-
Notifications
You must be signed in to change notification settings - Fork 8
/
Copy pathui.R
1612 lines (1527 loc) · 145 KB
/
ui.R
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
867
868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
function(request) {
sidebar <- dashboardSidebar(
useShinyjs(),
includeCSS("www/custom_shaman.css"),
inlineCSS(appCSS),
# tags$head(
# tags$script(src = "custom.js")
# ),
div(id = "loading-content-bar",
p()),
div(
id = "app-content-bar",
sidebarMenu(id = "side",
menuItem("Home", tabName = "Home", icon = icon("home")),
menuItem("Tutorial", tabName = "Tutorial", icon = icon("book")),
menuItem("Download/Install", tabName = "Download", icon = icon("download")),
menuItem("Raw data", tabName = "RawData", icon = icon("upload")),
menuItem("Upload your data", tabName = "Upload", icon = icon("upload")),
#bookmarkButton(),
menuItemOutput("dymMenu"),
img(src = "logo.jpg", height = 49, width = 220,style="position:absolute;bottom:0;margin:0 0 15px 10px;")
)
)
)
body <- dashboardBody(
tags$style(type="text/css", Errorcss),
useToastr(),
useShinyjs(),
inlineCSS(appCSS),
div(
id = "loading-content",
br(),
br(),
br(),
h2("Please wait while SHAMAN is loading...")),
div(
id = "app-content-bar",
tabItems(
tabItem(tabName = "Home",
fluidRow(
column(width=9,
div(style="width:100% ; max-width: 1200px; height: 550px",
tabBox(title="Welcome to SHAMAN", id="tabset1", width=NULL,
# tags$script(type="text/javascript", language="javascript", src="google-analytics.js"),
tabPanel("About",
p("SHAMAN is a shiny application for differential analysis of metagenomic data (16S, 18S, 23S, 28S, ITS and WGS) including bioinformatics treatment of raw reads for targeted metagenomics, statistical analysis and results visualization with a large variety of plots (barplot, boxplot, heatmap, …).",style = "font-family: 'times'; font-si16pt"),
p("The bioinformatics treatment is based on Vsearch", a("[Rognes 2016]", href="http://www.ncbi.nlm.nih.gov/pubmed/27781170"), "which showed to be both accurate and fast", a("[Wescott 2015]", href="http://www.ncbi.nlm.nih.gov/pubmed/26664811"),". The statistical analysis is based on DESeq2 R package", a("[Anders and Huber 2010]", href="http://www.ncbi.nlm.nih.gov/pubmed/20979621"),
"which robustly identifies the differential abundant features as suggested in", a("[McMurdie and Holmes 2014,",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3974642/"),a("Jonsson2016]",href="http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4727335/"),
". SHAMAN robustly identifies the differential abundant genera with the Generalized Linear Model implemented in DESeq2", a("[Love 2014]", href="http://www.ncbi.nlm.nih.gov/pubmed/25516281"),".",
"SHAMAN is compatible with standard formats for metagenomic analysis (.csv, .tsv, .biom) and figures can be downloaded in several formats.",
"A presentation about SHAMAN is available", a("here",target="_blank",href="shaman_presentation.pdf")," and a poster", a("here.",target="_blank",href="shaman_poster.pdf"),style = "font-family: 'times'; font-si16pt"), br(),
p("This website is free and open to all users and there is no login requirement. Hereafter is the global workflow of the SHAMAN application:",style = "font-family: 'times'; font-si16pt"),
div(img(src = "Workflow_sh.png",width = "100%",height = "100%",style="max-width: 800px;"),Align="center")
),
tabPanel("Authors", h3("The main contributors to SHAMAN:"),
p(a("Stevenn Volant", href="mailto:[email protected]"), "(Initiator, coding, testing, documentation, evaluation)"),
p(a("Amine Ghozlane",href="mailto:[email protected]"), "(Coding, testing, documentation, evaluation, packaging)"),
p("Perrine Woringer", "(Coding, testing, documentation, feature suggestions)"),
p("Zakary Azmani", "(Coding, testing, documentation, feature suggestions)"),
p("Pierre Lechat", "(Coding, testing, feature suggestions)"),
h3("Acknowledgements"),
p("Thanks to the following people for patches and other suggestions for improvements:"),
p("Valentin Marcon,", "Carine Rey, ", "Hugo Varet,", "Emeline Perthame,", "Julien Tap, ","Anna Zhukova.")
