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This code compiles summary information about the gene DOCK3.

This gene is specifically expressed in the central nervous system (CNS). It encodes a member of the DOCK (dedicator of cytokinesis) family of guanine nucleotide exchange factors (GEFs). This protein, dedicator of cytokinesis 3 (DOCK3), is also known as modifier of cell adhesion (MOCA) and presenilin-binding protein (PBP). The DOCK3 and DOCK1, -2 and -4 share several conserved amino acids in their DHR-2 (DOCK homology region 2) domains that are required for GEF activity, and bind directly to WAVE proteins [Wiskott-Aldrich syndrome protein (WASP) family Verprolin-homologous proteins] via their DHR-1 domains. The DOCK3 induces axonal outgrowth in CNS by stimulating membrane recruitment of the WAVE complex and activating the small G protein Rac1. This gene is associated with an attention deficit hyperactivity disorder-like phenotype by a complex chromosomal rearrangement. [provided by RefSeq, Aug 2010].

Refseq Gene: https://www.ncbi.nlm.nih.gov/gene/1795 Refseq Homologene: https://www.ncbi.nlm.nih.gov/homologene/21030 Other resources consulted includes: Uniprot: https://www.uniprot.org/uniprot/Q8IZD9

#install.packages("BiocManager")
library(BiocManager)
## Bioconductor version '3.13' is out-of-date; the current release version '3.14'
##   is available with R version '4.1'; see https://bioconductor.org/install
#install("drawProteins")
#BiocManager::install("drawProteins")
library(drawProteins)
# github packages
library(compbio4all)
library(ggmsa)
## Registered S3 methods overwritten by 'ggalt':
##   method                  from   
##   grid.draw.absoluteGrob  ggplot2
##   grobHeight.absoluteGrob ggplot2
##   grobWidth.absoluteGrob  ggplot2
##   grobX.absoluteGrob      ggplot2
##   grobY.absoluteGrob      ggplot2
## ggmsa v0.99.5  Document: http://yulab-smu.top/ggmsa/
## 
## If you use ggmsa in published research, please cite: DOI: 10.18129/B9.bioc.ggmsa
# CRAN packages
library(rentrez)
library(seqinr)
library(ape)
## 
## Attaching package: 'ape'
## The following objects are masked from 'package:seqinr':
## 
##     as.alignment, consensus
library(pander)


library(ggplot2)
library(drawProteins)
# github packages
library(compbio4all)
library(ggmsa)
# Bioconductor packages
## msa
### The msa package is having problems on some platforms
### You can skip the msa steps if necessary.  The msa output
### is used to make a distance matrix and then phylogenetics trees,
### but I provide code to build the matrix by hand so
### you can proceed even if msa doesn't work for you.
#BiocManager::install("msa")
library(msa)
## Loading required package: Biostrings
## Loading required package: BiocGenerics
## Loading required package: parallel
## 
## Attaching package: 'BiocGenerics'
## The following objects are masked from 'package:parallel':
## 
##     clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
##     clusterExport, clusterMap, parApply, parCapply, parLapply,
##     parLapplyLB, parRapply, parSapply, parSapplyLB
## The following objects are masked from 'package:stats':
## 
##     IQR, mad, sd, var, xtabs
## The following objects are masked from 'package:base':
## 
##     anyDuplicated, append, as.data.frame, basename, cbind, colnames,
##     dirname, do.call, duplicated, eval, evalq, Filter, Find, get, grep,
##     grepl, intersect, is.unsorted, lapply, Map, mapply, match, mget,
##     order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank,
##     rbind, Reduce, rownames, sapply, setdiff, sort, table, tapply,
##     union, unique, unsplit, which.max, which.min
## Loading required package: S4Vectors
## Loading required package: stats4
## 
## Attaching package: 'S4Vectors'
## The following objects are masked from 'package:base':
## 
##     expand.grid, I, unname
## Loading required package: IRanges
## Loading required package: XVector
## Loading required package: GenomeInfoDb
## 
## Attaching package: 'Biostrings'
## The following object is masked from 'package:ape':
## 
##     complement
## The following object is masked from 'package:seqinr':
## 
##     translate
## The following object is masked from 'package:base':
## 
##     strsplit
## 
## Attaching package: 'msa'
## The following object is masked from 'package:BiocManager':
## 
##     version
library(drawProteins)

## Biostrings
#install.packages("Biostrings")
library(Biostrings)
#install.packages("HGNChelper")
library(HGNChelper)
# CRAN packages
library(rentrez)
library(seqinr)
library(ape)
#                RefSeq           Uniprot PDB  sci name           common name  gene name
dock3_table<-c("NP_004938.1","Q8IZD9","NA","Homo sapiens","Human","DOCK3",
              "XP_516488.4","NA","NA", "Pan troglodytes","Chimpanzee","DOCK3",
              "NP_700462.2",   "Q8CIQ7","NA","Mus musculus","Mouse","DOCK3",
              "XP_001089458.2","Q8HXW5","NA","Macaca mulatta","Cynomolgus monkey","DOCK3",
              "XP_533813.4","Q6RH31","NA","Canis Lupus","Dog","DOCK3",
              "XP_002697118.2","Q9XT97","NA","Bos Taurus","Bovine","DOCK3",
              "ENSP00000266037","Q8IZD9","NA","Homo Sapiens","Human","DOCK3",
              "XM_032320975.1","NA","NA","Mustela erminea","stoat","DOCK3",
              "NW_020847977.1","NA","NA","Tachysurus fulvidraco","Catfish","DOCK3",
              "XP_006243927.1","P97887","NA","Rattus norvegicus", "rat","DOCK3")
#
## [1] 10 10
## [1] "data.frame"       "list"             "oldClass"         "vector"          
## [5] "list_OR_List"     "vector_OR_Vector" "vector_OR_factor"
## [1] "V1" "V2" "V3" "V4" "V5" "V6" "V7" "V8" "V9" "V10"
matrix(data = dock3_table, nrow = 10, ncol = 6, byrow = TRUE,
       dimnames = NULL)
##       [,1]              [,2]     [,3] [,4]                   
##  [1,] "NP_004938.1"     "Q8IZD9" "NA" "Homo sapiens"         
##  [2,] "XP_516488.4"     "NA"     "NA" "Pan troglodytes"      
##  [3,] "NP_700462.2"     "Q8CIQ7" "NA" "Mus musculus"         
##  [4,] "XP_001089458.2"  "Q8HXW5" "NA" "Macaca mulatta"       
##  [5,] "XP_533813.4"     "Q6RH31" "NA" "Canis Lupus"          
##  [6,] "XP_002697118.2"  "Q9XT97" "NA" "Bos Taurus"           
##  [7,] "ENSP00000266037" "Q8IZD9" "NA" "Homo Sapiens"         
##  [8,] "XM_032320975.1"  "NA"     "NA" "Mustela erminea"      
##  [9,] "NW_020847977.1"  "NA"     "NA" "Tachysurus fulvidraco"
## [10,] "XP_006243927.1"  "P97887" "NA" "Rattus norvegicus"    
##       [,5]                [,6]   
##  [1,] "Human"             "DOCK3"
##  [2,] "Chimpanzee"        "DOCK3"
##  [3,] "Mouse"             "DOCK3"
##  [4,] "Cynomolgus monkey" "DOCK3"
##  [5,] "Dog"               "DOCK3"
##  [6,] "Bovine"            "DOCK3"
##  [7,] "Human"             "DOCK3"
##  [8,] "stoat"             "DOCK3"
##  [9,] "Catfish"           "DOCK3"
## [10,] "rat"               "DOCK3"
length(dock3_table)
## [1] 60
dock3_table[[1]]
## [1] "NP_004938.1"
for(i in 1:length(dock3_table)){
  dock3_table[[i]] <- compbio4all::fasta_cleaner(dock3_table[[i]], parse = F)
}
library(BiocManager)
#install("drawProteins")
library(drawProteins)
library(ggplot2)
library(drawProteins)
Q8IZD9_json  <- drawProteins::get_features("Q8IZD9")
## [1] "Download has worked"
is(Q8IZD9_json)
## [1] "list"             "vector"           "list_OR_List"     "vector_OR_Vector"
## [5] "vector_OR_factor"
my_prot_df <- drawProteins::feature_to_dataframe(Q8IZD9_json)
is(my_prot_df)
## [1] "data.frame"       "list"             "oldClass"         "vector"          
## [5] "list_OR_List"     "vector_OR_Vector" "vector_OR_factor"
my_prot_df[,-2]
##                     type begin  end length accession   entryName taxid order
## featuresTemp       CHAIN     1 2030   2029    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.1    DOMAIN     6   67     61    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.2    DOMAIN   421  599    178    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.3    DOMAIN  1228 1635    407    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.4    REGION  1641 1662     21    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.5    REGION  1734 1771     37    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.6    REGION  1849 1927     78    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.7    REGION  1951 2030     79    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.8     MOTIF  1970 1976      6    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.9  COMPBIAS  1734 1765     31    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.10 COMPBIAS  1871 1920     49    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.11 COMPBIAS  1964 1980     16    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.12 COMPBIAS  1981 2005     24    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.13  MOD_RES  1658 1658      0    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.14  VARIANT   128 2030   1902    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.15  VARIANT   392  392      0    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.16  VARIANT  1296 1296      0    Q8IZD9 DOCK3_HUMAN  9606     1
## featuresTemp.17  VARIANT  1674 1674      0    Q8IZD9 DOCK3_HUMAN  9606     1
my_canvas <- draw_canvas(my_prot_df)  
my_canvas <- draw_chains(my_canvas, my_prot_df, 
                         label_size = 2.5)
my_canvas <- draw_domains(my_canvas, my_prot_df)
my_canvas

