Anaconda_ Python3.5+
Packages needed:
.. _Anaconda: https://www.anaconda.com/ .. _pyteomics: https://pyteomics.readthedocs.io/
Installation via pip
::
pip install diffacto
::
diffacto.py [-h] -i I [-db [DB]] [-samples [SAMPLES]] [-log2 LOG2] [-normalize {average,median,GMM,None}] [-farms_mu FARMS_MU] [-farms_alpha FARMS_ALPHA] [-reference REFERENCE] [-min_samples MIN_SAMPLES] [-use_unique USE_UNIQUE] [-impute_threshold IMPUTE_THRESHOLD] [-cutoff_weight CUTOFF_WEIGHT] [-fast FAST] [-out OUT] [-mc_out MC_OUT] optional arguments: -h, --help show this help message and exit -i I Peptides abundances in CSV format. The first row should contain names for all samples. The first column should contain unique peptide sequences. Missing values should be empty instead of zeros. (default: None) -db [DB] Protein database in FASTA format. If None, the peptide file must have protein ID(s) in the second column. (default: None) -samples [SAMPLES] File of the sample list. One run and its sample group per line, separated by tab. If None, read from peptide file headings, then each run will be summarized as a group. (default: None) -log2 LOG2 Input abundances are in log scale (True) or linear scale (False) (default: False) -normalize {average,median,GMM,None} Method for sample-wise normalization. (default: None) -farms_mu FARMS_MU Hyperparameter mu (default: 0.1) -farms_alpha FARMS_ALPHA Hyperparameter weight of prior probability (default: 0.1) -reference REFERENCE Names of reference sample groups (separated by semicolon) (default: average) -min_samples MIN_SAMPLES Minimum number of samples peptides needed to be quantified in (default: 1) -use_unique USE_UNIQUE Use unique peptides only (default: False) -impute_threshold IMPUTE_THRESHOLD Minimum fraction of missing values in the group. Impute missing values if missing fraction is larger than the threshold. (default: 0.99) -cutoff_weight CUTOFF_WEIGHT Peptides weighted lower than the cutoff will be excluded (default: 0.5) -fast FAST Allow early termination in EM calculation when noise is sufficiently small. (default: False) -out OUT Path to output file (writing in TSV format). -mc_out MC_OUT Path to MCFDR output (writing in TSV format). (default: None)
Examples are given in the example_ directory.
.. _example: ./example