),
tabPanel("Citing SHAMAN",
p("If you use SHAMAN for your project, please cite the following publication:",style = "font-family: 'times'; font-si16pt"),
p(a("SHAMAN: a user-friendly website for metataxonomic analysis from raw reads to statistical analysis", href="https://pubmed.ncbi.nlm.nih.gov/32778056/"), "Volant S, Lechat P, Woringer P, Azmani Z, Motreff L, Campagne P, Malabat C, Kennedy S, Ghozlane A; BMC Bioinformatics 2020 Aug 10;21(1):345.",style = "font-family: 'times'; font-si16pt"),
p("Publication using SHAMAN:",style = "font-family: 'times'; font-si18pt; font-style: strong"),
p(a("Prediction of the intestinal resistome by a three-dimensional structure-based method.", href="https://www.ncbi.nlm.nih.gov/pubmed/30478291"),"Ruppé E, Ghozlane A, Tap J, et al.;Nature microbiology 2018",style = "font-family: 'times'; font-si16pt"),
p(a("Combined bacterial and fungal intestinal microbiota analyses: Impact of storage conditions and DNA extraction protocols", href="https://www.ncbi.nlm.nih.gov/pubmed/30074988"), "Angebault C, Ghozlane A, Volant S, Botterel F, d’Enfert C, Bougnoux ME, PloS one 2018",style = "font-family: 'times'; font-si16pt"),
p(a("Clinical Efficacy and Microbiome Changes Following Fecal Microbiota Transplantation in Children With Recurrent Clostridium Difficile Infection", href="https://www.ncbi.nlm.nih.gov/pubmed/26566371"), "Li X, Gao X, Hu H, Xiao Y, Li D, Yu G, Yu D, Zhang T, Wang Y, Frontiers in Microbiology",style = "font-family: 'times'; font-si16pt"),
p(a("Diverse laboratory colonies of Aedes aegypti harbor the same adult midgut bacterial microbiome", href="https://www.ncbi.nlm.nih.gov/pubmed/29587819"),"Dickson LB, Ghozlane A, Volant S, Bouchier C, Ma L, Vega-Rúa A, Dusfour I, Jiolle D, Paupy C, Mayanja MN, Kohl A, Lutwama JJ, Duong V, Lambrechts L",style = "font-family: 'times'; font-si16pt"),
p(a("Characteristics of Fecal Microbiota in Pediatric Crohn’s Disease and Their Dynamic Changes During Infliximab Therapy.", href="https://www.ncbi.nlm.nih.gov/pubmed/29194468"), "Wang Y, Gao X, Ghozlane A, Hu H, Li X, Xiao Y, Li D, Yu G, Zhang T; Journal of Crohn's & colitis 2017",style = "font-family: 'times'; font-si16pt"),
p(a("Carryover effects of larval exposure to different environmental bacteria drive adult trait variation in a mosquito vector.", href="https://www.ncbi.nlm.nih.gov/pubmed/28835919"), "Dickson LB, Jiolle D, Minard G, Moltini-Conclois I, Volant S, Ghozlane A, Bouchier C, Ayala D, Paupy C, Moro CV, Lambrechts L; Science Advances 2017",style = "font-family: 'times'; font-si16pt"),
p(a("A bacteriocin from epidemic Listeria strains alters the host intestinal microbiota to favor infection.", href="http://www.ncbi.nlm.nih.gov/pubmed/27140611"), "Quereda JJ, Dussurget O, Nahori MA, Ghozlane A, Volant S, Dillies MA, Regnault B, Kennedy S, Mondot S, Villoing B, Cossart P, Pizarro-Cerda J.; PNAS 2016",style = "font-family: 'times'; font-si16pt"),
p("Reporting bugs, ask for help",style = "font-family: 'times'; font-si18pt; font-style: strong"),
p("If you have any comments, questions or suggestions, or need help to use SHAMAN, please contact us at", a("[email protected]", href="mailto:[email protected]"),"and please provide us with enough information that we can recreate the problem. Useful things to include are:", style = "font-family: 'times'; font-si16pt;"),
tags$ul(
tags$li("Input data (or examples, a small test case sufficient to recreate the problem)"),
tags$li("Information about which system your are using: web version, docker or R installation")
)
)))),
column(width=3,
box(
title = "What's new in SHAMAN", width = NULL, status = "primary",
div(style = 'overflow-y: scroll; height: 550px',
addNews("October 29th 2024", "Barplot visualization", "Bug fix in the barplot. In some case the composition of the barplot were mixed."),
addNews("January 8th 2024", "Sunburst visualization", "You can now see the composition of the communities detected in the Network."),
addNews("December 6th 2023", "Database update", "Greengenes2 and unite are up-to-date. New host genomes (mostly mosquitoes) are available."),
addNews("November 23th 2023", "New data visualization and Global View features", "UMAP has been added. We have also updated the Barplot to show other abundances for visualization of the 12 most abundant. For diversity, we have added a visualization of richness with comparison tests."),
addNews("October 15th 2023", "Updates of PCA and PCoA", "These updates bring new data visualizations. We have added some useful features for cluster visualization."),
addNews("May 9th 2023", "Raw fastq submission is re-activated !", "Shaman submission process is up again. We updated in the mean time the unite database to version 9.0."),
addNews("April 12th 2022", "Improvement of the docker and web interface raw read submission", "Raw read submission is now improved for gzip fastq files. We now recommend to send gzip compressed fastq especially for docker instance."),
addNews("March 11th 2022","Server maintenance on march 22th", "Raw reads submission will be temporarly desactivated from March 22th. For now we keep improving our workflows, submissions from the docker machine should now be much more improved !"),
addNews("February 29th 2022","Workflow updates","We updated the workflow with Alientrimmer 2 to improve speed and resilience. Let us know if you meet some trouble!"),
addNews("February 29th 2022","Upgrades on 29 feb !","Raw reads submission will be temporarly desactivated 29 February to upgrade the bioinformatic workflow."),
addNews("January 13th 2022","Server maintenance is done","Raw reads submission is back."),
addNews("January 7th 2022","Server maintenance from 10-12 January 2021","Raw reads submission will be temporarly desactivated from January 10 until 12 due to a cluster maintenance."),
addNews("May 5th 2021","Server maintenance is done","Raw reads submission is back. We updated vsearch to 2.17, RDP classifier to 2.13, Bowtie to 2.3.5.1 and Biom to 2.1.10. Let us know if you meet any issue."),
addNews("April 28th 2021","Server maintenance from 3-6 Mai 2021","Raw reads submission will be temporarly desactivated from Mai 3 until 6 due to a cluster maintenance."),
addNews("Feburary 19th 2020","New feature","Shaman now support Epi2me data output. Let us know if you meet any issue."),
addNews("August 19th 2020","SHAMAN paper is out","We are really happy to announce that the paper describing in depth shaman and comparing this application to other available is out in BMC Bioinformatics. Moreover we keep improving the stability and functions of the application and we hope that we will be able to maintain this application for a long time."),
addNews("August 14th 2019","Major update","We performed a global improvement of SHAMAN. The application is now migrated to R 3.6.1. We implemented several visualization for differential analysis and network of abundance. We hope you will enjoy this new version."),
addNews("April 11th 2019","Debugging","We fixed few bugs in export system and scatterplot visualisation system."),
addNews("March 28th 2019","Packaging","SHAMAN is now available as packrat package. Take a look at download section."),
addNews("April 17th 2018","Bioinformatics","The bioinformatic treatment offers a larger access to parameters. We also worked a lot on the documentation."),
addNews("September 4th 2017","Bioinformatics","The bioinformatic treatment of fastq reads is now available in SHAMAN. For now, SHAMAN allows to compute OTU, build an OTU table and annotate them with the last version of the available database. This application is for 16S/18S/23S/28S/ITS sequencing."),
addNews("July 18th 2017","Normalization and visualisation","A new method for normalization called total counts was added. More options have been added to the abundance tree."),
addNews("May 30th 2017","Bug fixes","Some visualization bug with the abundance tree and phylogenetic tree are now fixed. The export of the relative abundance and normalised abundance are now given in the right level. This update prepares the field for the next major release of shaman for June."),
addNews("March 30th 2017","Krona, Phylogeny and bug fixes","Krona and phylogenetic tree plots are now available in visualisation. Several new distance are available in PCOA. The import float count matrices is now ok. We have finaly debugged the export of the relative abundance/normalized matrices."),
addNews("Dec 9th 2016","Phylogenetic tree and stress plot","You can now upload a phylogenetic tree to calculate the unifrac distance (only available at the OTU level).
