https://github.com/haydeeperuyero/pangenome_

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Repository

Basic Info

Host: GitHub
Owner: HaydeePeruyero
Language: R
Default Branch: main
Homepage: https://haydeeperuyero.github.io/Pangenome_/
Size: 13.7 MB
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Created over 3 years ago · Last pushed over 3 years ago
Metadata Files

Readme
README.html














README


























































Pangenome
Pangenome analysis


Conectarse
ssh nombre@servidior
password
{: .language-bash}
Moverse a la carpeta
cd carpeta
{: .language-bash}

Make blast
Concatenar archivos y correr BLAST con la opción de prot
porque son Pangenomas.
cat Haydee/data/*.faa > all-genomes.faa
cd ~/Haydee/blast/output-blast/
makeblastdb -in ~/Haydee/data/all-genomes.faa -dbtype prot -out ~/Haydee/blast/database/all-genomes
{: .language-bash}
cat: /home/betterlab/Haydee/data/all-genomes.faa: input file is output file
Adding sequences from FASTA; added 27811 sequences in 4.72535 seconds.
{: .output}
#blastp blastp -query ~/Haydee/data/all-genomes.faa -db ~/Haydee/blast/all-genomes -outfmt "6" > all-genomes.blast
#Algunas de las posibles opciones: "6 qseqid sseqid pident length mismatch gapopen qstart qend sstart send evalue bitscore"
#Para dejar corriendo en la terminal
nohup blastp -query ~/Haydee/data/all-genomes.faa -db ~/Haydee/blast/all-genomes -outfmt "6" > all-genomes.blast &
{: .language-bash}
Copiar los archivos a local desde otra terminal. ~~~ scp servidor@servidor:/home/betterlab/Haydee/blast/all-genomes.blast
. ~~~ {: .language-bash}
Default values for output: ~~~ -outfmt “6 qseqid sseqid pident length
mismatch gapopen qstart qend sstart send evalue bitscore” ~~~ {:
.language-bash}

qseqid: Query Seq-id
sseqid: Subject Seq-id
pident: Percentage of identical matches
length: Alignment length
mismatch Number of mismatches
gapopen: Number of gap openings
qstart: Start of alignment in query
qend: End of alignment in query
sstart: Start of alignment in subject
send: End if alignment in subject
evalue: Expect value
bitscore: Bit score

Explore de dataset.
data <- read.delim("~/Pangenome/all-genomes.blast", header=FALSE)
head(data)
{: .language-bash}
                   V1                     V2      V3 V4 V5 V6 V7 V8 V9 V10      V11 V12
1 fig|2692915.4.peg.1    fig|2692915.4.peg.1 100.000 88  0  0  1 88  1  88 1.45e-62 183
2 fig|2692915.4.peg.1 fig|2692915.4.peg.7369  97.727 88  2  0  1 88  1  88 1.88e-61 180
3 fig|2692915.4.peg.1 fig|2692915.4.peg.3260  79.310 87 18  0  1 87  1  87 6.97e-47 153
4 fig|2692915.4.peg.1 fig|2692915.4.peg.1536  67.045 88 29  0  1 88  1  88 1.08e-41 132
5 fig|2692915.4.peg.1 fig|2692915.4.peg.1153  64.045 89 30  1  1 87  1  89 4.03e-39 132
6 fig|2692915.4.peg.1 fig|2692915.4.peg.5246 100.000 51  0  0  1 51  1  51 1.59e-33 108
{: .output}



Get_homologues
Crear carpeta con todos los archivos .faa (o .gbk) para
después si es necesario añadir más archivos. El siguiente código corre
get_homologues en todos los archivos de la carpeta con los archivos
.faa.
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ get_homologues.pl -d data_get -c
{: .language-bash}
Se obtiene lo siguiente (tarda al rededor de 20min.).
# /opt/anaconda3/envs/Pangenomics_Global/bin/get_homologues.pl -i 0 -d data_get -o 0 -X 0 -e 0 -f 0 -r 0 -t all -c 1 -z 0 -I 0 -m local -n 2 -M 0 -G 0 -p 0 -C 75 -S 1 -E 1e-05 -F 1.5 -N 0 -B 50 -b 0 -s 0 -D 0 -g 0 -a '0' -x 0 -R 0 -A 0 -P 0

