scoreEucDist: Scores Euclidean distance

scoreEucDistR Documentation

Scores Euclidean distance

Description

Scores Euclidean distance

Usage

scoreEucDist(
  df,
  id,
  label_scheme_sub,
  anal_type,
  scale_log2r,
  adjEucDist = FALSE,
  ...
)

Arguments

df

The name of a primary data file. By default, it will be determined automatically after matching the types of data and analysis with an id among c("pep_seq", "pep_seq_mod", "prot_acc", "gene"). A primary file contains normalized peptide or protein data and is among c("Peptide.txt", "Peptide_pVal.txt", "Peptide_impNA_pVal.txt", "Protein.txt", "Protein_pVal.txt", "protein_impNA_pVal.txt"). For analyses require the fields of significance p-values, the df will be one of c("Peptide_pVal.txt", "Peptide_impNA_pVal.txt", "Protein_pVal.txt", "protein_impNA_pVal.txt").

id

Character string; one of pep_seq, pep_seq_mod, prot_acc and gene.

label_scheme_sub

A data frame. Subset entries from label_scheme for selected samples.

anal_type

Character string; the type of analysis that are preset for method dispatch in function factories. The value will be determined automatically. Exemplary values include anal_type = c("PCA", "Corrplot", "EucDist", "GSPA", "Heatmap", "Histogram", "MDS", "Model", "NMF", "Purge", "Trend", "LDA", ...).

scale_log2r

Logical; if TRUE, adjusts log2FC to the same scale of standard deviation across all samples. The default is TRUE. At scale_log2r = NA, the raw log2FC without normalization will be used.

adjEucDist

Logical; if TRUE, adjusts the inter-plex Euclidean distance by 1/sqrt(2) at method = "euclidean". The option adjEucDist = TRUE may be suitable when reference samples from each TMT plex undergo approximately the same sample handling process as the samples of interest. For instance, reference samples were split at the levels of protein lysates. Typically, adjEucDist = FALSE if reference samples were split near the end of a sample handling process, for instance, at the stages immediately before or after TMT labeling. Also see online README, section MDS for a brief reasoning.

...

filter_: Variable argument statements for the row filtration against data in a primary file linked to df. See also normPSM for the format of filter_ statements.

arrange_: Variable argument statements for the row ordering against data in a primary file linked to df. See also prnHM for the format of arrange_ statements.

Additional parameters for plotting:
width, the width of plot
height, the height of plot

Additional arguments for pheatmap:
cluster_rows, clustering_method, clustering_distance_rows...

Notes about pheatmap:
annotation_col disabled; instead use keys indicated in annot_cols
annotation_row disabled; instead use keys indicated in annot_rows


qzhang503/proteoQ documentation built on March 16, 2024, 5:27 a.m.