The stress plot has been added to evaluate the goodness of fit of the NMDS."),
addNews("Nov 22th 2016","New visualization and bug fix","We have implemented a new visualization called tree abundance. Some bugs have been fixed (thanks Carine Rey from ENS)."),
addNews("Oct 12th 2016","Filtering step and bugs fix","You can now apply a filter on the features according to their abundance
and the number of samples. Bugs on confidence intervals for the alpha diversity have been fixed."),
addNews("Sep 21th 2016","SHAMAN on docker","The install of SHAMAN is now available with docker.
The R install is also updated and passed in release candidate state."),
addNews("Sep 14th 2016","Download and install SHAMAN","You can install SHAMAN (beta)."),
addNews("Sep 9th 2016","PCA/PCOA","You can select the axes for the PCOA and PCA plots."),
addNews("Aug 1st 2016","Biom format","SHAMAN can now support all the Biom format versions."),
addNews("Jun 24th 2016","Comparisons plots","The venn diagram and the heatmap of foldchange
have been added to compare the results of 2 or more contrasts."),
addNews("Jun 17th 2016","Diversity plots","Enhancement of the visualisation of the diverties.
The shanon and inv. shanon have been added.")
)
)
)
)
),
### TUTORIAL ####
tabItem(tabName = "Tutorial",
div(style="width:100% ; max-width: 1200px",
tabBox(title="How to use SHAMAN", id="tabset1", width =NULL,
tabPanel("Introduction",
p("First check out our user guide:"),
tags$ul(
tags$li(a("User's guide",target="_blank", href="Userguide.pdf")),
tags$li(a("Writing a target file for the experimental design",target="_blank", href="experimental_design_guide.pdf"))
),
p(" You can test SHAMAN with the dataset from", a("[Tap et al. 2015]",href="http://www.ncbi.nlm.nih.gov/pubmed/26235304"),
", which is available", a("here",target="_blank",href="Alimintest.zip"),"."),
p("The zip archive contains 4 different files :", br(),
"- the otu count matrix : Alimintest_otu_table.csv,", br(),
"- the otu annotation table : Alimintest_otu_annotation.csv,", br(),
"- the experimental design : Alimintest_target.csv,", br(),
"- the contrast table : Alimintest_contrasts.csv."),
p("Two groups of person follow two strict diet periods that involve the intake of 40g following 10g of fiber per day, or 10g of fiber after a 40g fiber intake period:"),
img(src = "tutorial/FigS1.png",width = "100%",style="max-width: 900px"),
p("The 16S rRNA (V3 - V4 regions) from fece samples was sequenced at time stamp : 2, 3, 4 and 5.", br(),
"The analysis will consider the different impact of the different fiber intake and the comparison to patient metabolic data.")),
tabPanel("1-Load 16S data",
p("The first step consists to load the count table and the annotation table as follow :"),
p("- Select 'Upload your data'", br(),
"- Load the count table :",br(), img(src = "tutorial/tutorial_upload1.png",width = "100%",style="max-width: 900px"),hr(),
"- Load the annotation table :", br(), img(src = "tutorial/tutorial_upload2.png",width = "100%",style="max-width: 900px"),hr(),
"- When successfully loaded, the tables are accessible as bellow :",br(),
img(src = "tutorial/tutorial_upload3.png",width = "100%",style="max-width: 600px"),img(src = "tutorial/tutorial_upload4.png",width = "100%",style="max-width: 600px"))),
tabPanel("2-Differential analysis",
p("The second step consists to load the experimental design and the contrast table as follow :"),
p("- Select 'Run differential analysis'",br(),
"- Load the target file :",br(),img(src = "tutorial/tutorial_target.png",width = "100%",style="max-width: 800px"),hr(),
"- Identify the taxonomy level where the analysis will be performed :",br(),img(src = "tutorial/tutorial_target1.png",width = "100%",style="max-width: 800px"),hr(),
"- Identify the interactions :",br(),img(src = "tutorial/tutorial_target2.png",width = "100%",style="max-width: 800px"),hr(),
"- Run the analysis :",br(),img(src = "tutorial/tutorial_target3.png",width = "100%",style="max-width: 800px"),hr(),
"- When successfully loaded, the tables are accessible as bellow :",br(),img(src = "tutorial/tutorial_target4.png",width = "100%",style="max-width: 800px")),hr(),
p("- Finally, load the contrast file :",br(),img(src = "tutorial/tutorial_contraste.png",width = "100%",style="max-width: 800px"),hr(),
"- Contrasts can be visualized as follow :",br(),img(src = "tutorial/tutorial_contraste1.png",width = "100%",style="max-width: 400px"))),
tabPanel("3-Diagnostic plots",
p("'Diagnostic plots' section provides several visualizations to control the analysis",br(),
"- Total mapped read count",br(),img(src="tutorial/tutorial_total_barplot.png",width = "100%",style="max-width: 900px"),hr(),
"- Nul barplot count",br(),img(src="tutorial/tutorial_nul_barplot.png",width = "100%",style="max-width: 900px"),hr(),
"- Maj taxonomy count",br(),img(src="tutorial/tutorial_maj_taxonomy.png",width = "100%",style="max-width: 900px"),hr(),
"- Density of counts",br(),img(src="tutorial/tutorial_density.png",width = "100%",style="max-width: 900px"),hr(),
"- Size factors vs total number of reads",br(),img(src="tutorial/tutorial_size_factor.png",width = "100%",style="max-width: 900px"),hr(),
"- PCA",br(),img(src="tutorial/tutorial_pca.png",width = "100%",style="max-width: 900px"),hr(),
"- PCOA",br(),img(src="tutorial/tutorial_pcoa.png",width = "100%",style="max-width: 900px"),hr(),
"- Clustering",br(),img(src="tutorial/tutorial_clustering.png",width = "100%",style="max-width: 900px"))),
tabPanel("4-Tables",
p("'Tables' section provides the results of the differential analysis.