# version 28042022
# results_directory=/home/alumno5/Haydee/data_get_homologues
# parameters: MAXEVALUEBLASTSEARCH=0.01 MAXPFAMSEQS=250 BATCHSIZE=100 KEEPSCNDHSPS=1
# diamond job:0

# checking input files...
# 2692915.4.faa 8802
# 287862.3.faa 8982
# 287863.3.faa 8982

# 3 genomes, 26766 sequences

# taxa considered = 3 sequences = 26766 residues = 7168829 MIN_BITSCORE_SIM = 18.7

# mask=2692915_f0_alltaxa_algBDBH_e0_ (_algBDBH)

# running makeblastdb with /home/alumno5/Haydee/data_get_homologues/2692915.4.faa.fasta

# running makeblastdb with /home/alumno5/Haydee/data_get_homologues/287862.3.faa.fasta

# running makeblastdb with /home/alumno5/Haydee/data_get_homologues/287863.3.faa.fasta

# running BLAST searches ...
# done

# concatenating and sorting BLAST/DIAMOND results...
# sorting _2692915.4.faa results (19MB)
# sorting _287862.3.faa results (19MB)
# sorting _287863.3.faa results (19MB)
# done


# parsing blast result! (/home/alumno5/Haydee/data_get_homologues/tmp/all.blast , 56MB)
# parsing file finished

# creating indexes, this might take some time (lines=7.70e+05) ...

# construct_taxa_indexes: number of taxa found = 3
# number of file addresses/BLAST queries = 2.7e+04

# genome composition report (samples=6,permutations=6,seed=0)
# genomic composition parameters: MIN_PERSEQID_HOM=0 MIN_COVERAGE_HOM=20 (set in lib/marfil_homology.pm)
# genome order:
# 0 2692915.4.faa
# 1 287862.3.faa
# 2 287863.3.faa

## sample 0 (2692915.4.faa | 0,1,2,)
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# adding 2692915.4.faa: core=8204 pan=8204
# clustering inparalogues in 287862.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287862.3.faa
# 4644 sequences
# finding homologs between 287862.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287862.3.faa: core=4644 pan=10648
# clustering inparalogues in 287863.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287863.3.faa
# 4644 sequences
# finding homologs between 287863.3.faa and 287862.3.faa
# 8979 sequences
# finding homologs between 287863.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287863.3.faa: core=4644 pan=10651
## sample 1 (287863.3.faa | 2,0,1,)
# clustering inparalogues in 287863.3.faa
# 515 sequences
# adding 287863.3.faa: core=8685 pan=8685
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# finding BDBHs between 287863.3.faa and 2692915.4.faa
# 4644 sequences
# finding homologs between 2692915.4.faa and 287863.3.faa
# 6496 sequences
# adding 2692915.4.faa: core=4644 pan=10863
# clustering inparalogues in 287862.3.faa
# 515 sequences
# finding BDBHs between 287863.3.faa and 287862.3.faa
# 8679 sequences
# finding homologs between 287862.3.faa and 2692915.4.faa
# 6529 sequences
# finding homologs between 287862.3.faa and 287863.3.faa
# 8979 sequences
# adding 287862.3.faa: core=4644 pan=10866
## sample 2 (2692915.4.faa | 0,2,1,)
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# adding 2692915.4.faa: core=8204 pan=8204
# clustering inparalogues in 287863.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287863.3.faa
# 4644 sequences
# finding homologs between 287863.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287863.3.faa: core=4644 pan=10648
# clustering inparalogues in 287862.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287862.3.faa
# 4644 sequences
# finding homologs between 287862.3.faa and 287863.3.faa
# 8979 sequences
# finding homologs between 287862.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287862.3.faa: core=4644 pan=10651
## sample 3 (2692915.4.faa | 0,1,2,)
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# adding 2692915.4.faa: core=8204 pan=8204
# clustering inparalogues in 287862.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287862.3.faa
# 4644 sequences
# finding homologs between 287862.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287862.3.faa: core=4644 pan=10648
# clustering inparalogues in 287863.3.faa
# 515 sequences
# finding BDBHs between 2692915.4.faa and 287863.3.faa
# 4644 sequences
# finding homologs between 287863.3.faa and 287862.3.faa
# 8979 sequences
# finding homologs between 287863.3.faa and 2692915.4.faa
# 6529 sequences
# adding 287863.3.faa: core=4644 pan=10651
## sample 4 (287862.3.faa | 1,0,2,)
# clustering inparalogues in 287862.3.faa
# 515 sequences
# adding 287862.3.faa: core=8685 pan=8685
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# finding BDBHs between 287862.3.faa and 2692915.4.faa
# 4644 sequences
# finding homologs between 2692915.4.faa and 287862.3.faa
# 6496 sequences
# adding 2692915.4.faa: core=4644 pan=10863
# clustering inparalogues in 287863.3.faa
# 515 sequences
# finding BDBHs between 287862.3.faa and 287863.3.faa
# 8679 sequences
# finding homologs between 287863.3.faa and 2692915.4.faa
# 6529 sequences
# finding homologs between 287863.3.faa and 287862.3.faa
# 8979 sequences
# adding 287863.3.faa: core=4644 pan=10866
## sample 5 (287863.3.faa | 2,1,0,)
# clustering inparalogues in 287863.3.faa
# 515 sequences
# adding 287863.3.faa: core=8685 pan=8685
# clustering inparalogues in 287862.3.faa
# 515 sequences
# finding BDBHs between 287863.3.faa and 287862.3.faa
# 8679 sequences
# finding homologs between 287862.3.faa and 287863.3.faa
# 8979 sequences
# adding 287862.3.faa: core=8679 pan=8688
# clustering inparalogues in 2692915.4.faa
# 914 sequences
# finding BDBHs between 287863.3.faa and 2692915.4.faa
# 4644 sequences
# finding homologs between 2692915.4.faa and 287862.3.faa
# 6496 sequences
# finding homologs between 2692915.4.faa and 287863.3.faa
# 6496 sequences
# adding 2692915.4.faa: core=4644 pan=10866

