assess_quality          Assess quality information of features
citations               Show citations
cluster_features        Cluster correlated features originating from
                        the same metabolite
combined_data           Retrieve both sample information and features
compress_clusters       Compress clusters of features to a single
                        feature
correct_drift           Correct drift using cubic spline
drop_flagged            Drop flagged features
drop_qcs                Drop QC samples
finish_log              Finish a log
fix_MSMS                Transform the MS/MS output to publication ready
fix_object              Fix object for functioning of notame
flag                    Get and set the values in the flag column
flag_contaminants       Flag contaminants based on blanks
flag_detection          Flag features with low detection rate
flag_quality            Flag low-quality features
flag_report             A report of flagged features
import_from_excel       Read formatted Excel files
impute_rf               Impute missing values using random forest
impute_simple           Simple imputation
init_log                Initialize log to a file
inverse_normalize       Inverse-rank normalization
join_colData            Join new columns to pheno data
join_rowData            Join new columns to feature data
log_text                Log text to the current log file
mark_nas                Mark specified values as missing
merge_notame_sets       Merge SummarizedExperiment objects together
notame-package          'notame' package.
pca_bhattacharyya_dist
                        Bhattacharyya distance between batches in PCA
                        space
perform_repeatability   Compute repeatability measures
pqn_normalization       Probabilistic quotient normalization
quality                 Extract quality information of features
ruvs_qc                 Remove Unwanted Variation (RUV) between batches
toy_notame_set          Toy data set
write_to_excel          Write results to Excel file