Q8IZD9_FASTA <- rentrez::entrez_fetch(id ="Q8IZD9" ,
                                      db = "protein", 
                                      rettype="fasta")
Q8IZD9_vector <- fasta_cleaner(Q8IZD9_FASTA)
Q8IZD9_FASTA_str <- fasta_cleaner(Q8IZD9_FASTA, 
                               parse = F)
length(Q8IZD9_FASTA)
## [1] 1
nchar(Q8IZD9_FASTA)
## [1] 2228
str(Q8IZD9_FASTA)
##  chr ">sp|Q8IZD9.1|DOCK3_HUMAN RecName: Full=Dedicator of cytokinesis protein 3; AltName: Full=Modifier of cell adhes"| __truncated__
str(Q8IZD9_vector)
##  chr [1:2030] "M" "W" "T" "P" "T" "E" "E" "E" "K" "Y" "G" "V" "V" "I" "C" ...
str(Q8IZD9_FASTA_str)
##  chr "MWTPTEEEKYGVVICSFRGSVPQGLVLEIGETVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTATLQEWASLWKQLYVKHKVDL"| __truncated__
align <- pairwiseAlignment(Q8IZD9_FASTA_str, 
                           Q8IZD9_FASTA_str, 
                           type = "global")
# set up 2 x 2 grid, make margins things
par(mfrow = c(2,2), 
    mar = c(0,0,2,1))

# plot 1: Defaults
dotPlot(Q8IZD9_vector, Q8IZD9_vector, 
        wsize = 1, 
        nmatch = 1, 
        main = "")

# plot 2 size = 10, nmatch = 1
dotPlot(Q8IZD9_vector, Q8IZD9_vector, 
        wsize = 10, 
        nmatch = 1, 
        main = "")

# plot 3: size = 10, nmatch = 5
dotPlot(Q8IZD9_vector, Q8IZD9_vector, 
        wsize = 10, 
        nmatch = 5, 
        main = "")

# plot 4: size = 20, nmatch = 5
dotPlot(Q8IZD9_vector, Q8IZD9_vector, 
        wsize = 20,
        nmatch = 5,
        main = "")

# reset par() - run this or other plots will be small!
par(mfrow = c(1,1), 
    mar = c(4,4,4,4))
par(mfrow = c(1,1), 
    mar = c(4,4,4,4))


dotPlot(Q8IZD9_vector, 
        Q8IZD9_vector,
        wsize = 20, 
        wstep = 1,
        nmatch = 5
        )

aa.1.1 <- c("A","R","N","D","C","Q","E","G","H","I",
            "L","K","M","F","P","S","T","W","Y","V")
## alpha proteins
alpha <- c(285, 53, 97, 163, 22, 67, 134, 197, 111, 91, 
           221, 249, 48, 123, 82, 122, 119, 33, 63, 167)
## beta proteins
beta <- c(203, 67, 139, 121, 75, 122, 86, 297, 49, 120, 
          177, 115, 16, 85, 127, 341, 253, 44, 110, 229)
## alpha + beta
a.plus.b <- c(175, 78, 120, 111, 74, 74, 86, 171, 33, 93,
              110, 112, 25, 52, 71, 126, 117, 30, 108, 123)
## alpha/beta
a.div.b <- c(361, 146, 183, 244, 63, 114, 257, 377, 107, 239, 
             339, 321, 91, 158, 188, 327, 238, 72, 130, 378)

data.frame(aa.1.1, alpha, beta, a.plus.b, a.div.b)
##    aa.1.1 alpha beta a.plus.b a.div.b
## 1       A   285  203      175     361
## 2       R    53   67       78     146
## 3       N    97  139      120     183
## 4       D   163  121      111     244
## 5       C    22   75       74      63
## 6       Q    67  122       74     114
## 7       E   134   86       86     257
## 8       G   197  297      171     377
## 9       H   111   49       33     107
## 10      I    91  120       93     239
## 11      L   221  177      110     339
## 12      K   249  115      112     321
## 13      M    48   16       25      91
## 14      F   123   85       52     158
## 15      P    82  127       71     188
## 16      S   122  341      126     327
## 17      T   119  253      117     238
## 18      W    33   44       30      72
## 19      Y    63  110      108     130
## 20      V   167  229      123     378
# convert them to frequencies
alpha.prop <- alpha/sum(alpha)
beta.prop <- beta/sum(beta)
a.plus.b.prop <- a.plus.b/sum(a.plus.b)
a.div.b <- a.div.b/sum(a.div.b)