# pan-genome (number of genes, can be plotted with plot_pancore_matrix.pl)
# file=data_get_homologues/pan_genome_algBDBH.tab
genomes mean    stddev  |       samples
0       8444    240     |       8204    8685    8204    8204    8685    8685
1       10393   769     |       10648   10863   10648   10648   10863   8688
2       10758   108     |       10651   10866   10651   10651   10866   10866

# core-genome (number of genes, can be plotted with plot_pancore_matrix.pl)
# file=data_get_homologues/core_genome_algBDBH.tab
genomes mean    stddev  |       samples
0       8444    240     |       8204    8685    8204    8204    8685    8685
1       5316    1504    |       4644    4644    4644    4644    4644    8679
2       4644    0       |       4644    4644    4644    4644    4644    4644

# clustering orthologous sequences

# clustering inparalogues in 2692915.4.faa (reference)
# 914 sequences

# clustering inparalogues in 287862.3.faa
# 515 sequences

# finding BDBHs between 2692915.4.faa and 287862.3.faa
# 4644 sequences

# clustering inparalogues in 287863.3.faa
# 515 sequences

# finding BDBHs between 2692915.4.faa and 287863.3.faa
# 4644 sequences

# looking for valid ORF clusters (n_of_taxa=3)...


# number_of_clusters = 4644
# cluster_list = data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_.cluster_list
# cluster_directory = data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_

# runtime: 1159 wallclock secs (26.93 usr  0.80 sys + 1338.43 cusr  6.07 csys = 1372.23 CPU)
# RAM use: 72.3 MB
{: .output}
Correr el siguiente: ~~~ (Pangenomics_Global) alumno5@betterlabub:~/Haydee$ get_homologues.pl -d
data_get -G ~~~ {: .language-bash}
Se obtiene lo siguiente:
# /opt/anaconda3/envs/Pangenomics_Global/bin/get_homologues.pl -i 0 -d data_get -o 0 -X 0 -e 0 -f 0 -r 0 -t all -c 0 -z 0 -I 0 -m local -n 2 -M 0 -G 1 -p 0 -C 75 -S 1 -E 1e-05 -F 1.5 -N 0 -B 50 -b 0 -s 0 -D 0 -g 0 -a '0' -x 0 -R 0 -A 0 -P 0

