Deseq Size Factor

Estimate DESeq-style sample size factors by median ratios to per-gene geometric means.

Description

Median-ratio size factors compare sample counts with per-gene geometric means.

Median-ratio size factors compare sample counts with per-gene geometric means. Genes containing a zero in any sample cannot supply a positive geometric reference in this implementation.^[1]

Estimate DESeq-style sample size factors by median ratios to per-gene geometric means.

When to use Deseq Size Factor

Use this tool to estimate DESeq-style sample size factors by median ratios to per-gene geometric means.

Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.

How to use Deseq Size Factor and understand its results

Prepare the upstream counts, expression values, sequences or record lists requested by this tool. Keep corresponding features in the same order and confirm count units, transformations and caller-selected criteria.
Enter geneCountsBySample using the field table and calculation rules, then run the tool.
Read sizeFactors, usedGenes. 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
geneCountsBySample	Gene counts by sample	list of list of number	Required

Enter a nonempty rectangular gene-row/sample-column matrix of nonnegative counts. Keep only rows strictly positive in every sample; at least one must remain. Compute geometric means and sample ratios, using the average of the middle two ratios for an even median. Return size factors and eligible gene count.

gm_g=exp(mean_samples ln(count_g)); factor_s=median_g(count_gs/gm_g)

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

Output field	Meaning	Value type
sizeFactors	Size factors	list of number
usedGenes	Used genes	number

json

{
  "input": {
    "geneCountsBySample": [
      [
        10,
        20
      ],
      [
        20,
        40
      ],
      [
        30,
        60
      ]
    ]
  },
  "output": {
    "sizeFactors": [
      0.7071067811865476,
      1.4142135623730951
    ],
    "usedGenes": 3
  }
}

Limitations and assumptions

No zero-tolerant variant, dispersion estimation, significance testing or full DESeq2 fit is run. Composition assumptions and feature selection affect normalization.

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 TMM Scaling Factor: Estimate an unweighted TMM-style scaling factor after trimming extreme log ratios. For a complementary task, use Counts Per Million: Convert raw feature counts into counts per million mapped reads.

References

Deseq Size Factor — tool.io

Similar or alternative tools

TMM Scaling Factor
Estimate an unweighted TMM-style scaling factor after trimming extreme log ratios.
Counts Per Million
Convert raw feature counts into counts per million mapped reads.