## dataframe
aa.prop <- data.frame(alpha.prop,
                      beta.prop,
                      a.plus.b.prop,
                      a.div.b)
## row labels
row.names(aa.prop) <- aa.1.1

pander::pander(aa.prop)
  alpha.prop beta.prop a.plus.b.prop a.div.b
A 0.1165 0.07313 0.09264 0.08331
R 0.02166 0.02414 0.04129 0.03369
N 0.03964 0.05007 0.06353 0.04223
D 0.06661 0.04359 0.05876 0.05631
C 0.008991 0.02702 0.03917 0.01454
Q 0.02738 0.04395 0.03917 0.02631
E 0.05476 0.03098 0.04553 0.05931
G 0.08051 0.107 0.09052 0.08701
H 0.04536 0.01765 0.01747 0.02469
I 0.03719 0.04323 0.04923 0.05516
L 0.09031 0.06376 0.05823 0.07824
K 0.1018 0.04143 0.05929 0.07408
M 0.01962 0.005764 0.01323 0.021
F 0.05027 0.03062 0.02753 0.03646
P 0.03351 0.04575 0.03759 0.04339
S 0.04986 0.1228 0.0667 0.07547
T 0.04863 0.09114 0.06194 0.05493
W 0.01349 0.01585 0.01588 0.01662
Y 0.02575 0.03963 0.05717 0.03
V 0.06825 0.08249 0.06511 0.08724 
plot(aa.prop,panel = panel.smooth)

names(dock3_table)
## NULL
length(dock3_table)
## [1] 60
dock3_table[1]
## [1] "NP_004938.1"
# Make each entry of the list into a vector
dock3_table
##  [1] "NP_004938.1"           "Q8IZD9"                "NA"                   
##  [4] "Homo sapiens"          "Human"                 "DOCK3"                
##  [7] "XP_516488.4"           "NA"                    "NA"                   
## [10] "Pan troglodytes"       "Chimpanzee"            "DOCK3"                
## [13] "NP_700462.2"           "Q8CIQ7"                "NA"                   
## [16] "Mus musculus"          "Mouse"                 "DOCK3"                
## [19] "XP_001089458.2"        "Q8HXW5"                "NA"                   
## [22] "Macaca mulatta"        "Cynomolgus monkey"     "DOCK3"                
## [25] "XP_533813.4"           "Q6RH31"                "NA"                   
## [28] "Canis Lupus"           "Dog"                   "DOCK3"                
## [31] "XP_002697118.2"        "Q9XT97"                "NA"                   
## [34] "Bos Taurus"            "Bovine"                "DOCK3"                
## [37] "ENSP00000266037"       "Q8IZD9"                "NA"                   
## [40] "Homo Sapiens"          "Human"                 "DOCK3"                
## [43] "XM_032320975.1"        "NA"                    "NA"                   
## [46] "Mustela erminea"       "stoat"                 "DOCK3"                
## [49] "NW_020847977.1"        "NA"                    "NA"                   
## [52] "Tachysurus fulvidraco" "Catfish"               "DOCK3"                
## [55] "XP_006243927.1"        "P97887"                "NA"                   
## [58] "Rattus norvegicus"     "rat"                   "DOCK3"
human <- unlist(dock3_table[1])
chimpanzee <- unlist(dock3_table[2])
mouse <- unlist(dock3_table[3])
monkey <- unlist(dock3_table[4])
dog <- unlist(dock3_table[5])
bovine <- unlist(dock3_table[6])
human <- unlist(dock3_table[7])
stoat <- unlist(dock3_table[8])
catfish <- unlist(dock3_table[9])
rat <- unlist(dock3_table[10])

dock3_vector <- rep(NA, length(dock3_table))

for(i in 1:length(Q8IZD9_vector)){
  Q8IZD9_vector[i] <- dock3_table[i]}

# name the vector
names(Q8IZD9_vector) <- names(dock3_table)

PID table

pairwise alignment for human, chimpanze, mouse and rat.

#Chimps: XP_516488.4
chimps_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "XP_516488.4",
                         rettype = "fasta")

#Human: NP_004938.1
human_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "NP_004938.1",
                         rettype = "fasta")

#Fruit_Fly: NP_700462.2
mouse_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "NP_700462.2",
                         rettype = "fasta")

#Cattle: XP_001089458
cynomolgus_monkey_fasta <- rentrez::entrez_fetch(db = "protein",
                        id = "XP_001089458",
                         rettype = "fasta")
#BiocManager::install("fasta_cleaner")
chimps_vector <- fasta_cleaner(chimps_fasta)
human_vector <- fasta_cleaner(human_fasta)
mouse_vector <- fasta_cleaner(mouse_fasta)
cynomolgus_monkey_vector <- fasta_cleaner(cynomolgus_monkey_fasta)
data(package="Biostrings")
chimps_string <- paste(chimps_vector,collapse = "") 
human_string <- paste(human_vector,collapse = "" )
mouse_string <- paste(mouse_vector,collapse = "")
cynomolgus_monkey_string <- paste(cynomolgus_monkey_vector,collapse = "")
chimps_string   <- toupper(chimps_string)
human_string   <- toupper(human_string)
mouse_string   <- toupper(mouse_string)
cynomolgus_monkey_string   <- toupper(cynomolgus_monkey_string)
data(BLOSUM50)
#CHIMPS VS OTHER

chimps_vs_human <- Biostrings::pairwiseAlignment(chimps_string, 
                                               human_string,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
chimps_vs_mouse <- Biostrings::pairwiseAlignment(chimps_string, 
                                               mouse_string,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
chimps_vs_cynomolgus_monkey <- Biostrings::pairwiseAlignment(chimps_string, 
                                               cynomolgus_monkey_string ,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
pid(chimps_vs_human)
## [1] 98.20301
pid(chimps_vs_mouse)
## [1] 96.45459
pid(chimps_vs_cynomolgus_monkey)
## [1] 97.13453
#HUMAN VS OTHER


human_vs_mouse <- Biostrings::pairwiseAlignment(human_string, 
                                               mouse_string,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
human_vs_cynomolgus_monkey <- Biostrings::pairwiseAlignment(human_string, 
                                               cynomolgus_monkey_string ,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
pid(human_vs_mouse)
## [1] 98.12808
pid(human_vs_cynomolgus_monkey)
## [1] 98.37438
#mouse VS OTHER

mouse_vs_cynomolgus_monkey <- Biostrings::pairwiseAlignment(mouse_string,
                                               cynomolgus_monkey_string ,
                                               substitutionMatrix = BLOSUM50,
                                               gapOpening = -8, 
                                               gapExtension = -2, 
                                               scoreOnly = FALSE)
pid(mouse_vs_cynomolgus_monkey)
## [1] 96.74877
pids <- c(1,          NA,     NA,     NA,
          98.20301,    1,     NA,     NA,
          96.45459, 98.12808,  1,     NA,
          97.13453,  98.37438, 96.74877, 1)

mat <- matrix(pids, nrow = 4, byrow = T)
row.names(mat) <- c("CHIMPS","HUMANS","MOUSE","CYNOMOLGUS_MONKEY")   
colnames(mat) <- c("CHIMPS","HUMANS","MOUSE","CYNOMOLGUS_MONKEY")   
pander::pander(mat)
  CHIMPS HUMANS MOUSE CYNOMOLGUS_MONKEY
CHIMPS 1 NA NA NA
HUMANS 98.2 1 NA NA
MOUSE 96.45 98.13 1 NA
CYNOMOLGUS_MONKEY 97.13 98.37 96.75 1 
#PID methods comparison
#chimps vs human