# version 28042022
# results_directory=/home/alumno5/Haydee/data_get_homologues
# parameters: MAXEVALUEBLASTSEARCH=0.01 MAXPFAMSEQS=250 BATCHSIZE=100 KEEPSCNDHSPS=1
# diamond job:0

# checking input files...
# 2692915.4.faa 8802
# 287862.3.faa 8982
# 287863.3.faa 8982

# 3 genomes, 26766 sequences

# taxa considered = 3 sequences = 26766 residues = 7168829 MIN_BITSCORE_SIM = 18.7

# mask=2692915_f0_alltaxa_algCOG_e0_ (_algCOG)

# skipped genome parsing (data_get_homologues/tmp/selected.genomes)


# running BLAST searches ...
# done


# parsing file (COG)
# parsing file (COG) finished

# creating indexes, this might take some time (lines=7.70e+05) ...

# construct_taxa_indexes: number of taxa found = 3
# number of file addresses/BLAST queries = 2.7e+04

# clustering orthologous sequences
# checking lineage-specific expansions
# making COGs
# prunning COGs
# done

# looking for valid ORF clusters (n_of_taxa=3)...


# number_of_clusters = 4641
# cluster_list = data_get_homologues/2692915_f0_alltaxa_algCOG_e0_.cluster_list
# cluster_directory = data_get_homologues/2692915_f0_alltaxa_algCOG_e0_

# runtime: 24 wallclock secs ( 2.97 usr  0.11 sys +  6.74 cusr  1.95 csys = 11.77 CPU)
# RAM use: 67.1 MB
{: .output}
Correr el siguiente algoritmo de clustering.
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ get_homologues.pl -d data_get -M
{: .language-bash}
Da la siguiente salida.
# /opt/anaconda3/envs/Pangenomics_Global/bin/get_homologues.pl -i 0 -d data_get -o 0 -X 0 -e 0 -f 0 -r 0 -t all -c 0 -z 0 -I 0 -m local -n 2 -M 1 -G 0 -p 0 -C 75 -S 1 -E 1e-05 -F 1.5 -N 0 -B 50 -b 0 -s 0 -D 0 -g 0 -a '0' -x 0 -R 0 -A 0 -P 0

# version 28042022
# results_directory=/home/alumno5/Haydee/data_get_homologues
# parameters: MAXEVALUEBLASTSEARCH=0.01 MAXPFAMSEQS=250 BATCHSIZE=100 KEEPSCNDHSPS=1
# diamond job:0

# checking input files...
# 2692915.4.faa 8802
# 287862.3.faa 8982
# 287863.3.faa 8982

# 3 genomes, 26766 sequences

# taxa considered = 3 sequences = 26766 residues = 7168829 MIN_BITSCORE_SIM = 18.7

# mask=2692915_f0_alltaxa_algOMCL_e0_ (_algOMCL)

# skipped genome parsing (data_get_homologues/tmp/selected.genomes)

# skip BLAST searches and parsing

# WARNING: please remove/rename results directory:
# '/home/alumno5/Haydee/data_get_homologues/'
# if you change the sequences in your .gbk/.faa files or want to re-run

# creating indexes, this might take some time (lines=7.70e+05) ...

# construct_taxa_indexes: number of taxa found = 3
# number of file addresses/BLAST queries = 2.7e+04

# clustering orthologous sequences

# identifying orthologs between 2692915.4.faa and 287862.3.faa (0)
# 5608 sequences

# identifying orthologs between 2692915.4.faa and 287863.3.faa (0)
# 5608 sequences

# identifying inparalogs in 2692915.4.faa
# 914 sequences

# identifying orthologs between 287862.3.faa and 287863.3.faa (0)
# 10032 sequences

# identifying inparalogs in 287862.3.faa
# 515 sequences

# identifying inparalogs in 287863.3.faa
# 515 sequences

# running MCL (inflation=1.5) ...
# running MCL finished

# find_OMCL_clusters: parsing clusters (/home/alumno5/Haydee/data_get_homologues/tmp/all_ortho.mcl)


# looking for valid ORF clusters (n_of_taxa=3)...


# number_of_clusters = 4622
# cluster_list = data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_.cluster_list
# cluster_directory = data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_

