brennanpincardiff / drawproteins Goto Github PK

View Code? Open in Web Editor NEW

33.0 33.0 19.0 916 KB

Creating package to draw proteins from Uniprot API

License: Other

R 100.00%

drawproteins's People

Contributors

Stargazers

Watchers

Forkers

gtuckerkellogg rescalante-lilly yangj9932 lijxug daniel-wells evanrobuca miguelcos alptaciroglu emmamchugh akiessling92 welshsae stevin-wilson erin-r-butterfield joicmajo27 daisysawdon francoherreara258 m-shivkumar maisaadzaghloul jonathandavies509

drawproteins's Issues

Protein isoforms from a gene

Hi,

Thank you for the great package!
I wonder if there is a way to draw multiple isoforms under a single UniProt ID. For example, there are three human NFkB isoforms annotated from the gene: P19838-1, P19838-2, and P19838-3. Can I draw them together to compare? It would be very helpful if I could do this.

Best,

empty chain

Hi. Im using drawProteins to plot the domains of various genes. As a test i followed the script of this page:
http://rforbiochemists.blogspot.com/2018/02/my-drawproteins-package-has-been.html
This worked perfectly well.
When trying to draw the chains for the gene MARCH5 (https://www.uniprot.org/uniprot/Q9NX47#family_and_domains) Im proceeding as follows:
`
prot_data <- drawProteins::get_features("Q9NX47")
# produce data frame
prot_data <- drawProteins::feature_to_dataframe(prot_data)

    # make protein schematic
    p <- draw_canvas(prot_data)
    p <- draw_chains(p, prot_data)
    p <- draw_domains(p, prot_data)

I get a grey chain with no domains (see attached picture).
Although when checking prot_data I can see that there are domain features listed:

> prot                                            
                   type                                                                      
featuresTemp      CHAIN                           
featuresTemp.1 TRANSMEM                           
featuresTemp.2 TRANSMEM                         
featuresTemp.3 TRANSMEM                         
featuresTemp.4 TRANSMEM                          
featuresTemp.5  ZN_FING                                                                                
featuresTemp.6  MUTAGEN                                                                                
featuresTemp.7  MUTAGEN                                                                                
featuresTemp.8  MUTAGEN                                                                                
                                                                                                       
                                                                                  description          
featuresTemp                                                                                           
                                                           E3 ubiquitin-protein ligase MARCH5          
featuresTemp.1                                                                                         
                                                                                      Helical          
featuresTemp.2                                                                                         
                                                                                      Helical          
featuresTemp.3                                                                                         
                                                                                      Helical          
featuresTemp.4                                                                                         
                                                                                      Helical          
featuresTemp.5                                                                                         
                                                                                 RING-CH-type          
featuresTemp.6 Loss of ubiquitin ligase activity, formation of highly interconnected mitochondria, chan
ge in mitochondria morphology that in turns triggers senescence, and perinuclear accumulation          
featuresTemp.7                                         Loss of E3 ubiquitin ligase activity. Formation
of highly interconnected mitochondria and perinuclear accumulation; when associated with S-68
featuresTemp.8                                         Loss of E3 ubiquitin ligase activity. Formation
of highly interconnected mitochondria and perinuclear accumulation; when associated with S-65
               begin end length accession   entryName taxid order            
featuresTemp       1 278    277    Q9NX47 MARH5_HUMAN  9606     1        
featuresTemp.1    99 119     20    Q9NX47 MARH5_HUMAN  9606     1       
featuresTemp.2   139 159     20    Q9NX47 MARH5_HUMAN  9606     1        
featuresTemp.3   209 229     20    Q9NX47 MARH5_HUMAN  9606     1        
featuresTemp.4   238 258     20    Q9NX47 MARH5_HUMAN  9606     1   
featuresTemp.5     6  75     69    Q9NX47 MARH5_HUMAN  9606     1            
featuresTemp.6    43  43      0    Q9NX47 MARH5_HUMAN  9606     1                  
featuresTemp.7    65  65      0    Q9NX47 MARH5_HUMAN  9606     1                                      
featuresTemp.8    68  68      0    Q9NX47 MARH5_HUMAN  9606     1

Did I do sth wrong or is there simply not more data to be retrieved?