pid(chimps_vs_human, type = "PID1")
## [1] 98.20301
pid(chimps_vs_human, type = "PID2")
## [1] 99.60591
pid(chimps_vs_human, type = "PID3")
## [1] 99.60591
pid(chimps_vs_human, type = "PID4")
## [1] 98.89949
pids_comparison <- c("PID1",  98.23875, "(aligned_positions_PLUS_internal_gap_positions)",
                     "PID2",  98.23875, "(aligned_positions)",
                     "PID3",  98.23875, "(length_shorter_sequence)",
                     "PID4",  98.23875, "(average_length_of_the_two_sequences)")

mat <- matrix(pids_comparison, nrow = 4, byrow = T)
row.names(mat) <- c("1","2","3","4")   
colnames(mat) <- c("Method","PID","denominator")   
pander::pander(mat)
Method PID denominator
PID1 98.23875 (aligned_positions_PLUS_internal_gap_positions)
PID2 98.23875 (aligned_positions)
PID3 98.23875 (length_shorter_sequence)
PID4 98.23875 (average_length_of_the_two_sequences) 
#Multiple sequence alignment


a1 <- entrez_fetch(db = "protein", 
                          id = "NP_004938.1", 
                          rettype = "fasta")
a2 <- entrez_fetch(db = "protein", 
                          id = "XP_516488.4", 
                          rettype = "fasta")
a3 <- entrez_fetch(db = "protein", 
                          id = "NP_700462.2", 
                          rettype = "fasta")
a4 <- entrez_fetch(db = "protein", 
                          id = "NP_001008222.1", 
                          rettype = "fasta")
a5 <- entrez_fetch(db = "protein", 
                          id = "XP_001089458.2", 
                          rettype = "fasta")

a1 <- fasta_cleaner(a1,  parse = F)
a2 <- fasta_cleaner(a2,  parse = F)
a3 <- fasta_cleaner(a3,  parse = F)
a4 <- fasta_cleaner(a4,  parse = F)
a5 <- fasta_cleaner(a5,  parse = F)
TABLE <- c("NP_004938.1",     "Homo_sapiens",            "a1",
           "XP_516488.4",  "Pan_troglodytes",         "a2",
           "NP_700462.2",  "Mus_musculus",              "a3",
           "NP_001008222.1",  "Homo_sapiens",            "a4",
           "XP_001089458.2",  "Macaca_mulatta", "a5" )


TABLE_matrix <- matrix(TABLE,
                                  byrow = T,
                                  nrow = 5)

table <- data.frame(TABLE_matrix, 
                     stringsAsFactors = F)