# runtime:  7 wallclock secs ( 4.22 usr  0.17 sys +  1.24 cusr  0.62 csys =  6.25 CPU)
# RAM use: 85.3 MB
{: .output}
Observar que da diferente número de clusters.
Para listar los genomas de referencia ~~~ (Pangenomics_Global) alumno5@betterlabub:~/Haydee$ ls -d
data_get_homologues/alltaxa ~~~ {: .language-bash}
data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_
data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_.cluster_list
data_get_homologues/2692915_f0_alltaxa_algCOG_e0_
data_get_homologues/2692915_f0_alltaxa_algCOG_e0_.cluster_list
data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_
data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_.cluster_list
{: .output}
Obtener la intersección entre los clusters.
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ compare_clusters.pl -o alg_intersection -d \
data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_,\
data_get_homologues/2692915_f0_alltaxa_algCOG_e0_,\
data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_
{: .language-bash}
# /opt/anaconda3/envs/Pangenomics_Global/bin/compare_clusters.pl -d data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_,data_get_homologues/2692915_f0_alltaxa_algCOG_e0_,data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_ -o alg_intersection -n 0 -m 0 -t 0 -I  -r 0 -s 0 -x 0 -T 0

# output directory: alg_intersection

# number of input cluster directories = 3

# parsing clusters in data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_ ...
# cluster_list in place, will parse it (data_get_homologues/2692915_f0_alltaxa_algBDBH_e0_.cluster_list)
# number of clusters = 4644 duplicated = 0
# parsing clusters in data_get_homologues/2692915_f0_alltaxa_algCOG_e0_ ...
# cluster_list in place, will parse it (data_get_homologues/2692915_f0_alltaxa_algCOG_e0_.cluster_list)
# number of clusters = 4641 duplicated = 0
# parsing clusters in data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_ ...
# cluster_list in place, will parse it (data_get_homologues/2692915_f0_alltaxa_algOMCL_e0_.cluster_list)
# number of clusters = 4622 duplicated = 0

# duplicated list: alg_intersection/duplicated.cluster_list (please review)

# intersection size = 4519 clusters

# intersection list = alg_intersection/intersection_t0.cluster_list

# input set: alg_intersection/2692915_f0_alltaxa_algBDBH_e0_.venn_t0.txt
# input set: alg_intersection/2692915_f0_alltaxa_algCOG_e0_.venn_t0.txt
# input set: alg_intersection/2692915_f0_alltaxa_algOMCL_e0_.venn_t0.txt

# Venn diagram = alg_intersection/venn_t0.pdf alg_intersection/venn_t0.svg
# Venn region file: alg_intersection/unique_2692915_f0_alltaxa_algBDBH_e0_.venn_t0.txt (53)
# Venn region file: alg_intersection/unique_2692915_f0_alltaxa_algCOG_e0_.venn_t0.txt (100)
# Venn region file: alg_intersection/unique_2692915_f0_alltaxa_algOMCL_e0_.venn_t0.txt (27)
# Venn region file: alg_intersection/intersection_2692915_f0_alltaxa_algBDBH_e0__2692915_f0_alltaxa_algCOG_e0_.venn_t0.txt (9)
# Venn region file: alg_intersection/intersection_2692915_f0_alltaxa_algBDBH_e0__2692915_f0_alltaxa_algOMCL_e0_.venn_t0.txt (63)
# Venn region file: alg_intersection/intersection_2692915_f0_alltaxa_algCOG_e0__2692915_f0_alltaxa_algOMCL_e0_.venn_t0.txt (13)
{: .output}
En el diagrama de Venn se puede observar los genes que están en el
core (4519).


