These Python scripts create metrics and graphs from genome assemblies.

To use, first install the dependancies with conda install biopython matplotlib. After that, edit the input.csv file to match your situation. Then you can run the image and stats generating script with:

python AssemblyStats.py input.fasta or

python AssemblyStats.py input.fasta input.fasta.gz input.fasta.bz2 or

python AssemblyStats.py input.csv

The CSV (comma separated) columns are: Seq_Name Seq_File

Spaces are allowed. The order in the file will define the order in the graphics legend. You can comment lines with # First line HAS to be the title: Seq_Name,Seq_File

To change the output of the graph, one can set a couple of environment values. These are :

MAX_CONTIGS
MIN_LENGTH
TITLE
TYPE
EXPECTED_GENOME_SIZE

So an example looks like this :

export TITLE="103"
export MAX_CONTIGS=4000
export MIN_LENGTH=100
python ~/A50-plot/AssemblyStats.py 103_assemblies.csv > 103.stats

To parse the output to human readable, one can use this : cat 103.stats | tr ',' '\t' | numfmt --header --field 2-5,7-18,20 --grouping | numfmt --header --field 6,19,21 --format '%.1f' | column -t

This then results in:

Name                      Count  Sum            Max         Min  Average   Median  N50         L50  NG50  LG50  N90        L90  N95        L95  Count>1000  Count>10000  #GC            GC    #N     N
103/assembly.fasta        3,467  3,002,559,922  53,397,245  104  866039.8  6,152   10,128,795  77   0     0     2,373,600  302  1,366,482  382  2,897       1,327        1,045,685,741  34.9  5,100  0.1
103_final/assembly.fasta  3,636  3,006,248,922  40,557,336  104  826801.2  5,803   11,571,573  76   0     0     2,427,154  296  1,406,690  374  3,019       1,323        1,047,101,522  34.9  4,800  0.1
103_pbont/assembly.fasta  3,547  3,007,150,960  38,923,932  100  847801.3  5,785   11,975,311  76   0     0     2,910,579  273  1,394,760  344  2,870       1,297        1,047,384,588  34.9  5,500  0.1

As I had not entered the expected genome size, the NG50 and LG50 are zero.

The image output of the script looks like this :