Installation

The CSCSomics can be easily installed via conda, make sure conda-forge and bioconda channels are added.

conda create -n cscsomics -c agusinac cscsomics

Usage

In the test directory, test cases for metagenomics, proteomics and metabolomics can be found.

The order of FASTA file and abundances after the -i argument is not important for metagenomics and proteomics.

• Metagenomics example:

python CSCSomics.py -m metagenomics -i features.fasta abundances.tsv -o [DIRECTORY] 

• Proteomics example:

python CSCSomics.py -m proteomics -i features.fasta abundances.tsv -o [DIRECTORY] 

The order of features and abundances is important for metabolomics. Make sure that the input files are in the order of features.tsv followed by abundances.tsv as shown in the example below.

• Metabolomics example:

python CSCSomics.py -m metabolomics -i features.tsv abundances.tsv -o [DIRECTORY] 

Options

usage: CSCSomics    [-h,    --help]
                    [-i,    --input INPUT_FILES]
                    [-o,    --output OUTPUT DIRECTORY]
                    [-md,   --metadata [INPUT_FILE COLUMN_ID COLUMN_GROUP]
                    [-m,    --mode MODE] 
                    [-n,    --normalise NORM] 
                    [-w,    --weight WEIGHT] 
                    [-s,    --seed SEED] 
                    [-it,   --iterations NUM_ITERS]
                    [-c,    --cores NUM_CORES]
                    [-t,    --threads MKL_THREADS]

• In principel INPUT FILES require a features or abundances file, unless custom mode is selected. Then the following scenario is applied:

--input [DISTANCE_MATRIX] -m custom

• PERMANOVA and PCoA graphs requires metadata file and columns for samples ID and the grouping column.

--metadata [METADATA FILE] [COLUMN ID] [COLUMN_GROUP]