For one given contrast, we have:",br(),
"- The id of the given taxonomical level",br(),
"- The base mean is the mean normalized count for the given annotation of all samples.",br(),
"- The fold-change is a mesure describing how much the abundance varies from one condition to an other. For instance, if the abundance is 100 in condition 1 and 200 for condition 2, the fold-change equals 100/200=0.5.",br(),
"- The log2 fold-change is the log2 value of the fold-change.",br(),
"- The p-value adjusted (padj) is the pvalue obtained by the Wald test and adjusted by Benjamini & Hochberg procedure (BH) or Benjamini & Yekutieli procedure (see linear model options).",
img(src = "tutorial/tutorial_table.png",width = "100%",style="max-width: 900px"))),
tabPanel("5-Visualization",
p("'Diagnostic plots' section provides several visualization to control the analysis",br(),
"- Barplot",br(),img(src="tutorial/tutorial_barplot.png",width = "100%",style="max-width: 900px"),hr(),
"- Heatmap",br(),img(src="tutorial/tutorial_heatmap.png",width = "100%",style="max-width: 900px"),hr(),
"- Boxplot",br(),img(src="tutorial/tutorial_boxplot.png",width = "100%",style="max-width: 900px"),hr(),
"- Diversity",br(),img(src="tutorial/tutorial_diversity.png",width = "100%",style="max-width: 900px"),hr(),
"- Rarefaction",br(),img(src="tutorial/tutorial_rarefaction.png",width = "100%",style="max-width: 900px"))),
tabPanel("6-Other datasets available",
p("You can test SHAMAN with two other datasets : "),
p("- Bacteriocin impact on mice microbiota from ", a("[Quereda et al. 2016]",href="http://www.ncbi.nlm.nih.gov/pubmed/27140611"), ":", a("here",target="_blank",href="listeria.zip"), br(),br(),
"The project is divided into three group : WT, Delta : Bacteriocin KO, Delta-complemented: Bacteriocin KO + complementation.", br(),
"Three time points are considered :", br(),
"- T0 : merged counts from -48H and -24H", br(),
"- T2 : 6H after listeria infection", br(),
"- T3 : 24H after listeria infection", br(),
img(src="listeria.png",width = "100%",style="max-width: 500px"),br(),br(),
"Analysis with SHAMAN:", br(),
"Set variables: condition, time, mice", br(),
"Set interactions:",
"1. condition:mice", br(),
"2. condition:time", br(),hr(),
"- MOCK communities from ", a("[The NIH HMP Working Group, 2009]",href="http://www.ncbi.nlm.nih.gov/pubmed/19819907"), ":", a("here",target="_blank",href="mock.zip"),br(),
"Mock communities are composed of 21 species mixed in even or staggered proportions :", br(),br(),
img(src="mock.png",width = "100%",style="max-width: 600px"),br(),br(),
"Analysis with SHAMAN: ",br(),
"Set variables : Community", br(),
"no interaction"))
))
),
### DOWNLOAD ####
tabItem(tabName = "Download",
fluidRow(
column(width=9,
div(style="width:100% ; max-width: 1200px",
tabBox(title="Download / Install SHAMAN", id="tabset1", width=NULL,
tabPanel("Docker install",
p("Docker install is the easiest way to use SHAMAN locally."),
p("- On ubuntu (Linux), install docker",a("(link here)",href="https://docs.docker.com/engine/installation/linux/ubuntulinux/"), ", download/run shaman:"),
mainPanel(div(style = 'max-width: 900px',"docker pull aghozlane/shaman && docker run --rm -p 80:80 -p 5438:5438 aghozlane/shaman"),width=8,class="mainwell"),
p("Then connect to http://localhost/ or http://0.0.0.0/ with your favorite web navigator."),
p("Failed: port is already allocated ?"),
mainPanel(div(style = 'max-width: 900px',"docker run --rm -p 3838:80 -p 5438:5438 aghozlane/shaman"),width=6,class="mainwell"),
p("Connect to http://localhost:3838/ http://0.0.0.0:3838/."),
p("- Install docker on Windows and Mac:"),
p("Download and install docker from",a("https://www.docker.com/", href="https://www.docker.com/")),
p("- Search for aghozlane/SHAMAN and run:", br(), img(src = "install/docker_shaman1.png",width = "100%",style="max-width: 900px"),hr()),
p("- In advanced settings, configure host port, 5438 with 5438/tcp and 80 with 80/tcp and run:", br(), img(src = "install/docker_shaman2.png",width = "100%",style="max-width: 900px"),hr()),
p("- Connect to http://localhost/ or http://0.0.0.0/ with your favorite web navigator.")