names(table) <- c("accession", "name.orig","name.new")
table$accession
## [1] "NP_004938.1"    "XP_516488.4"    "NP_700462.2"    "NP_001008222.1"
## [5] "XP_001089458.2"
LIST <- entrez_fetch(db = "protein", 
                          id = table$accession, 
                          rettype = "fasta")
cat(LIST)
## >NP_004938.1 dedicator of cytokinesis protein 3 [Homo sapiens]
## MWTPTEEEKYGVVICSFRGSVPQGLVLEIGETVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVS
## NRGQYETVVPLEDSIVTEVTATLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVR
## EVKRHITVRLDWGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCR
## MPVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERMCALFTDLSS
## KDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSLTEVKEEKDFVLKVYTCNNE
## SEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQIRRENPMIFNRGLAITRKLGFPDVIMPGDI
## RNDLYLTLEKGDFERGGKSVQKNIEVTMYVLYADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEI
## IKLPIPIDRFRGSHLRFEFRHCSTKDKGEKKLFGFAFSTLMRDDGTTLSDDIHELYVYKCDENSTFNNHA
## LYLGLPCCKEDYNGCPNIPSSLIFQRSTKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDVLGRLR
## HVSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQKHFAGALAY
## KELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGMEEEQFRSSIQELFQSIRFV
## LSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEFVRGTLGSMPSTVHIGQSMDVVKLQSIART
## VDSRLFSFSESRRILLPVVLHHIHLHLRQQKELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDV
## LLQTLLTIMSKSHAQEAVRGQRCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKI
## FCVFRNLMKMSVFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQ
## LEIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVRNIMIPIFHD
## MMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYPSLLEKVEQETWRETGISFV
## TSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEINKEEMYIRYIHKLCDMHLQAENYTEAAFT
## LLLYCELLQWEDRPLREFLHYPSQTEWQRKEGLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSL
## SWIRKMEASYYDNIMEQQRLEPEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAM
## QHPNHPDDAILQCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENE
## FKSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHKQVHGNINLL
## SMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVHVLGVGLAVHEKFVHPEMRP
## LHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVLASHSPMSPESIKMTHRHSPMNLMGTGRHS
## SSSLSSHASSEAGNMVMLGDGSMGDAPEDLYHHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHS
## APSQMITSAPSSARGSPSLPDKYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGAC
## KPCSDPNLSVAEKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSAS
## SGVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQPCRSHSAPG
## CVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPRGLHRKAPLPPGSAKEEQARMAWEHGRGEQ
## 
## >XP_516488.4 PREDICTED: dedicator of cytokinesis protein 3 [Pan troglodytes]
## MEENEENMEPKDLQQEHSDYRMLRANGVEGCSPELRKEWSDVICSFRGSVPQGLVLEIGETVQILEKCEG
## WYRGVSTKKPNVKGIFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTATLQEWASLWKQLYVKHKVDL
## FYKLRHVMNELIDLRRQLLSGHLTQDQVREVKRHITVRLDWGNEHLGLDLVPRKDFEVVDSDQISVSDLY
## KMHLSSRQSVQQSTSQVDTMRPRHGETCRMPVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISER
## FLVRLNKNGGPRNPEKIERMCALFTDLSSKDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAV
## LSILDVLQSLTEVKEEKDFVLKVYTCNNESEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQI
## RRENPMIFNRGLAITRKLGFPDVIMPGDIRNDLYLTLEKGDFERGGKSVQKNIEVTMYVLYADGEILKDC
## ISLGSGEPNRSSYHSFVLYHSNSPRWGEIIKLPIPIDRFRGSHLRFEFRHCSTKDKGEKKLFGFAFSPLM
## RDDGTTLSDDIHELYVYKCDENSTFNNHALYLGLPCCKEDYNGCPNIPSSLIFQRSTKESFFISTQLSST
## KLTQNVDLLALLKWKAFPDRIMDVLGRLRHVSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFII
## NLLRDIKYFHFRPVMDTYIQKHFAGALAYKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSR
## ILYSRATCGMEEEQFRSSIQELFQSIRFVLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEF
## VRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRILLPVVLHHIHLHLRQQKELLICSGILG
## SIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHAQEAVRGQRCPQCTAEITGEYVSCLLSL
## LRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMSVFPRDWMVMRLLTSNIIVTTVQYLSSALHK
## NFTETDFDFKVWNSYFSLAVLFINQPSLQLEIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHF
## IPGMIGPFLGVTLVPQPEVRNIMIPIFHDMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFS
## LLTQLFGPYPSLLEKVEQETWRETGISFVTSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEI
## NKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRPLREFLHYPSQTEWQRKEGLCRKIIHYF
## NKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNIMEQQRLEPEFFRVGFYGRKFPFFLRNK
## EYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAILQCDAQYLQIYAVTPIPDYVDVLQMDRVPDR
## VKSFYRVNNVRKFRYDRPFHKGPKDKENEFKSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAI
## QVVENKNQELRSLISQYQHKQVHGNINLLSMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQ
## LKELMQEQVHVLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTNTPRGNVL
## ASHSPMSPESIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGNMVMLGDGSMGDAPEDLYHHMQLAYPNP
## RYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSARGSPSLPDKYRHAREMMLLLPTYRDRPS
## SAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSVAEKGHYSLHFDAFHHPLGDTPPALPARTLRK
## SPLHPIPASPTSPQSGLDGSNSTLSGSASSGVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNADEDLEPP
## YLPVHYSLSESAVLDSIKAQPCRSHSAPGCVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPR
## GLHRKAPLPPGSAKEEQARMAWEHGRGEQ
## 
## >NP_700462.2 dedicator of cytokinesis protein 3 [Mus musculus]
## MWTPTEEEKYGVVICSFRGSVPQGLVLEIGETVQILEKCEGWYRGVSTKKPNVKGLFPANYIHLKKAIVS
## NRGQYETVVPLEDSIVTEVTTTLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVR
## EVKRHITVRLDWGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCR
## MPVPHHFFFSLKSFTYNTIGEDSDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERMCALFTDLSS
## KDMKRDLYIVAHVIRIGRMLLNDSKKGPAHLHYRRPYGCAVLSILDVLQSLTELKEEKDFVLKVYTCNNE
## SEWTQIHENIIRKSSTKYSAPSASHGLIISLQLFRGDMEQIRRENPMIFNRGLAITRKLGFPDVIMPGDI
## RNDLYLTLEKGDFERGGKSVQKNIEVTMYVLYADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEI
## IKLPIPIDRFRGSHLRFEFRHCSTKDKGEKKLFGFAFSPLMRDDGTTLSDDIHELYVYKCDENSTFNNHA
## LYLGLPCCKEDYNGCPNIPSSLIFQRSAKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDILGRLR
## HVSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQKHFAGALAY
## KELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGMEEEQFRSSIQELFQSIRFV
## LSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEFVRGTLGSMPSTVHIGQSMDVVKLQSIART
## VDSRLFSFSESRRILLPVVLHHIHLHLRQQKELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDV
## LLQTLLTIMSKSHAQEAVRGQRCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKI
## FCVFRNLMKMSVFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQ
## LEIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGDHKIHFIPGMIGPFLGVTLVPQPEVRNIMIPIFHD
## MMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFGLLTQLFGPYPSLLEKVEQETWRETGISFV
## TSVTRLMERLLDYRDCMKGEETENKKVGCTVNLMNFYKSEINKEEMYIRYIHKLCDMHLQAENYTEAAFT
## LLLYCELLQWEDRPLREFLHYPSQTEWQRKEGLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSL
## SWIRKMEASYYDNIIEQQRLEPEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAM
## QHPNHPDDAILQCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKDNE
## FKSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRALISQYQHKQVHGNINLL
## SMCLNGVIDAAVNGGIARYQEAFFDKDYITKHPGDAEKISQLKELMQEQVHVLGVGLAVHEKFVHPEMRP
## LHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVLASHSPMSPENIKMTHRHSPMNLMGTGRHS
## SSSLSSHASSEAGNMMMMGDNSMGEAPEDLYHHMQLAYHNPRYQGSVTNVSVLSSSQASPSSSSLSSTHS
## APSQMITSAPSSTRGSPSLPDKYRHAREMMLLLPTHRDRPSSAMYPAAILENGQPPNFQRALFQQVVGAC
## KPCSDPNLSMAEKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSAS
## SGVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNGDEDLEPPYLPVHYSLSESAVLDAIKSQPCRSHSAPG
## CVLPQDPMDPPALPPKPYHPRLPALEHDEGMLLREEAERPRGLHRKASLPPGSVKEEQARLAWEHGRGEQ
## 
## >NP_001008222.1 alpha-amylase 1A precursor [Homo sapiens]
## MKLFWLLFTIGFCWAQYSSNTQQGRTSIVHLFEWRWVDIALECERYLAPKGFGGVQVSPPNENVAIHNPF
## RPWWERYQPVSYKLCTRSGNEDEFRNMVTRCNNVGVRIYVDAVINHMCGNAVSAGTSSTCGSYFNPGSRD
## FPAVPYSGWDFNDGKCKTGSGDIENYNDATQVRDCRLSGLLDLALGKDYVRSKIAEYMNHLIDIGVAGFR
## IDASKHMWPGDIKAILDKLHNLNSNWFPEGSKPFIYQEVIDLGGEPIKSSDYFGNGRVTEFKYGAKLGTV
## IRKWNGEKMSYLKNWGEGWGFMPSDRALVFVDNHDNQRGHGAGGASILTFWDARLYKMAVGFMLAHPYGF
## TRVMSSYRWPRYFENGKDVNDWVGPPNDNGVTKEVTINPDTTCGNDWVCEHRWRQIRNMVNFRNVVDGQP
## FTNWYDNGSNQVAFGRGNRGFIVFNNDDWTFSLTLQTGLPAGTYCDVISGDKINGNCTGIKIYVSDDGKA
## HFSISNSAEDPFIAIHAESKL
## 
## >XP_001089458.2 PREDICTED: dedicator of cytokinesis protein 3-like [Macaca mulatta]
## MLIGVFILAFLVICSFRGSVPQGLVLEIGETVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVSN
## RGQYETVVPLEDSIVTEVTATLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVRE
## VKRHITVRLDWGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCRM
## PVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERMCALFTDLSSK
## DMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSLTEVKEEKDFVLKVYTCNNES
## EWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQIRRENPMIFNRGLAITRKLGFPDVIMPGDIR
## NDLYLTLEKGDFERGGKSVQKNIEVTMYVLYADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEII
## KLPIPIDRFRGSHLRFEFRHCSTKDKGEKKLFGFAFSPLMRDDGTTLSDDIHELYVYKCDENSTFNNHAL
## YLGLPCCKEDYNGCPNIPSSLIFQRSTKXXXXXDLLALLKWKAFPDRIMDVLGRLRHVSGEEIVKFLQDI
## LDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQKHFAGALAYKELIRCLKWYMDCS
## AELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGMEEEQFRSSIQELFQSIRFVLSLDSRNSETLLFT
## QAALLNSFPTIFDELLQMFTVQEVAEFVRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRI
## LLPVVLHHIHLHLRQQKELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHA
## QEAVRGQRCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMSVFP
## RDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQLEIITSVKRKKILD
## KYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVRNIMIPIFHDMMDWEQRKNGNFKQ
## VEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYPSLLEKVEQETWRETGISFVTSVTRLMERLLDYR
## DCMKGEETENKKIGCTVNLMNFYKSEINKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRP
## LREFLHYPSQTEWQRKEGLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNI
## MEQQRLEPEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAILQCD
## AQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENEFKSLWIERTTLTLT
## HSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHKQVHGNINLLSMCLNGVIDAAVNG
## GIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVHVLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRA
## SLYHEFPGLDKLSPACSGTSTPRGNVLASHSPMSPESIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGN
## MVMLGDGSMGDAPEDLYHHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSAR
## GSPSLPDKYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSVAEKG
## HYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSASSGVSSLSESNFGHS
## SEVPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQPCRSHSAPGCVIPQDPMDPPALP
## PKPYHPRLPALEHDEGVLLREETERPRGLHRKASLPPGSAKEEQARMAWEHGRGEQ
entrez_fetch_list <- function(db, id, rettype, ...){