Diagrama de Venn con el número de genes en cada
cluster




Obtener la matriz de Pangenoma
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ get_homologues.pl -d data_get -t 0 -M
{: .language-bash}
Salida:
# /opt/anaconda3/envs/Pangenomics_Global/bin/get_homologues.pl -i 0 -d data_get -o 0 -X 0 -e 0 -f 0 -r 0 -t 0 -c 0 -z 0 -I 0 -m local -n 2 -M 1 -G 0 -p 0 -C 75 -S 1 -E 1e-05 -F 1.5 -N 0 -B 50 -b 0 -s 0 -D 0 -g 0 -a '0' -x 0 -R 0 -A 0 -P 0

# version 28042022
# results_directory=/home/alumno5/Haydee/data_get_homologues
# parameters: MAXEVALUEBLASTSEARCH=0.01 MAXPFAMSEQS=250 BATCHSIZE=100 KEEPSCNDHSPS=1
# diamond job:0

# checking input files...
# 2692915.4.faa 8802
# 287862.3.faa 8982
# 287863.3.faa 8982

# 3 genomes, 26766 sequences

# taxa considered = 3 sequences = 26766 residues = 7168829 MIN_BITSCORE_SIM = 18.7

# mask=2692915_f0_0taxa_algOMCL_e0_ (_algOMCL)

# skipped genome parsing (data_get_homologues/tmp/selected.genomes)

# skip BLAST searches and parsing

# WARNING: please remove/rename results directory:
# '/home/alumno5/Haydee/data_get_homologues/'
# if you change the sequences in your .gbk/.faa files or want to re-run

# creating indexes, this might take some time (lines=7.70e+05) ...

# construct_taxa_indexes: number of taxa found = 3
# number of file addresses/BLAST queries = 2.7e+04

# clustering orthologous sequences
# find_OMCL_clusters: re-using previous results (same parameters)

# find_OMCL_clusters: parsing clusters (/home/alumno5/Haydee/data_get_homologues/tmp/all_ortho.mcl)


# add_unmatched_singletons : 3393 sequences, 3 taxa


# looking for valid ORF clusters (n_of_taxa=0)...


# number_of_clusters = 12233
# cluster_list = data_get_homologues/2692915_f0_0taxa_algOMCL_e0_.cluster_list
# cluster_directory = data_get_homologues/2692915_f0_0taxa_algOMCL_e0_

# runtime:  5 wallclock secs ( 2.74 usr  0.21 sys +  0.31 cusr  0.02 csys =  3.28 CPU)
# RAM use: 54.5 MB
{: .output}
Segundo algoritmo
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ get_homologues.pl -d data_get -t 0 -M
{: .language-bash}
Salida
# /opt/anaconda3/envs/Pangenomics_Global/bin/get_homologues.pl -i 0 -d data_get -o 0 -X 0 -e 0 -f 0 -r 0 -t 0 -c 0 -z 0 -I 0 -m local -n 2 -M 1 -G 0 -p 0 -C 75 -S 1 -E 1e-05 -F 1.5 -N 0 -B 50 -b 0 -s 0 -D 0 -g 0 -a '0' -x 0 -R 0 -A 0 -P 0

# version 28042022
# results_directory=/home/alumno5/Haydee/data_get_homologues
# parameters: MAXEVALUEBLASTSEARCH=0.01 MAXPFAMSEQS=250 BATCHSIZE=100 KEEPSCNDHSPS=1
# diamond job:0

# checking input files...
# 2692915.4.faa 8802
# 287862.3.faa 8982
# 287863.3.faa 8982

# 3 genomes, 26766 sequences

# taxa considered = 3 sequences = 26766 residues = 7168829 MIN_BITSCORE_SIM = 18.7

# mask=2692915_f0_0taxa_algOMCL_e0_ (_algOMCL)

# skipped genome parsing (data_get_homologues/tmp/selected.genomes)

# skip BLAST searches and parsing

# WARNING: please remove/rename results directory:
# '/home/alumno5/Haydee/data_get_homologues/'
# if you change the sequences in your .gbk/.faa files or want to re-run

# creating indexes, this might take some time (lines=7.70e+05) ...

# construct_taxa_indexes: number of taxa found = 3
# number of file addresses/BLAST queries = 2.7e+04

# clustering orthologous sequences
# find_OMCL_clusters: re-using previous results (same parameters)

# find_OMCL_clusters: parsing clusters (/home/alumno5/Haydee/data_get_homologues/tmp/all_ortho.mcl)


# add_unmatched_singletons : 3393 sequences, 3 taxa


# looking for valid ORF clusters (n_of_taxa=0)...


# number_of_clusters = 12233
# cluster_list = data_get_homologues/2692915_f0_0taxa_algOMCL_e0_.cluster_list
# cluster_directory = data_get_homologues/2692915_f0_0taxa_algOMCL_e0_