),
tabPanel("R install with Packrat (linux only)",
p("SHAMAN is available for R=3.6.1. Packrat framework allows an easy installation of all the dependencies. Of note, raw data submission is not possible with this version.",style = "font-family: 'times'; font-si16pt"),
mainPanel(div(style = 'max-width: 900px; word-wrap: break-word;',
"# Download packrat package",br(),"wget https://zenodo.org/record/7418309/files/shaman_package_202204.tar.gz", br(),
"mkdir packrat/"), width=9,class="mainwell"),
p("Now you can run R:"),
mainPanel(div(style = 'max-width: 900px; word-wrap: break-word;',
"install.packages(\"devtools\")",br(),
"devtools::install_github(\"rstudio/packrat\")",br(),
"packrat::unbundle(\"shaman_package_202204.tar.gz\", \"packrat/\")", br(),
"packrat::init(\"packrat/shaman\")",br(),
"system(\"Rscript -e 'shiny::runGitHub(\\\"pierreLec/KronaRShy\\\",port=5438)'\",wait=FALSE)",
br(),"shiny::runGitHub('aghozlane/shaman')"),width=9,class="mainwell")),
tabPanel("R install (deprecated)",
p("SHAMAN is available for R=3.6.1. Gfortran is required on mac (https://cran.r-project.org/bin/macosx/tools/) and Rtools on windows (https://cran.r-project.org/bin/windows/Rtools/index.html).
Of note, raw data submission is not possible with this version.
The installation, download and execution can all be performed with a small R script:",style = "font-family: 'times'; font-si16pt"),
mainPanel(div(style = 'max-width: 900px; word-wrap: break-word;',"# Load shiny packages",br(),
"if(!require('shiny')){",br()," install.packages('shiny')",br(),"}",br(),
"system(\"Rscript -e 'shiny::runGitHub(\\\"pierreLec/KronaRShy\\\",port=5438)'\",wait=FALSE)",
br(),"# Install dependencies,",br(),"# download last version from github,",br(),"# and run SHAMAN in one command:",br(),
"shiny::runGitHub('aghozlane/shaman')"),width=9,class="mainwell"),
p("This script can also be dowloaded", a("here", target="_blank", href="shaman.R"), "and executed as following :"),
mainPanel(div(style = 'max-width: 900px; word-wrap: break-word;',"chmod +x ./shaman.R && Rscript ./shaman.R"),width=6,class="mainwell"),br(),
p("Of note, contribution to SHAMAN code are always welcome and can be performed with the", a("github deposit.",href="https://github.com/aghozlane/shaman"))),
tabPanel("Conda install (deprecated)",
p("Conda installation of SHAMAN is available for linux and mac. It can be performed as follow: ",style = "font-family: 'times'; font-si16pt"),
mainPanel(div(style = 'max-width: 900px; word-wrap: break-word;',
"# Download and install SHAMAN", br(),
"conda install -c aghozlane shaman", br(),
"# Now run shaman", br(), "shaman_conda.R"), width=6,class="mainwell"))
)
)
)
)
),
### RAW DATA ####
#id="rawdatatab",
tabItem(tabName = "RawData",
tags$style(type='text/css', ".well { max-width: 20em; }"),
# tags$head(tags$style(HTML(InfoBoxCSS))),
tags$head(tags$script("$(function() { $(\"[data-toggle='popover']\").popover(); })")),
fluidRow(
# column(width=3,valueBoxOutput("valueErrorPercent",width=NULL)),
# column(width=3,infoBoxOutput("InfoErrorCounts",width=NULL)),
# column(width=3,infoBoxOutput("InfoErrorTaxo",width=NULL)),
div(id="masque-infobox",
column(width=3,
withPopup(infoBoxOutput("infoBoxPass",width=NULL),
title="Once you have entered a valid email address, click on this button:",
img_src="icons/GetKey_button.png")
),
column(width=3,
infoBoxOutput("infoBoxFastQ",width=NULL)
),
column(width=3,
infoBoxOutput("infoBoxFastQ_match",width=NULL)
),
column(width=3,
valueBoxOutput("progressBoxMasque",width=NULL)
)
)),
# fluidRow(
# HTML('<center><h1>MASQUE : Metagenomic Analysis with a Quantitative pipeline</h1></center>'),
# column(width=8,
# div(style="background-color: white; padding-left:20px;",
# HTML('
# <h2>Introduction</h2>
#
# <p>The aim of this part is to provide an easy cluster interface to perform <b>targeted metagenomic analysis</b>. This analysis will be done using the MASQUE pipeline which allows :</p>
#
# <ul>
# <li>to analyse 16S/18S/23S/28S/ITS data. It builds a count matrix, an annotation table and a phylogeny of the OTU.</li>
# <li>to perform to use a set of parameters already tested on serveral projects for the numerous software used to perform the clustering and the annotation.</li>
# <li>to perform an "uptodate" analysis considering the scientific litterature.</li>
# </ul>
#
# <hr></hr>
# <h2>Process</h2>
#
# <p>We follow the recommandation described by Robert C. Edgar in <a href="http://www.nature.com/nmeth/journal/v10/n10/full/nmeth.2604.html" target="_blank" >Uparse</a> supplementary paper.<br>
# The clustering process in MASQUE is performed as the following :<br>
# 1. Read quality control<br>
# 2. Dereplication<br>
# 3. Chimera filtering<br>
# 4. Clustering<br>
# 5. Realignment/mapping<br>
# 6. Taxonomical annotation of the OTU<br>
# 7. Quality check of every step </p>
#
# <p>You can find more information in the presentation <a href="/aghozlane/masque/blob/master/tp/Targeted_metagenomics.pdf">here</a>. We try to describe the idea behind each step and a complete TP to do it on your own.</p>'
# )
# #
# #
# # <\ui> to analyse 16S/18S/23S/28S/ITS data. It builds a count matrix, an annotation table and a phylogeny of the OTU.
# # to perform to use a set of parameters already tested on serveral projects for the numerous software used to perform the clustering and the annotation.