Thanks in advance

`Running under: Ubuntu 14.04.5 LTS

Matrix products: default
BLAS: /usr/lib/libblas/libblas.so.3.0
LAPACK: /usr/lib/lapack/liblapack.so.3.0

locale:
[1] LC_CTYPE=en_DK.UTF-8 LC_NUMERIC=C
[3] LC_TIME=en_DK.UTF-8 LC_COLLATE=en_DK.UTF-8
[5] LC_MONETARY=en_DK.UTF-8 LC_MESSAGES=en_DK.UTF-8
[7] LC_PAPER=en_DK.UTF-8 LC_NAME=C
[9] LC_ADDRESS=C LC_TELEPHONE=C
[11] LC_MEASUREMENT=en_DK.UTF-8 LC_IDENTIFICATION=C

attached base packages:
[1] stats4 parallel stats graphics grDevices utils
[7] datasets methods base

other attached packages:
[1] ggplot2_3.1.0 drawProteins_1.2.0
[3] ensembldb_2.6.3 AnnotationFilter_1.6.0
[5] GenomicFeatures_1.34.1 AnnotationDbi_1.44.0
[7] Biobase_2.41.2 GenomicRanges_1.32.4
[9] GenomeInfoDb_1.18.1 IRanges_2.15.16
[11] S4Vectors_0.19.19 BiocGenerics_0.28.0
[13] nvimcom_0.9-58

loaded via a namespace (and not attached):
[1] Rcpp_0.12.18 lattice_0.20-38
[3] prettyunits_1.0.2 Rsamtools_1.33.3
[5] Biostrings_2.49.0 assertthat_0.2.0
[7] digest_0.6.15 R6_2.3.0
[9] plyr_1.8.4 RSQLite_2.1.1
[11] httr_1.3.1 pillar_1.3.0
[13] zlibbioc_1.28.0 rlang_0.3.0.1
[15] progress_1.2.0 lazyeval_0.2.1
[17] curl_3.2 blob_1.1.1
[19] Matrix_1.2-15 labeling_0.3
[21] BiocParallel_1.15.8 stringr_1.3.1
[23] ProtGenerics_1.14.0 RCurl_1.95-4.11
[25] bit_1.1-14 biomaRt_2.38.0
[27] munsell_0.5.0 DelayedArray_0.7.21
[29] compiler_3.5.1 rtracklayer_1.41.3
[31] pkgconfig_2.0.2 tidyselect_0.2.4
[33] SummarizedExperiment_1.10.1 tibble_1.4.2
[35] GenomeInfoDbData_1.2.0 matrixStats_0.54.0
[37] XML_3.98-1.12 withr_2.1.2
[39] crayon_1.3.4 dplyr_0.7.7
[41] GenomicAlignments_1.16.0 bitops_1.0-6
[43] grid_3.5.1 jsonlite_1.5
[45] gtable_0.2.0 DBI_1.0.0
[47] magrittr_1.5 scales_1.0.0
[49] stringi_1.2.4 XVector_0.21.3
[51] bindrcpp_0.2.2 tools_3.5.1
[53] bit64_0.9-7 glue_1.3.0
[55] purrr_0.2.5 hms_0.4.2
[57] colorspace_1.3-2 memoise_1.1.0
[59] bindr_0.1.1 `

Easy way of displaying exons?

Hello there,

Today I started to learn how to use this great package, this is going to be very useful for at least two publications I am trying to wrap up :)

I am interested to use these schematics to show the effect of some alternative splicing events into domains. Do you know of a n easy way of plotting the exons into the proteins? I think I should be able to extract this information manually and then using the draw_domains function. However, it would be handy if you know of more smooth way to do automatically extract this information.

Any guide or help on this would be very well appreciated!
Thanks

feature category of legend

Hi, I was wondering if it is possible to get a description for the legend. In the case of drawing all features of the protein it is unclear what the legend is actually describing. as in, is it a motif, or a repeat...etc?

