analTrend: Trend analysis

In qzhang503/proteoQ: Processing and Informatic Analysis of Mass Spectrometrirc Data

Trend analysis

Description

Trend analysis

Usage

analTrend(
  df,
  id,
  col_group,
  col_order,
  label_scheme_sub,
  choice,
  n_clust,
  scale_log2r,
  complete_cases,
  impute_na,
  filepath,
  filename,
  anal_type,
  ...
)

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.
col_group	Character string to a column key in expt_smry.xlsx. Samples corresponding to non-empty entries under col_group will be used for sample grouping in the indicated analysis. At the NULL default, the column key Group will be used. No data annotation by groups will be performed if the fields under the indicated group column is empty.
col_order	Character string to a column key in expt_smry.xlsx. Numeric values under which will be used for the left-to-right arrangement of samples in graphic outputs or top-to-bottom arrangement in text outputs. At the NULL default, the column key Order will be used. If values under column Order are left blank, samples will be ordered by their names.
label_scheme_sub	A data frame. Subset entries from label_scheme for selected samples.
choice	Character string; the clustering method in c("cmeans", "clara", "kmeans", "pam", "fanny"). The default is "cmeans".
n_clust	Numeric vector; the number(s) of clusters that data will be divided into. At the NULL default, it will be determined by the gap method in clusGap. The n_clust overwrites the argument centers in cmeans.
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.
complete_cases	Logical; if TRUE, only cases that are complete with no missing values will be used. The default is FALSE.
impute_na	Logical; if TRUE, data with the imputation of missing values will be used. The default is FALSE.
filepath	Use system default.
filename	A representative file name to outputs. By default, it will be determined automatically by the name of the current call.
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", ...).
...	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 arguments for cmeans, kmeans, clara, pam. Note that centers in cmeans or kmeans is replaced with n_clust. The same applies to k in clara or pam. With cmeans, m is according to Schwaemmle and Jensen if not provided; x is disabled with input data being determined automatically.

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