# # to perform an uptodate analysis considering the scientific litterature."
# )),
# column(width=4)
# # column(width=4,
# # inlineCSS(gaugeCSS),
# # gaugeOutput("gaugeMasque", width = "100%", height = "100%")
# # )
# ),
# hr(),
# HTML('<center><h2 style="color:#053383;"><b>Start your analysis</b></h2></center>'),
# hr(),
fluidRow(
# column(width=3,
# inlineCSS(gaugeCSS),
# gaugeOutput("gaugeMasque", width = "100%", height = "100%")
#
# ),
column(width=9,
div(id="masque-form",
box(title="About",width = NULL, status = "primary",
column(width=6, radioButtons("DataTypeMasque",label = "Type of data",choices = c("16S" = "16S", "18S" = "18S","23S/28S" = "23S_28S","ITS" = "ITS"),inline = TRUE)),
column(width=6, radioButtons("PairedOrNot",label = "Paired-end sequencing ?",choices = c('Yes'="y","No"="n"),selected = "n",inline = TRUE)),
column(width=3, textInput("to", "Email address *", value="yyy@xxx"),
bsTooltip("to", "Enter a valid email address to get your results","bottom",trigger = "hover", options = list(container = "body"))
),
column(width=3, actionButton("checkMail",label = " Get key",icon=icon('key')),
bsTooltip("checkMail", "Click here to get your key by mail","bottom", options = list(container = "body")),
tags$style(type='text/css', "#checkMail { width:100%; margin-top: 25px;}")
),
column(width=6, selectizeInput("HostName",label = "Select the host",
choices = c("None"="", "a.coluzzi (mosquito)" = "acoluzzi", "a.funestus (mosquito)" = "afunestus", "a.aegypti (mosquito)" = "aaegypti", "a.albopictus (mosquito)" = "aalbopictus",
"a.stephensi (mosquito)" = "astephensi", "b.taurus (cow)" = "btaurus", "c.familiaris (dog)" = "cfamiliaris",
"chiroptera (bat)" = "chiroptera", "c.pipiens (mosquito)" = "cpipiens", "c.sabaeus (Apes)" = "csabaeus" , "d.melanogaster (fly)"="dmelanogaster",
"d.rerio (fish)" = "drerio", "e.caballus (Horse)" = "ecaballus", "f.catus (cat)" = "fcatus", "hg18 (human)"="hg18", "hg19 (human)"="hg19",
"hg38 (human)" = "hg38", "m.lucifugus (bat)" = "mlucifugus", "mm8 (mouse)"= "mm8", "mm9 (mouse)" = "mm9",
"mm10 (mouse)"="mm10", "p.vampyrus (bat)" = "pvampyrus", "s.scrofa (boar)" = "sscrofa"))),
column(width=6,checkboxInput("primer", "Specify the primer"),
bsTooltip("primer", "If no, default values are chosen","bottom", options = list(container = "body"))
),
column(width=6,checkboxInput("options", "More workflow options"),
bsTooltip("options", "If no, default values are chosen","bottom", options = list(container = "body"))
),
conditionalPanel(condition="input.primer && input.PairedOrNot=='y'",
column(width=12,
textInput("R1primer",label = "Forward primer",value = "TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG"),
textInput("R2primer",label = "Reverse primer",value = "GTCTCGTGGGCTCGGAGATGTGTATAAGAGACAGGACTACHVGGGTATCTAATCC")
)
),
conditionalPanel(condition="input.primer && input.PairedOrNot=='n'",
column(width=12,
textInput("primerSingle",label = "Primer",value = "TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGCCTACGGGNGGCWGCAG")
)
),
conditionalPanel(condition="input.options",
column(width=4, h3("Read processing"),
sliderInput("phredthres", "Phred quality score cutoff to trim off low-quality read ends",
min = 0, max = 40, value = 20),
sliderInput("mincorrect", "Minimum allowed percentage of correctly called nucleotides per reads",
min = 50, max = 100, value = 80),
numericInput("minreadlength", "Minimum read length", 50,step=1,min=50),
conditionalPanel(condition="input.options && input.PairedOrNot=='y'", numericInput("minoverlap", "Minimum overlap size", 10,step=1,min=1))
),
column(width=4, h3("OTU processing"),
selectInput("dreptype", "Dereplication ", choices = list("Prefix" = "--derep_prefix", "Full length" = "--derep_fulllength"), selected = "--derep_prefix"),
numericInput("maxampliconlength", "Maximum OTU length (0 is no limit)", 0,step=1,min=0),
numericInput("minampliconlength", "Minimum OTU length", 50, step=1, min=35),
numericInput("minabundance", "Minimum abundance at dereplication", 4, step=1, min=2),
selectInput("clusteringstrand", "Clustering strand ", choices = list("Both" = "both", "Plus" = "plus"), selected = "both"),
sliderInput("clusteringthreshold", "Clustering threshold", min = 0, max = 1, value = 0.97)),
column(width=4, h3("OTU annotation"),
selectInput("annotationstrand", "Annotation strand ", choices = list("Both" = "both", "Plus" = "plus"), selected = "both"),
sliderInput("annotationKingdomthreshold", "Minimum identity for Kingdom annotation", min = 0, max = 1, value = 0.75, step = 0.005),
sliderInput("annotationPhylumthreshold", "Identity thresholds for Phylum annotation", min = 0, max = 1, value = c(0.75, 0.785), step = 0.005),
sliderInput("annotationClassthreshold", "Identity thresholds for Class annotation", min = 0, max = 1, value = c(0.785, 0.82), step = 0.005),
sliderInput("annotationOrderthreshold", "Identity thresholds for Order annotation", min = 0, max = 1, value = c(0.82, 0.865), step = 0.005),