Export SVG and test SVG

As discussed @CardiffRUG, there must be a way to export an SVG from ggplot and then set up a unit test to compare the objects.

Need to add the option to show a legend for each of the draw functions

This shouldn't be too difficult but will really help plotting control.
I think it's a normal function in ggplot2...

Set an external scale for the plot...

This can be done manually I think - maybe we need a use case....

Useful for data plotting

Hey, Great package!

i am very, very new to R

Would it be possible to use drawprotiens, to create the protein schematic and put it directly below an X axis, containing amino acid number, and have Y as something else? (i.e FATHMM scores?)

Figure from: Millán Ortiz, Nicolas Guex, Etienne Patin, Olivier Martin, Ioannis Xenarios, Angela Ciuffi, Lluís Quintana-Murci, Amalio Telenti, Evolutionary Trajectories of Primate Genes Involved in HIV Pathogenesis, Molecular Biology and Evolution, Volume 26, Issue 12, December 2009, Pages 2865–2875, https://doi.org/10.1093/molbev/msp197
My thought process was -
Draw the protien
set to y= -(n, where n looks the best!)

Then plot my actual Y values

Error in draw_chains function, incomplete representation

I´m trying to show 7 proteins of different CoVs, 4 of these proteins (red arrows) show only part of the protein S2 (subunit 2).
I don´t understand why this happens. I reviewed if the protein in Uniprot is complete and it looks like that all is fine.
Here is my script:

data <- drawProteins::get_features("P0DTC2 A0A6B9WHD3 A0A6M3G9R1 P59594 E0XIZ3 K9N5Q8 U5NJG5")

p <- draw_canvas(real_data)
p <- draw_chains(p, real_data, label_size =  2.5)
p <- draw_domains(p, real_data, show.legend = F, label_domains = F)
p <- draw_motif(p, real_data)

p <- p + theme_bw(base_size = 10) +
  theme(panel.grid.minor = element_blank(),
        panel.grid.major = element_blank()) +
  theme(axis.ticks = element_blank(),
        axis.text.y = element_blank()) +
  theme(panel.border = element_blank())

So, clearly, there is a issue in these protein draws, that only shows the S2.
There is a way to force the code to show the complete protein?

Here is the plot

error in draw_canvas(rel_data) : could not find function "draw_canvas"

Hello,

I have installed the software following the instruction on the github page. It can read, however, despite the multiple installations I get the same error: error in draw_canvas(rel_data) : could not find function "draw_canvas".
Do you know what can be the problem?

Roberto

Control position of chain labels

Hi @brennanpincardiff,

I'm trying to plot a figure similar to Fig. 1A at https://academic.oup.com/view-large/figure/77823485/molbiolevolmss081f01_3c.jpeg.

How can I plot the chain labels on the top left of for each chain? Maybe it could also be useful to add additional labels (e.g. protein size) to add additional information.

Best,
Jan

Additional control of legend colours

Hi @brennanpincardiff,

By default drawProteins appears to use some sort of rainbow colour scheme which become hard to read when there are more than 5 feature types/categories displayed in the legend.

I think it would be great to have more control of the legend colours for protein features.

Best,
Jan

Label with description (or other names)

Sometimes the info in the description or other names are more useful.
I need to add a way to include/allow this.

flip a chain...

While drawing receptors, if we want to draw type I and type II receptors on the same image, we need to be able to flip some of the chains. This is interesting and creates some challenges.
Might be better to plot separately and combine the plots... Can we keep the scale?

Write script/vignette to show how to use drawProteins with BiomaRt

It's possible to get Uniprot Accession numbers out of BiomaRt. Writing a vignette or at least a script to demonstrate this would be very helpful.

Add a test for whole ggplot object

Control the behaviour of domain labels

I was trying to figure out how to vertically flip domain labels for a large protein.

The issue was solved by modifying draw_domains function. Switched to 'geom_text' layer on top of 'geom_rect' layer (latter serves as a box for the text). The original function uses geom_label layer instead.