# runtime:  5 wallclock secs ( 2.74 usr  0.21 sys +  0.31 cusr  0.02 csys =  3.28 CPU)
# RAM use: 54.5 MB
{: .output}
Lista de cluster directorios de COG y OMCL
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ ls -d data_get_homologues/*0taxa*
{: .language-bash}
Directorios:
data_get_homologues/2692915_f0_0taxa_algCOG_e0_
data_get_homologues/2692915_f0_0taxa_algOMCL_e0_
{: .output}
compare_clusters.pl -o alg_intersection -m -T -d \
data_get_homologues/2692915_f0_0taxa_algCOG_e0_,\
data_get_homologues/2692915_f0_0taxa_algOMCL_e0_
{: .language-bash}
Salida (revisar)
# /opt/anaconda3/envs/Pangenomics_Global/bin/compare_clusters.pl -d data_get_homologues/2692915_f0_0taxa_algCOG_e0_,data_get_homologues/2692915_f0_0taxa_algOMCL_e0_ -o alg_intersection -n 0 -m 1 -t 0 -I  -r 0 -s 0 -x 0 -T 1

# output directory: alg_intersection
# WARNING: output directory alg_intersection already exists, note that you might be mixing clusters from previous runs


# number of input cluster directories = 2

# parsing clusters in data_get_homologues/2692915_f0_0taxa_algCOG_e0_ ...
# cluster_list in place, will parse it (data_get_homologues/2692915_f0_0taxa_algCOG_e0_.cluster_list)
# WARNING: cluster 9113_fig-287862.3.peg.2940.faa duplicates 8962_fig-287862.3.peg.3636.faa
# WARNING: cluster 11014_fig-287862.3.peg.3798.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 12285_fig-287862.3.peg.5187.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 13279_fig-287862.3.peg.6426.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 13396_fig-287862.3.peg.6543.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 14075_fig-287862.3.peg.7261.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 15342_fig-287862.3.peg.8131.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 15444_fig-287862.3.peg.8233.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 16549_fig-287862.3.peg.8694.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 19255_fig-287862.3.peg.3033.faa duplicates 10273_fig-287862.3.peg.3033.faa
# WARNING: cluster 19481_fig-287862.3.peg.3259.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 19996_fig-287862.3.peg.3798.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 21267_fig-287862.3.peg.5187.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 21758_fig-287862.3.peg.5746.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 22175_fig-287862.3.peg.6279.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 22261_fig-287862.3.peg.6426.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 22378_fig-287862.3.peg.6543.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 23057_fig-287862.3.peg.7261.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 23500_fig-287862.3.peg.7704.faa duplicates 14518_fig-287862.3.peg.7704.faa
# WARNING: cluster 24324_fig-287862.3.peg.8131.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 24426_fig-287862.3.peg.8233.faa duplicates 10499_fig-287862.3.peg.3259.faa
# WARNING: cluster 25531_fig-287862.3.peg.8694.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 26163_fig-287862.3.peg.1549.faa duplicates 17181_fig-287862.3.peg.1549.faa
# number of clusters = 11925 duplicated = 30
# parsing clusters in data_get_homologues/2692915_f0_0taxa_algOMCL_e0_ ...
# cluster_list in place, will parse it (data_get_homologues/2692915_f0_0taxa_algOMCL_e0_.cluster_list)
# WARNING: cluster 9113_fig-287862.3.peg.2940.faa duplicates 8962_fig-287862.3.peg.3636.faa
# WARNING: cluster 13396_fig-287862.3.peg.6543.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 14075_fig-287862.3.peg.7261.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 15342_fig-287862.3.peg.8131.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 16549_fig-287862.3.peg.8694.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 19255_fig-287862.3.peg.3033.faa duplicates 10273_fig-287862.3.peg.3033.faa
# WARNING: cluster 20785_fig-287862.3.peg.4705.faa duplicates 11803_fig-287862.3.peg.4705.faa
# WARNING: cluster 21758_fig-287862.3.peg.5746.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 22175_fig-287862.3.peg.6279.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 22378_fig-287862.3.peg.6543.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 23057_fig-287862.3.peg.7261.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 23500_fig-287862.3.peg.7704.faa duplicates 14518_fig-287862.3.peg.7704.faa
# WARNING: cluster 24324_fig-287862.3.peg.8131.faa duplicates 12776_fig-287862.3.peg.5746.faa
# WARNING: cluster 25531_fig-287862.3.peg.8694.faa duplicates 13193_fig-287862.3.peg.6279.faa
# WARNING: cluster 26163_fig-287862.3.peg.1549.faa duplicates 17181_fig-287862.3.peg.1549.faa
# number of clusters = 12211 duplicated = 22