sliderInput("annotationFamilythreshold", "Identity thresholds for Family annotation", min = 0, max = 1, value = c(0.865, 0.945), step = 0.005),
sliderInput("annotationGenusthreshold", "Identity thresholds for Genus annotation", min = 0, max = 1, value = c(0.945, 0.98), step = 0.005),
sliderInput("annotationSpeciethreshold", "Minimum identity for Specie annotation", min = 0, max = 1, value = 0.98, step = 0.005)
)
)
),
box(title="Directory containing the FastQ files ",width = NULL, status = "primary",
# column(width=12,verbatimTextOutput("dirSel")),
# br(),
column(width=12,
fileInput("dir",label = 'Select your fastq files',accept = c(".fastq",".gz",".fq"),multiple = TRUE),
# shinyDirButton("dir", "Select a directory", "Upload",buttonType = "primary")
# tags$input(id = "dir2", webkitdirectory = TRUE, type = "file", onchange="pressed()"),
# HTML(" "),
# actionButton("LoadFiles",'Load',icon=icon("play"))
uiOutput("FastQList_out")
)
),
box(id="box-match",title=" Match the paired files (only for paired-end sequencing)",width = NULL, status = "primary",
column(width=6, textInput("R1files",label = "Suffix R1 (Forward, do not include file extension)",value = "_R1"),
selectInput("R1filesList",label = "","",multiple =TRUE,selectize=FALSE)),
column(width=6,
textInput("R2files",label = "Suffix R2 (Reverse, do not include file extension)",value = "_R2"),
selectInput("R2filesList",label = "","",multiple =TRUE,selectize=FALSE)
),
column(width=12,
actionButton("MatchFiles_button",'Match',icon=icon("exchange"),class="btn-primary",style="color: #fff;"),
HTML(" "),
actionButton("RemoveFastQbut_R1R2",'Remove file(s)',icon=icon("remove"))
)
),
div(style = "text-align:center;",
actionButton("submit", strong("Check and submit"), icon("chevron-circle-right"),class="btn-primary",style = "color: #fff"),
#receiveSweetAlert(messageId = "ErrorMasque"),
tags$style(type='text/css', "#submit { width:50%; margin-top: 5px;}")#,
#receiveSweetAlert(messageId = "SuccessMasque")
)
),
div(id="project_over",style="text-align:center; display: none;",
HTML("<center><h1><strong>Computations are over</strong></h1></center>"),
actionButton("Check_project_over", h2("Check results"),icon=icon("check-circle fa-2x"),class="btn-primary",style = "color: #fff"),
tags$style(type='text/css', "#Check_project_over {margin-top: 15px;width:50%;}")
),
div(id="current-project",style="display: none;",
uiOutput("masque_results")
),
div(id="project-over-wait",style="display: none;",
HTML('<center><h1><strong> Please wait during the creation of the files...</strong></h1> <br/> <em><h4> This can take about 30 seconds</h4> </em> </center>'),
tags$img(src = "gears.gif",id ="loading-spinner")
)),
div(id="reload-project",style="display: none;",
column(width=12,
actionButton("comeback",strong("Close and come back"),icon=icon("backward")),
#shinyjs::useShinyjs(),
#shinyjs::extendShinyjs(text = "shinyjs.refresh = function() { history.go(0); }"),
actionButton("refresh", "Refresh progress"),
uiOutput("masque_status_key")
)
),
# div(id="MasqueToShaman",style="display: none;",
# column(width=3,
# #uiOutput("loaddb"),
# box(id="box-zip",title="Download .zip file",width = NULL, status = "success",
# downloadButton('Download_masque_zip', 'Download the results'),
# tags$style(type='text/css', "#Download_masque_zip { width:100%;}")
# )
# )
# ),
div(id="pass",style = "word-wrap: break-word;",
column(width=3,
box(id="boxpass",title = strong("Enter the key"), width = NULL, background = "light-blue",
inlineCSS(list(.pwdGREEN = "background-color: #DDF0B3",.pwdRED = "background-color: #F0B2AD")),
uiOutput("pass_Arg"),
textInput("password","",value = NULL),
div(style = "text-align:right;",
actionButton("Check_project", "Check project",icon=icon("check-circle")),
tags$style(type='text/css', "#Check_project {margin-top: 15px;}")
),
bsTooltip("password", 'Fill in the email field and click the "Get key" button',"bottom",trigger = "hover", options = list(container = "body")),
tags$style(type='text/css', "#password { width:100%; margin-top: 10px;}")
),
tags$style(type='text/css', "#boxpass {margin-bottom: 0px;}"),
# valueBoxOutput("progressBoxMasque",width = 12),
# infoBox(title = "tete",icon= uiOutput("spinner_icon"),width=12),
uiOutput("summary_box_masque")
)),
column(width=3,
# inlineCSS(gaugeCSS),
# gaugeOutput("gaugeMasque", width = "100%", height = "100%"),
uiOutput("InfoMasque"),
uiOutput("InfoMasqueHowTo")
# uiOutput("MasqueToShaman_button")
)
)
),
### UPLOAD YOUR DATA ####
tabItem(tabName = "Upload",
tags$style(type='text/css', ".well { max-width: 20em; }"),
fluidRow(
column(width=3,valueBoxOutput("valueErrorPercent",width=NULL)),
column(width=3,infoBoxOutput("InfoErrorCounts",width=NULL)),
column(width=3,infoBoxOutput("InfoErrorTaxo",width=NULL)),
column(width=3,infoBoxOutput("InfoTreePhylo_box",width=NULL))
),
br(),
fluidRow(
box(title="Select your file format",width = 3,status = "success", solidHeader = TRUE,collapsible = FALSE,