  #setup list for storing output
  n.seq <- length(id)
  list.output <- as.list(rep(NA, n.seq))
  names(list.output) <- id

  # get output
  for(i in 1:length(id)){
    list.output[[i]] <- rentrez::entrez_fetch(db = db,
                                              id = id[i],
                                              rettype = rettype)
  }


  return(list.output)
}

list <- entrez_fetch_list(db = "protein", 
                          id =table$accession, 
                          rettype = "fasta")

list[[1]]
## [1] ">NP_004938.1 dedicator of cytokinesis protein 3 [Homo sapiens]\nMWTPTEEEKYGVVICSFRGSVPQGLVLEIGETVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVS\nNRGQYETVVPLEDSIVTEVTATLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVR\nEVKRHITVRLDWGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCR\nMPVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERMCALFTDLSS\nKDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSLTEVKEEKDFVLKVYTCNNE\nSEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQIRRENPMIFNRGLAITRKLGFPDVIMPGDI\nRNDLYLTLEKGDFERGGKSVQKNIEVTMYVLYADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEI\nIKLPIPIDRFRGSHLRFEFRHCSTKDKGEKKLFGFAFSTLMRDDGTTLSDDIHELYVYKCDENSTFNNHA\nLYLGLPCCKEDYNGCPNIPSSLIFQRSTKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDVLGRLR\nHVSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQKHFAGALAY\nKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGMEEEQFRSSIQELFQSIRFV\nLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEFVRGTLGSMPSTVHIGQSMDVVKLQSIART\nVDSRLFSFSESRRILLPVVLHHIHLHLRQQKELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDV\nLLQTLLTIMSKSHAQEAVRGQRCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKI\nFCVFRNLMKMSVFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQ\nLEIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVRNIMIPIFHD\nMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYPSLLEKVEQETWRETGISFV\nTSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEINKEEMYIRYIHKLCDMHLQAENYTEAAFT\nLLLYCELLQWEDRPLREFLHYPSQTEWQRKEGLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSL\nSWIRKMEASYYDNIMEQQRLEPEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAM\nQHPNHPDDAILQCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENE\nFKSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHKQVHGNINLL\nSMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVHVLGVGLAVHEKFVHPEMRP\nLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVLASHSPMSPESIKMTHRHSPMNLMGTGRHS\nSSSLSSHASSEAGNMVMLGDGSMGDAPEDLYHHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHS\nAPSQMITSAPSSARGSPSLPDKYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGAC\nKPCSDPNLSVAEKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSAS\nSGVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQPCRSHSAPG\nCVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPRGLHRKAPLPPGSAKEEQARMAWEHGRGEQ\n\n"
list[[1]] <- fasta_cleaner(list[[1]], parse = F)
list[[2]] <- fasta_cleaner(list[[2]], parse = F)
list[[3]] <- fasta_cleaner(list[[3]], parse = F)
list[[4]] <- fasta_cleaner(list[[4]], parse = F)
list[[5]] <- fasta_cleaner(list[[5]], parse = F)

length(list)
## [1] 5
list_vector <- rep(NA, length(list))
list_vector
## [1] NA NA NA NA NA
for(i in 1:length(list_vector)){
  list_vector[i] <- list[[i]]}

names(list_vector) <- names(list)

list_vector_ss <- Biostrings::AAStringSet(list_vector)

list_align <- msa(list_vector_ss,
                     method = "ClustalW")
## use default substitution matrix
list_align
## CLUSTAL 2.1  
## 
## Call:
##    msa(list_vector_ss, method = "ClustalW")
## 
## MsaAAMultipleAlignment with 5 rows and 2059 columns
##     aln                                                    names
## [1] --------------------------...KAPLPPGSAKEEQARMAWEHGRGEQ NP_004938.1
## [2] MEENEENMEPKDLQQEHSDYRMLRAN...KAPLPPGSAKEEQARMAWEHGRGEQ XP_516488.4
## [3] --------------------------...KASLPPGSAKEEQARMAWEHGRGEQ XP_001089458.2
## [4] --------------------------...KASLPPGSVKEEQARLAWEHGRGEQ NP_700462.2
## [5] --------------------------...------------------------- NP_001008222.1
## Con --------------------------...KA?LPPGSAKEEQARMAWEHGRGEQ Consensus
class(list_align)
## [1] "MsaAAMultipleAlignment"
## attr(,"package")
## [1] "msa"
class(list_align) <- "AAMultipleAlignment"
list_align_seqinr <- msaConvert(list_align, 
                                   type = "seqinr::alignment")

