Useful scripts

A repository of scripts/code used across multiple projects.

asm_stats.py

• Calculates common assembly statistics for one or more FASTA files.
• Input: takes either a single FASTA or a directory of FASTA files.

Usage:

asm_stats.py --fasta <FASTA>

asm_stats.py --fasta_dir <fasta_dir/>

Parameters:

  -f FILE, --file FILE            Input FASTA file
  --fasta_dir FASTA_DIR           Directory containing FASTA files
  --fasta FASTA                   Single FASTA file
  --gap GAP                       Minimum gap length to be considered a scaffold (optional) [2]
  --output OUTPUT                 Output file prefix (optional) ['sample']
  --version                       Show program's version number and exit

• Output: CSV file containing assembly metrics with columns:
  • sampleid : Based on the first part of the input fasta (delimeter: '.')
  • assembly_length_bp : Assembly length (bp)
  • scaffold_count : Number of scaffolds
  • scaffold_N50_bp : Scaffold N₅₀ (bp)
  • scaffold_N90_bp : Scaffold N₉₀ (bp)
  • contig_count : Number of contigs
  • contig_N50_bp : Contig N₅₀ (bp)
  • contig_N90_bp : Contig N₉₀ (bp)
  • GC_perc : GC content (%)
  • gaps_count : Number of gaps (min length to define a gap can be changed with --gap parameter)
  • gaps_sum_bp : Total gap length (bp)
  • gaps_perc : Proportion of genome composed of gaps (%)

ari.py

• Calculates the Adjusted Rand Index between clusters schemes.
• Input: takes tab or comma separated files (works on any number of files ≥ 2).
• Input format: sample_name,cluster_id

Usage:

ari.py <file1> <file2> <file3>

• Output: pairwise ARI values in both list and matrix format

code_similarity.py

• Calculates the Cosine similarity, Jaccard similarity, longest common substring and Abstract Syntax Tree (optional, not fully tested) between different input files.
• Input: two directories of files to be compared (at present must be .md, .R or .py files)

Usage:

code_similarity.py --dir1 <first directory/> --dir2 <second directory/>

Parameters:

options:
  -h, --help          show this help message and exit
  --dir1 DIR1         Path to the first directory of scripts
  --dir2 DIR2         Path to the second directory of scripts
  --include-comments  Include comments in the similarity comparison
  --enable-ast        Enable AST-based similarity comparison for Python files
  --keep-duplicates   Keep duplicate lines in the similarity comparison

• Output: pairwise ARI values in both list and matrix format

count_file_differences.py [ Note: not fully tested ]

• Counts the pairwise row and column differences between files.
• Input: two directories of CSV files to be compared.

Usage:

code_similarity.py --dir1 <first directory/> --dir2 <second directory/> --output <output file prefix>

Parameters:

options:
  -h, --help       show this help message and exit
  --dir1 DIR1      Path to the first directory
  --dir2 DIR2      Path to the second directory
  --output OUTPUT  Output TSV file for comparison results

• Output: 3 files:
  • {prefix}.tsv: Pairwise comparisons between two files, with filenames (cols 1&2), counts of differences by row (col3) or column (col4), names of rows that have changed (col5) and names of columns that have changed (col6)
  • {prefix}.row_diff_matrix.tsv: Matrix of pariwise row differences (counts)
  • {prefix}.col_diff_matrix.tsv: Matrix of pariwise column differences (counts)

fa_select.py

• Calculates the Adjusted Rand Index between clusters schemes.
• Input: FASTA file

Usage:

fa_select.py -f <FASTA>

Parameters:

-f FILE, --file FILE            Input FASTA file
-s, --sort                      Sort by header name
-l LENGTH, --length LENGTH      Keep only contigs longer than the specified length
-p PREFIX, --prefix PREFIX      Append prefix to each contig header
-i INCLUDE, --include INCLUDE   File with list of contig headers to include
-e EXCLUDE, --exclude EXCLUDE   File with list of contig headers to exclude
-o OUTPUT, --output OUTPUT      Output file name
-v, --version                   Show program's version number and exit

• Output: FASTA file

split_spreadsheet.py

• Converts an excel spreadsheet into individual, named after each tab name.

Usage:

split_spreadsheet.py -e <spreadsheet> -o  <output directory name>

Parameters:

options:
-h, --help            show this help message and exit
-e EXCEL_FILE_PATH, --excel_file_path EXCEL_FILE_PATH
                      Path to the Excel file.
-o OUTPUT_DIRECTORY, --output_directory OUTPUT_DIRECTORY
                      Directory to save the output files.
-f {csv,tsv}, --format {csv,tsv}
                      Output format: csv or tsv (default: csv)

• Output: Directory with individual TSV or CSV files

switch_names.py

• Switches the names of two files.

Usage:

switch_names.py --file1 <first_file> --file2 <second_file>

unique_values.py

• For a specified column, returns one representative row containing each unique value in the dataframe. Similiar to 'uniq' on a single column but returns the whole row.
• Input: takes a tab separated file with a header (relevant column must be specified with the --col parameter) and --mode determines whether the first row in a dataframe containing the value is retained or a row is randomly selected.

Usage:

unique_values.py --input <input file> --col <column name> --mode <first|random>