12 of ±1 are snapped to that endpoint.

r_xy=Σ(x−meanX)(y−meanY)/(||x−meanX|| ||y−meanY||)

Units, indexing, boundary conditions and exceptional cases are defined in the calculation rules above.

Output field	Meaning	Value type
pearsonMatrix	Pearson matrix	list of list of number

json

{
  "input": {
    "metaboliteProfiles": [
      [
        1,
        2,
        3
      ],
      [
        3,
        2,
        1
      ]
    ],
    "transcriptProfiles": [
      [
        2,
        4,
        6
      ],
      [
        3,
        2,
        1
      ]
    ]
  },
  "output": {
    "pearsonMatrix": [
      [
        1,
        -1
      ],
      [
        -1,
        1
      ]
    ]
  }
}

Limitations and assumptions

No sample alignment, normalization, p-value or causal association is established.

Numeric inputs must be finite. Follow the calculation-specific rules for overflow, underflow and exceptional cases. Matrices are limited to 128 rows and 128 entries per row; other lists are limited to 100,000 entries. Missing required fields, extra fields, wrong value types and violations of the calculation rules are input errors.

Alternative or Complementary methods

Use Unit Variance Scaling: Autoscale a feature to zero mean and unit population variance. For a complementary task, use Empirical Permutation P: Estimate permutation p-value with plus-one correction.

References

Metabolite Transcript Correlation — tool.io

Similar or alternative tools

Unit Variance Scaling
Autoscale a feature to zero mean and unit population variance.
Empirical Permutation P
Estimate permutation p-value with plus-one correction.