compbio4all::print_msa(alignment = list_align_seqinr, 
          chunksize = 60)
## [1] "-----------------------------MWTPTEEEKYGVVICSFRGSVPQGLVLEIGE 0"
## [1] "MEENEENMEPKDLQQEHSDYRMLRANGVEGCSPELRKEWSDVICSFRGSVPQGLVLEIGE 0"
## [1] "------------------------------MLIGVFILAFLVICSFRGSVPQGLVLEIGE 0"
## [1] "-----------------------------MWTPTEEEKYGVVICSFRGSVPQGLVLEIGE 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "TVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTA 0"
## [1] "TVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTA 0"
## [1] "TVQILEKCEGWYRGVSTKKPNVKGIFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTA 0"
## [1] "TVQILEKCEGWYRGVSTKKPNVKGLFPANYIHLKKAIVSNRGQYETVVPLEDSIVTEVTT 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "TLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVREVKRHITVRLD 0"
## [1] "TLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVREVKRHITVRLD 0"
## [1] "TLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVREVKRHITVRLD 0"
## [1] "TLQEWASLWKQLYVKHKVDLFYKLRHVMNELIDLRRQLLSGHLTQDQVREVKRHITVRLD 0"
## [1] "-----------------MKLFWLLFTIG----------FCWAQYSSNTQQGRTSIVHLFE 0"
## [1] " "
## [1] "WGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCRM 0"
## [1] "WGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCRM 0"
## [1] "WGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCRM 0"
## [1] "WGNEHLGLDLVPRKDFEVVDSDQISVSDLYKMHLSSRQSVQQSTSQVDTMRPRHGETCRM 0"
## [1] "WRWVDIALECER------------------------------------------------ 0"
## [1] " "
## [1] "PVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERM 0"
## [1] "PVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERM 0"
## [1] "PVPHHFFLSLKSFTYNTIGEDTDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERM 0"
## [1] "PVPHHFFFSLKSFTYNTIGEDSDVFFSLYDMREGKQISERFLVRLNKNGGPRNPEKIERM 0"
## [1] "------YLAPKGFGGVQVSPPNENVAIHNPFRPWWERYQPVSYKLCTRSG---------- 0"
## [1] " "
## [1] "CALFTDLSSKDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSL 0"
## [1] "CALFTDLSSKDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSL 0"
## [1] "CALFTDLSSKDMKRDLYIVAHVIRIGRMLLNDSKKGPPHLHYRRPYGCAVLSILDVLQSL 0"
## [1] "CALFTDLSSKDMKRDLYIVAHVIRIGRMLLNDSKKGPAHLHYRRPYGCAVLSILDVLQSL 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "TEVKEEKDFVLKVYTCNNESEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQI 0"
## [1] "TEVKEEKDFVLKVYTCNNESEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQI 0"
## [1] "TEVKEEKDFVLKVYTCNNESEWSQIHENIIRKSSAKYSAPSASHGLIISLQLLRGDMEQI 0"
## [1] "TELKEEKDFVLKVYTCNNESEWTQIHENIIRKSSTKYSAPSASHGLIISLQLFRGDMEQI 0"
## [1] "----NEDEFRNMVTRCNNVGVRIYVDAVINHMCGNAVSAGTSST---------------- 0"
## [1] " "
## [1] "RRENPMIFNRGLAITRKLGFPDVIMPGDIRNDLYLTLEKGDFERGGKSVQKNIEVTMYVL 0"
## [1] "RRENPMIFNRGLAITRKLGFPDVIMPGDIRNDLYLTLEKGDFERGGKSVQKNIEVTMYVL 0"
## [1] "RRENPMIFNRGLAITRKLGFPDVIMPGDIRNDLYLTLEKGDFERGGKSVQKNIEVTMYVL 0"
## [1] "RRENPMIFNRGLAITRKLGFPDVIMPGDIRNDLYLTLEKGDFERGGKSVQKNIEVTMYVL 0"
## [1] "---CGSYFNP-----GSRDFPAVPYSG-------WDFNDGKCKTGSGDIEN--------- 0"
## [1] " "
## [1] "YADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEIIKLPIPIDRFRGSHLRFEFRH 0"
## [1] "YADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEIIKLPIPIDRFRGSHLRFEFRH 0"
## [1] "YADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEIIKLPIPIDRFRGSHLRFEFRH 0"
## [1] "YADGEILKDCISLGSGEPNRSSYHSFVLYHSNSPRWGEIIKLPIPIDRFRGSHLRFEFRH 0"
## [1] "YNDATQVRDCRLSG------------------------LLDLALGKDYVR---------- 0"
## [1] " "
## [1] "CSTKDKGEKKLFGFAFSTLMRDDGTTLSDDIHELYVYKCDENSTFNNHALYLGLPCCKED 0"
## [1] "CSTKDKGEKKLFGFAFSPLMRDDGTTLSDDIHELYVYKCDENSTFNNHALYLGLPCCKED 0"
## [1] "CSTKDKGEKKLFGFAFSPLMRDDGTTLSDDIHELYVYKCDENSTFNNHALYLGLPCCKED 0"
## [1] "CSTKDKGEKKLFGFAFSPLMRDDGTTLSDDIHELYVYKCDENSTFNNHALYLGLPCCKED 0"
## [1] "---------------------------------------SKIAEYMNHLIDIGVAGFRID 0"
## [1] " "
## [1] "YNGCPNIPSSLIFQRSTKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDVLGRLRH 0"
## [1] "YNGCPNIPSSLIFQRSTKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDVLGRLRH 0"
## [1] "YNGCPNIPSSLIFQRSTKXXXXX-------------DLLALLKWKAFPDRIMDVLGRLRH 0"
## [1] "YNGCPNIPSSLIFQRSAKESFFISTQLSSTKLTQNVDLLALLKWKAFPDRIMDILGRLRH 0"
## [1] "AS-----------------------------------------KHMWPGDIKAILDKLHN 0"
## [1] " "
## [1] "VSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQ 0"
## [1] "VSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQ 0"
## [1] "VSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQ 0"
## [1] "VSGEEIVKFLQDILDTLFVILDDNTEKYGLLVFQSLVFIINLLRDIKYFHFRPVMDTYIQ 0"
## [1] "LNSN-------------------------------------------------------- 0"
## [1] " "
## [1] "KHFAGALAYKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGM 0"
## [1] "KHFAGALAYKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGM 0"
## [1] "KHFAGALAYKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGM 0"
## [1] "KHFAGALAYKELIRCLKWYMDCSAELIRQDHIQEAMRALEYLFKFIVQSRILYSRATCGM 0"
## [1] "-----------------WFPEGSKPFIYQEVIDLGGEPIK-------------------- 0"
## [1] " "
## [1] "EEEQFRSSIQELFQSIRFVLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEF 0"
## [1] "EEEQFRSSIQELFQSIRFVLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEF 0"
## [1] "EEEQFRSSIQELFQSIRFVLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEF 0"
## [1] "EEEQFRSSIQELFQSIRFVLSLDSRNSETLLFTQAALLNSFPTIFDELLQMFTVQEVAEF 0"
## [1] "-----------------------------------------------SSDYFGNGRVTEF 0"
## [1] " "
## [1] "VRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRILLPVVLHHIHLHLRQQK 0"
## [1] "VRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRILLPVVLHHIHLHLRQQK 0"
## [1] "VRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRILLPVVLHHIHLHLRQQK 0"
## [1] "VRGTLGSMPSTVHIGQSMDVVKLQSIARTVDSRLFSFSESRRILLPVVLHHIHLHLRQQK 0"
## [1] "KYG-----------------AKLGTVIRKWNGEKMSYLKN-------------------- 0"
## [1] " "
## [1] "ELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHAQEAVRGQ 0"
## [1] "ELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHAQEAVRGQ 0"
## [1] "ELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHAQEAVRGQ 0"
## [1] "ELLICSGILGSIFSIVKTSSLEADVMEEVEMMVESLLDVLLQTLLTIMSKSHAQEAVRGQ 0"
## [1] "--------WGEGWGFMPSD----------------------RALVFVDNHDNQRGHGAGG 0"
## [1] " "
## [1] "RCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMS 0"
## [1] "RCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMS 0"
## [1] "RCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMS 0"
## [1] "RCPQCTAEITGEYVSCLLSLLRQMCDTHFQHLLDNFQSKDELKEFLLKIFCVFRNLMKMS 0"
## [1] "-----------------------------ASILTFWDAR----------------LYKMA 0"
## [1] " "
## [1] "VFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQL 0"
## [1] "VFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQL 0"
## [1] "VFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQL 0"
## [1] "VFPRDWMVMRLLTSNIIVTTVQYLSSALHKNFTETDFDFKVWNSYFSLAVLFINQPSLQL 0"
## [1] "VG------------------------------------------------FMLAHP---- 