# duplicated list: alg_intersection/duplicated.cluster_list (please review)

# intersection size = 11620 clusters

# intersection list = alg_intersection/intersection_t0.cluster_list

# pangenome_file = alg_intersection/pangenome_matrix_t0.tab transposed = alg_intersection/pangenome_matrix_t0.tr.tab
# pangenome_genes = alg_intersection/pangenome_matrix_genes_t0.tab transposed = alg_intersection/pangenome_matrix_genes_t0.tr.tab
# pangenome_phylip file = alg_intersection/pangenome_matrix_t0.phylip
# pangenome_FASTA file = alg_intersection/pangenome_matrix_t0.fasta
# pangenome CSV file (Scoary) = alg_intersection/pangenome_matrix_t0.tr.csv

# parsimony results by PARS (PHYLIP suite, http://evolution.genetics.washington.edu/phylip/doc/pars.html):
# pangenome_phylip tree = alg_intersection/pangenome_matrix_t0.phylip.ph
# pangenome_phylip log = alg_intersection/pangenome_matrix_t0.phylip.log

# input set: alg_intersection/2692915_f0_0taxa_algCOG_e0_.venn_t0.txt
# input set: alg_intersection/2692915_f0_0taxa_algOMCL_e0_.venn_t0.txt

# Venn diagram = alg_intersection/venn_t0.pdf alg_intersection/venn_t0.svg
# Venn region file: alg_intersection/unique_2692915_f0_0taxa_algCOG_e0_.venn_t0.txt (305)
# Venn region file: alg_intersection/unique_2692915_f0_0taxa_algOMCL_e0_.venn_t0.txt (591)
{: .output}
#Plot core y Pangenome cluster del algoritmo BDBH
(Pangenomics_Global) alumno5@betterlabub:~/Haydee$ plot_pancore_matrix.pl -i data_get_homologues/pan_genome_algBDBH.tab 
{: .language-bash}
# /opt/anaconda3/envs/Pangenomics_Global/bin/plot_pancore_matrix.pl -i data_get_homologues/pan_genome_algBDBH.tab -f core_Tettelin -F 0.80 -a 
# outfiles: data_get_homologues/pan_genome_algBDBH.tab_core_Tettelin.log , data_get_homologues/pan_genome_algBDBH.tab_core_Tettelin.png , data_get_homologues/pan_genome_algBDBH.tab_core_Tettelin.pdf , data_get_homologues/pan_genome_algBDBH.tab_core_Tettelin.svg
{: .output}
No se pude hacer este análisis. ~~~ (Pangenomics_Global) alumno5@betterlabub:~/Haydee$
parse_pangenome_matrix.pl -m alg_intersection/pangenome_matrix_t0.tab -s
~~~ {: .language-bash}
# /opt/anaconda3/envs/Pangenomics_Global/bin/parse_pangenome_matrix.pl -m alg_intersection/pangenome_matrix_t0.tab -I  -A  -B  -a 0 -g 0 -e 0 -p  -s 1 -n 0 -l 0 -x 0 -P 100 -S 0

# matrix contains 11620 clusters and 3 taxa

# EXIT : need at least 5 taxa to perform -s analysis
{: .output}
=======
Owner

Name: Haydee Peruyero
Login: HaydeePeruyero
Kind: user
Location: México
Website: https://haydeeperuyero.github.io/
Repositories: 23
Profile: https://github.com/HaydeePeruyero
Posdoctorante en el Centro de Ciencias Matemáticas UNAM. Doctorado en Ciencias Matemáticas, IMATE UNAM. Especialidad en Estadística Aplicada, IIMAS UNAM.
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