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library(ggplot2) | |
library(reshape2) | |
# Load data, and rerank teams by points | |
data = read.table("SL_points.txt", sep="\t", header=T) | |
data$old_rank = rank(-data$Old, ties.method="first") | |
data$bonus_rank = rank(-data$Bonus, ties.method="first") | |
data$penalty_rank = rank(-data$Penalty, ties.method="first") | |
# New dataframe of ranked teams under each scheme |
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from KGML_scrape import retrieve_kgml_to_file | |
retrieve_kgml_to_file('ddc00190', 'ddc00190.kgml') |
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In [1]: from KGML_scrape import * | |
In [2]: ex1 = retrieve_kgml('eco00010') | |
In [3]: ex1[:100] | |
Out[3]: '<?xml version="1.0"?>\n<!DOCTYPE pathway SYSTEM "http://www.genome.jp/kegg/xml/KGML_v0.7.1_.dtd">\n<!-' | |
In [4]: ex2 = retrieve_kgml_stream('ype02040') | |
In [5]: type(ex2) | |
Out[5]: instance | |
In [6]: ex2.readline() | |
Out[6]: '<?xml version="1.0"?>\n' | |
In [7]: ex3 = retrieve_KEGG_pathway('ara01120') |
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import KGML_parser | |
from KGML_scrape import retrieve_KEGG_pathway | |
from KGML_vis import KGMLCanvas | |
# Get the ko01110 map from KEGG, and write it out to file, visualised as | |
# the .png, and as the elements from the KGML file | |
pathway = retrieve_KEGG_pathway('ko01110') | |
kgml_map = KGMLCanvas(pathway, show_maps=True) | |
# Default settings are for the KGML elements only | |
kgml_map.draw('ex1_kgml_render.pdf') |
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import KGML_parser | |
from KGML_scrape import retrieve_KEGG_pathway | |
from KGML_vis import KGMLCanvas | |
from Bio.Graphics.ColorSpiral import ColorSpiral | |
# Get the ko03070 map from KEGG, and write it out to file, visualised as | |
# the .png, and as the elements from the KGML file | |
pathway = retrieve_KEGG_pathway('ko03070') | |
kgml_map = KGMLCanvas(pathway, show_maps=True) |
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import KGML_parser | |
from KGML_scrape import retrieve_KEGG_pathway | |
from KGML_vis import KGMLCanvas | |
# Get list of pathway elements to enhance | |
glyc_path = retrieve_KEGG_pathway('ko00010') | |
tca_path = retrieve_KEGG_pathway('ko00020') | |
enhance_list = [] | |
for pathway in (glyc_path, tca_path): | |
for e in pathway.entries.values(): |
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ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_chlorochromatii_CaD3_uid58375/NC_007514.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_limicola_DSM_245_uid58127/NC_010803.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_luteolum_DSM_273_uid58175/NC_007512.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_phaeobacteroides_BS1_uid58131/NC_010831.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_phaeobacteroides_DSM_266_uid58133/NC_008639.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_phaeovibrioides_DSM_265_uid58129/NC_009337.fna | |
ftp://ftp.ncbi.nih.gov/genomes/Bacteria/Chlorobium_tepidum_TLS_uid57897/NC_002932.fna |
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mkdir test_isolates | |
cd test_isolates/ | |
wget -i chlorobium.txt | |
cd .. |
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time python calculate_ani.py -i test_isolates/ -m ANIb -o chlorobium_anib -g -v -l chlorobium_anib.log | |
time python calculate_ani.py -i test_isolates/ -m ANIm -o chlorobium_anim -g -v -l chlorobium_anim.log | |
time python calculate_ani.py -i test_isolates/ -m TETRA -o chlorobium_tetra -g -v -l chlorobium_tetra.log |
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time python calculate_ani.py -i test_anaplasma/ -m ANIb -o anaplasma_anib -g | |
time python calculate_ani.py -i test_anaplasma/ -m ANIb -o anaplasma_anib -g -v --noclobber -f --format png --skip_blast | |
time python calculate_ani.py -i test_anaplasma/ -m ANIm -o anaplasma_anim -g -v | |
time python calculate_ani.py -i test_anaplasma/ -m ANIm -o anaplasma_anim -g -v --noclobber -f --format png --skip_nucmer | |
time python calculate_ani.py -i test_anaplasma/ -m TETRA -o anaplasma_tetra -g -v -f | |
time python calculate_ani.py -i test_anaplasma/ -m TETRA -o anaplasma_tetra -g -v -f --format png |
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