0"
## [1] " "
## [1] "EIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVR 0"
## [1] "EIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVR 0"
## [1] "EIITSVKRKKILDKYGDMRVMMAYELFSMWQNLGEHKIHFIPGMIGPFLGVTLVPQPEVR 0"
## [1] "EIITSAKRKKILDKYGDMRVMMAYELFSMWQNLGDHKIHFIPGMIGPFLGVTLVPQPEVR 0"
## [1] "--------------YGFTRVMSSYRWPRYFENG--------------------------- 0"
## [1] " "
## [1] "NIMIPIFHDMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYP 0"
## [1] "NIMIPIFHDMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYP 0"
## [1] "NIMIPIFHDMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFSLLTQLFGPYP 0"
## [1] "NIMIPIFHDMMDWEQRKNGNFKQVEAELIDKLDSMVSEGKGDESYRELFGLLTQLFGPYP 0"
## [1] "-------KDVNDWVGPPND--NGVTKEVTINPDTTCGN---------------------- 0"
## [1] " "
## [1] "SLLEKVEQETWRETGISFVTSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEI 0"
## [1] "SLLEKVEQETWRETGISFVTSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEI 0"
## [1] "SLLEKVEQETWRETGISFVTSVTRLMERLLDYRDCMKGEETENKKIGCTVNLMNFYKSEI 0"
## [1] "SLLEKVEQETWRETGISFVTSVTRLMERLLDYRDCMKGEETENKKVGCTVNLMNFYKSEI 0"
## [1] "---DWVCEHRWRQIRN------------MVNFRNVVDGQ-----------PFTNWYDNGS 0"
## [1] " "
## [1] "NKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRPLREFLHYPSQTEWQRKE 0"
## [1] "NKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRPLREFLHYPSQTEWQRKE 0"
## [1] "NKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRPLREFLHYPSQTEWQRKE 0"
## [1] "NKEEMYIRYIHKLCDMHLQAENYTEAAFTLLLYCELLQWEDRPLREFLHYPSQTEWQRKE 0"
## [1] "N---------------------------------------------------QVAFGRGN 0"
## [1] " "
## [1] "GLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNIMEQQRLE 0"
## [1] "GLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNIMEQQRLE 0"
## [1] "GLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNIMEQQRLE 0"
## [1] "GLCRKIIHYFNKGKSWEFGIPLCRELACQYESLYDYQSLSWIRKMEASYYDNIIEQQRLE 0"
## [1] "---RGFIVFNN--DDWTF-------------------SLTLQTGLPAGTYCDVISGDKIN 0"
## [1] " "
## [1] "PEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAIL 0"
## [1] "PEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAIL 0"
## [1] "PEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAIL 0"
## [1] "PEFFRVGFYGRKFPFFLRNKEYVCRGHDYERLEAFQQRMLSEFPQAVAMQHPNHPDDAIL 0"
## [1] "GNCTGIKIY-------------------------VSDDGKAHFSISNSAEDP-------- 0"
## [1] " "
## [1] "QCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENEF 0"
## [1] "QCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENEF 0"
## [1] "QCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKENEF 0"
## [1] "QCDAQYLQIYAVTPIPDYVDVLQMDRVPDRVKSFYRVNNVRKFRYDRPFHKGPKDKDNEF 0"
## [1] "-----FIAIHAESKL--------------------------------------------- 0"
## [1] " "
## [1] "KSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHK 0"
## [1] "KSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHK 0"
## [1] "KSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRSLISQYQHK 0"
## [1] "KSLWIERTTLTLTHSLPGISRWFEVERRELVEVSPLENAIQVVENKNQELRALISQYQHK 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "QVHGNINLLSMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVH 0"
## [1] "QVHGNINLLSMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVH 0"
## [1] "QVHGNINLLSMCLNGVIDAAVNGGIARYQEAFFDKDYINKHPGDAEKITQLKELMQEQVH 0"
## [1] "QVHGNINLLSMCLNGVIDAAVNGGIARYQEAFFDKDYITKHPGDAEKISQLKELMQEQVH 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "VLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVL 0"
## [1] "VLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTNTPRGNVL 0"
## [1] "VLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVL 0"
## [1] "VLGVGLAVHEKFVHPEMRPLHKKLIDQFQMMRASLYHEFPGLDKLSPACSGTSTPRGNVL 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "ASHSPMSPESIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGNMVMLGDGSMGDAPEDLY 0"
## [1] "ASHSPMSPESIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGNMVMLGDGSMGDAPEDLY 0"
## [1] "ASHSPMSPESIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGNMVMLGDGSMGDAPEDLY 0"
## [1] "ASHSPMSPENIKMTHRHSPMNLMGTGRHSSSSLSSHASSEAGNMMMMGDNSMGEAPEDLY 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "HHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSARGSPSLPD 0"
## [1] "HHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSARGSPSLPD 0"
## [1] "HHMQLAYPNPRYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSARGSPSLPD 0"
## [1] "HHMQLAYHNPRYQGSVTNVSVLSSSQASPSSSSLSSTHSAPSQMITSAPSSTRGSPSLPD 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "KYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSVA 0"
## [1] "KYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSVA 0"
## [1] "KYRHAREMMLLLPTYRDRPSSAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSVA 0"
## [1] "KYRHAREMMLLLPTHRDRPSSAMYPAAILENGQPPNFQRALFQQVVGACKPCSDPNLSMA 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "EKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSASS 0"
## [1] "EKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSASS 0"
## [1] "EKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSASS 0"
## [1] "EKGHYSLHFDAFHHPLGDTPPALPARTLRKSPLHPIPASPTSPQSGLDGSNSTLSGSASS 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "GVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQ 0"
## [1] "GVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQ 0"
## [1] "GVSSLSESNFGHSSEVPPRTDTMDSMPSQAWNADEDLEPPYLPVHYSLSESAVLDSIKAQ 0"
## [1] "GVSSLSESNFGHSSEAPPRTDTMDSMPSQAWNGDEDLEPPYLPVHYSLSESAVLDAIKSQ 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "PCRSHSAPGCVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPRGLHRKAPLPP 0"
## [1] "PCRSHSAPGCVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPRGLHRKAPLPP 0"
## [1] "PCRSHSAPGCVIPQDPMDPPALPPKPYHPRLPALEHDEGVLLREETERPRGLHRKASLPP 0"
## [1] "PCRSHSAPGCVLPQDPMDPPALPPKPYHPRLPALEHDEGMLLREEAERPRGLHRKASLPP 0"
## [1] "------------------------------------------------------------ 0"
## [1] " "
## [1] "GSAKEEQARMAWEHGRGEQ 41"
## [1] "GSAKEEQARMAWEHGRGEQ 41"
## [1] "GSAKEEQARMAWEHGRGEQ 41"
## [1] "GSVKEEQARLAWEHGRGEQ 41"
## [1] "------------------- 41"
## [1] " "
class(list_align) <- "AAMultipleAlignment"

ggmsa::ggmsa(list_align,   
      start = 1, 
      end = 50) 

#Distance matrix

list_subset_dist <- seqinr::dist.alignment(list_align_seqinr, 
                                       matrix = "identity")
list_subset_dist
##                NP_004938.1 XP_516488.4 XP_001089458.2 NP_700462.2
## XP_516488.4     0.08002463                                       
## XP_001089458.2  0.08636536  0.08636536                           
## NP_700462.2     0.13681817  0.15536387     0.15609608            
## NP_001008222.1  0.88916065  0.88916065     0.88916065  0.88805952
#Phylogenetic tree for all sequences


tree_subset <- nj(list_subset_dist)

#rooted
plot.phylo(tree_subset, main="Phylogenetic Tree", 
            use.edge.length = F)
mtext(text = "DOCK3 family gene tree - rooted, no branch lenths")