Also added scale_fill_npg() function from 'ggsci' package which is totally optional. Dropping this here in case it is useful for others.

library(ggsci)
draw_domains <- function(p,
                         data = data,
                         label_domains = TRUE,
                         label_size = 4,
                         show.legend = TRUE,
                         type = "DOMAIN"){
  begin=end=description=NULL
  
  p <- p + ggplot2::geom_rect(data= data[data$type == type,],
                              mapping=ggplot2::aes(xmin=begin,
                                                   xmax=end,
                                                   ymin=order-0.25,
                                                   ymax=order+0.25,
                                                   fill=description),
                              show.legend = show.legend) + scale_fill_npg()
  
  if(label_domains == TRUE){
    ## xmin, xmax values can be optimized for better visualization
    p <- p + geom_rect(data = data[data$type == type, ], 
                       ggplot2::aes(xmin = (begin + (end-begin)/2 - 40), xmax = (begin + (end-begin)/2 + 50), 
                                    ymin = (order - 0.05), ymax = (order + 0.05)), fill = "grey80", alpha = 0.75) + 
      ggplot2::geom_text(data = data[data$type == type, ],
                         ggplot2::aes(x = begin + (end-begin)/2, y = order, label = description),
                         size = label_size, angle = 90)
  }
  
  return(p)
}

Option to draw vertical.

It would be good to have a way to draw receptors aligned by their transmembrane proteins. Could just rotate the image but that's crude. A proper way needs to be conceived.

How to draw protein features not supported by any of the draw_* functions?

Hi @brennanpincardiff,

very useful package!

I have a similar issue as described at #13 (comment) trying to find the best solution to plot types currently not supported by any of the draw_* function.

I'm trying to draw schematics for multiple proteins and I'm currently looking for the best way to draw coiled coil domains (prot_data$type == "COILED") and compositional bias regions (prot_data$type == "COMPBIAS").

My prot_data frame looks as follows:

> my.prot_data
       type   description begin  end length accession    entryName taxid order
1     CHAIN PF3D7_0530300     1 1446   1445    C0H4G8 C0H4G8_PLAF7 36329     1
2  TRANSMEM       Helical    20   39     19    C0H4G8 C0H4G8_PLAF7 36329     1
3  TRANSMEM       Helical    91  115     24    C0H4G8 C0H4G8_PLAF7 36329     1
4  TRANSMEM       Helical  1422 1441     19    C0H4G8 C0H4G8_PLAF7 36329     1
5    REGION    Disordered   568  599     31    C0H4G8 C0H4G8_PLAF7 36329     1
6    REGION    Disordered   611  648     37    C0H4G8 C0H4G8_PLAF7 36329     1
7    COILED          NONE   328  348     20    C0H4G8 C0H4G8_PLAF7 36329     1
8  TRANSMEM       Helical   779  805     26    C0H4G8 C0H4G8_PLAF7 36329     1
9  TRANSMEM       Helical   857  880     23    C0H4G8 C0H4G8_PLAF7 36329     1
10 TRANSMEM       Helical   886  906     20    C0H4G8 C0H4G8_PLAF7 36329     1
11 TRANSMEM       Helical  1252 1272     20    C0H4G8 C0H4G8_PLAF7 36329     1
12 TRANSMEM       Helical  1292 1314     22    C0H4G8 C0H4G8_PLAF7 36329     1
13 TRANSMEM       Helical  1326 1343     17    C0H4G8 C0H4G8_PLAF7 36329     1
14 TRANSMEM       Helical  1363 1381     18    C0H4G8 C0H4G8_PLAF7 36329     1
15 TRANSMEM       Helical  1393 1416     23    C0H4G8 C0H4G8_PLAF7 36329     1
16    CHAIN PF3D7_0415800     1  875    874    Q8I1S9 Q8I1S9_PLAF7 36329     2
17   REGION    Disordered   560  611     51    Q8I1S9 Q8I1S9_PLAF7 36329     2
18 COMPBIAS         Polar   560  599     39    Q8I1S9 Q8I1S9_PLAF7 36329     2
19   DOMAIN     RING-type    79  117     38    Q8I1S9 Q8I1S9_PLAF7 36329     2
20    CHAIN PF3D7_0508900     1 3134   3133    Q8I414 Q8I414_PLAF7 36329     3
21   COILED          NONE  3073 3093     20    Q8I414 Q8I414_PLAF7 36329     3
22 COMPBIAS         Polar   728  745     17    Q8I414 Q8I414_PLAF7 36329     3
23 COMPBIAS Polyampholyte   746  794     48    Q8I414 Q8I414_PLAF7 36329     3
24 COMPBIAS Polyampholyte   931  954     23    Q8I414 Q8I414_PLAF7 36329     3
25 COMPBIAS Polyampholyte  1739 1759     20    Q8I414 Q8I414_PLAF7 36329     3
26 COMPBIAS         Polar  1760 1799     39    Q8I414 Q8I414_PLAF7 36329     3
27 COMPBIAS        Acidic  2487 2771    284    Q8I414 Q8I414_PLAF7 36329     3
28   REGION    Disordered   817  844     27    Q8I414 Q8I414_PLAF7 36329     3
29   REGION    Disordered   931  965     34    Q8I414 Q8I414_PLAF7 36329     3
30   REGION    Disordered  1739 1801     62    Q8I414 Q8I414_PLAF7 36329     3
31   REGION    Disordered  2335 2371     36    Q8I414 Q8I414_PLAF7 36329     3
32   REGION    Disordered  2476 2771    295    Q8I414 Q8I414_PLAF7 36329     3
33   COILED          NONE   660  680     20    Q8I414 Q8I414_PLAF7 36329     3
34   COILED          NONE   862  882     20    Q8I414 Q8I414_PLAF7 36329     3
35   COILED          NONE  1520 1540     20    Q8I414 Q8I414_PLAF7 36329     3
36   COILED          NONE  2875 2895     20    Q8I414 Q8I414_PLAF7 36329     3
37   REGION    Disordered   714  797     83    Q8I414 Q8I414_PLAF7 36329     3
38    CHAIN PF3D7_1229300     1  990    989    Q8I5C6 Q8I5C6_PLAF7 36329     4
39   REGION    Disordered    83  106     23    Q8I5C6 Q8I5C6_PLAF7 36329     4
40   REGION    Disordered   333  355     22    Q8I5C6 Q8I5C6_PLAF7 36329     4
41   REGION    Disordered   429  453     24    Q8I5C6 Q8I5C6_PLAF7 36329     4
42   REGION    Disordered   751  771     20    Q8I5C6 Q8I5C6_PLAF7 36329     4
43 COMPBIAS Polyampholyte    38   58     20    Q8I5C6 Q8I5C6_PLAF7 36329     4
44 COMPBIAS Polyampholyte    86  105     19    Q8I5C6 Q8I5C6_PLAF7 36329     4
45   REGION    Disordered    38   71     33    Q8I5C6 Q8I5C6_PLAF7 36329     4
46    CHAIN PF3D7_0822900     1 1176   1175    Q8IB63 Q8IB63_PLAF7 36329     5
47 COMPBIAS        Acidic   266  372    106    Q8IB63 Q8IB63_PLAF7 36329     5
48 COMPBIAS         Polar   373  417     44    Q8IB63 Q8IB63_PLAF7 36329     5
49   REGION    Disordered   976  995     19    Q8IB63 Q8IB63_PLAF7 36329     5
50   REGION    Disordered  1010 1032     22    Q8IB63 Q8IB63_PLAF7 36329     5
51   COILED          NONE     7   30     23    Q8IB63 Q8IB63_PLAF7 36329     5
52 COMPBIAS         Basic    55   69     14    Q8IB63 Q8IB63_PLAF7 36329     5
53 COMPBIAS Polyampholyte    70   91     21    Q8IB63 Q8IB63_PLAF7 36329     5
54 COMPBIAS         Polar    92  173     81    Q8IB63 Q8IB63_PLAF7 36329     5
55 COMPBIAS Polyampholyte   175  196     21    Q8IB63 Q8IB63_PLAF7 36329     5
56 COMPBIAS         Basic   197  214     17    Q8IB63 Q8IB63_PLAF7 36329     5
57 COMPBIAS Polyampholyte   235  257     22    Q8IB63 Q8IB63_PLAF7 36329     5
58   REGION    Disordered    53  425    372    Q8IB63 Q8IB63_PLAF7 36329     5
59    CHAIN PF3D7_1318700     1  749    748    Q8IEC9 Q8IEC9_PLAF7 36329     6
60   REGION    Disordered   705  749     44    Q8IEC9 Q8IEC9_PLAF7 36329     6
61   COILED          NONE   232  259     27    Q8IEC9 Q8IEC9_PLAF7 36329     6
62   COILED          NONE   274  332     58    Q8IEC9 Q8IEC9_PLAF7 36329     6
63   COILED          NONE   432  466     34    Q8IEC9 Q8IEC9_PLAF7 36329     6
64   COILED          NONE   495  515     20    Q8IEC9 Q8IEC9_PLAF7 36329     6
65   COILED          NONE   562  600     38    Q8IEC9 Q8IEC9_PLAF7 36329     6
66 COMPBIAS         Polar   385  412     27    Q8IEC9 Q8IEC9_PLAF7 36329     6
67   REGION    Disordered   385  415     30    Q8IEC9 Q8IEC9_PLAF7 36329     6
68    CHAIN PF3D7_1312800     1 2361   2360    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
69   COILED          NONE  1001 1028     27    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
70   REGION    Disordered   148  195     47    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
71 COMPBIAS Polyampholyte    61   87     26    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
72 COMPBIAS Polyampholyte   148  185     37    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
73 COMPBIAS Polyampholyte  1242 1315     73    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
74 COMPBIAS Polyampholyte  1646 1685     39    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
75 COMPBIAS         Polar  1686 1718     32    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
76 COMPBIAS Polyampholyte  1719 1736     17    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
77 COMPBIAS Polyampholyte  1935 1969     34    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
78 COMPBIAS        Acidic  1970 2017     47    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
79 COMPBIAS Polyampholyte  2046 2064     18    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
80 COMPBIAS         Polar  2065 2109     44    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
81 COMPBIAS Polyampholyte  2110 2177     67    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
82 COMPBIAS         Polar  2178 2194     16    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
83 COMPBIAS Polyampholyte  2195 2245     50    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
84   REGION    Disordered  1229 1315     86    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
85   REGION    Disordered  1404 1436     32    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
86   REGION    Disordered  1638 1753    115    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
87   REGION    Disordered  1786 1813     27    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
88   REGION    Disordered  1935 2252    317    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
89   REGION    Disordered  2341 2361     20    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
90   COILED          NONE   282  302     20    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
91   COILED          NONE   433  453     20    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
92   REGION    Disordered    61   92     31    Q8IEJ4 Q8IEJ4_PLAF7 36329     7
93    CHAIN PF3D7_0308300     1  337    336    O77324 O77324_PLAF7 36329     8

I tried to use the following to draw coiled coil domains (which works):

### add COILED block in blue
p <- p + ggplot2::geom_rect(data = my.prot_data[my.prot_data$type == "COILED",],
                            mapping=ggplot2::aes(xmin=begin,
                                                 xmax=end,
                                                 ymin=order-0.2,
                                                 ymax=order+0.2),
                            fill = "blue")
p

Yet, I'm currently not sure what the best way is to add coiled coils to the legend?

Alternatively, I think I could just (manually) define coiled coils as domain types and maybe compositional bias as region type?!

I would be very happy about feedback and suggestions.

Many thanks in advance!

Annotation Glycosylation

Hello, I found this tool very useful for protein visualization. Will it be possible to include in the graphs information about glycosylation sites based on the information on the Uniprot website?, I am quite new to R, it is very likely someone had already asked this, apologies

Adding peptide coverage information

Hello. I am very glad to know about this package.

I am working on a way to represent peptide coverage over a protein sequence (i. e. represent peptides identified by MS over the whole protein). I think this could be a very good implementation for this package.

brennanpincardiff / drawproteins Goto Github PK

drawproteins's People

Contributors

Stargazers

Watchers

Forkers

drawproteins's Issues

Recommend Projects

Recommend Topics

Recommend Org