# selectInput("FileFormat","",c("Count table & taxonomy (*.csv or *.tsv)"="fileCounts","BIOM file"="fileBiom","Saved project"="fileRData"),selected="fileCounts"),
selectInput("FileFormat","",c("Count table & taxonomy (*.csv or *.tsv)"="fileCounts","BIOM file"="fileBiom","Epi2me file"="fileEpi2me","Project number"="projnum"),selected="fileCounts"),
conditionalPanel(condition="input.FileFormat=='fileCounts'",
checkboxInput("NoTaxoFile","No taxonomy table",value=FALSE),
selectInput("DemoDataset",h6(strong('Or select a dataset')),
c("..."="...",
"ZymoBIOMICS mock 16S: Volant et al. 2020"=c("10b0238abee0d|silva|Volant et al. 2020 in review"),
"Afribiota: Vonaesch et al. 2018"=c("1be225fc935c7|silva|Vonaesch et al. 2018"),
"DNA extraction protocols 16S: Angebault et al. 2018"=c("eec74b27d162|silva|Angebault et al. 2018"),
"DNA extraction protocols ITS1: Angebault et al. 2018"=c("3580714197f5|unite|Angebault et al. 2018"),
"Listeria: Quereda et al. 2016"=c("69207712064|silva|Quereda et al. 2016")),
selected="...")#,
#receiveSweetAlert(messageId = "DemoDataset")
),
conditionalPanel(condition="input.FileFormat=='projnum'",
inlineCSS(list(.pwdGREEN = "background-color: #DDF0B3",.pwdRED = "background-color: #F0B2AD")),
textInput("password_home","Enter the key",value = NULL),
div(style = "text-align:right;",
actionButton("Check_project_home", "Check project number",icon=icon("check-circle")),
tags$style(type='text/css', "#Check_project_home {margin-top: 15px;}")
)
)
),
conditionalPanel(condition="input.FileFormat=='fileCounts'",
box(title="Load the count table",width = 3,height = "260px", status = "primary", solidHeader = TRUE,collapsible = FALSE,
fluidRow(
column(width=6,radioButtons("TypeTable",h6(strong("Type:")),c("OTU/Gene table"="OTU","MGS table"="MGS"))),
column(width=6,selectInput("sepcount", h6(strong("Separator:")),c("Tab" = "\t", "Comma" = ",","Semi-colon" = ";")))
),
fileInput('fileCounts', h6(strong('Select your file')),width="100%",accept = c(".csv",".tsv",'.xls','.xlsx','.txt')),
tags$script('$( "#fileCounts" ).on( "click", function() { this.value = null; });')
),
conditionalPanel(condition="!input.NoTaxoFile",
box(title="Load the taxonomy file",width = 3,height = "260px", status = "primary", solidHeader = TRUE,collapsible = FALSE,
fluidRow(
column(width=6,radioButtons("TypeTaxo",h6(strong("Format:")),c("Table"="Table","RDP"="RDP"))),
column(width=6,
conditionalPanel(condition="input.TypeTaxo=='RDP'",numericInput("RDP_th",h6(strong("Threshold:")),0.5,step=0.01,min=0.01,max=1))
),
column(width=6,
conditionalPanel(condition="input.TypeTaxo=='Table'",selectInput("septaxo", h6(strong("Separator:")),
c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";")))
)
),
fileInput('fileTaxo', h6(strong('Select your file')),width="100%",accept = c(".csv",".tsv",'.xls','.xlsx','.txt')),
tags$script('$( "#fileTaxo" ).on( "click", function() { this.value = null; });')
)
)
),
#&&is.null(input.password_home)
conditionalPanel(condition="input.FileFormat=='fileBiom'&&input.DemoDataset=='...'",
box(title="Load the BIOM file",width = 3, status = "primary", solidHeader = TRUE,collapsible = FALSE,
fileInput('fileBiom', h5(strong('Select your file')),width="100%",accept = c(".biom")),
tags$script('$( "#fileBiom" ).on( "click", function() { this.value = null; });')
)
),
conditionalPanel(condition="input.FileFormat=='fileEpi2me'&&input.DemoDataset=='...'",
box(title="Load the Epi2me file",width = 3, status = "primary", solidHeader = TRUE,collapsible = FALSE,
column(width=6,
selectInput("sepepi2me", h6(strong("Separator:")), c("Comma" = ",", "Semicolon" = ";", "Tab" = "\t"))),
column(width=6,
numericInput("Epi2me_th",h6(strong("Minimum accuracy level:")),70,step=0.5,min=1,max=100)),
column(width=12,
fileInput('fileEpi2me', h6(strong('Select your file')),width="100%",accept = c(".csv", ".tsv"))),
tags$script('$( "#fileEpi2me" ).on( "click", function() { this.value = null; });')
)
),
conditionalPanel(condition="input.FileFormat=='projnum'||input.DemoDataset!='...'",
uiOutput("Project_box_home")
),
#&&is.null(input.password_home)
conditionalPanel(condition="input.FileFormat!='projnum'&&input.DemoDataset=='...'||input.FileFormat=='fileCounts'",
box(title="Load phylogenetic tree (optional)",width = 3, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed = TRUE,
fileInput('fileTree', h6(strong('Select your file (tree)')),width="100%"),
tags$script('$( "#fileTree" ).on( "click", function() { this.value = null; });')
)
),
fluidRow(column(width=3,
uiOutput("InfoCountsFile"),
uiOutput("InfoTaxoFile"),
uiOutput("InfoEpi2me"),
uiOutput("InfoBIOM")
)
)
),
column(id="tabboxdata_col",width=12,uiOutput("TabBoxData")),
tags$script("$(document).on('click', '#DataTaxo button', function () {
Shiny.onInputChange('lastClickId',this.id);
Shiny.onInputChange('lastClick', Math.random())
});")
# receiveSweetAlert(messageId = "ErrorTaxo"),
# receiveSweetAlert(messageId = "ErrorBiom1"),
# receiveSweetAlert(messageId = "ErrorBiom2"),
# receiveSweetAlert(messageId = "ErrorSizeFactor"),
# receiveSweetAlert(messageId = "ErrorCounts"),
# receiveSweetAlert(messageId = "ErrorRDP")
),
#### STATISTICAL ANALYSIS ####
#### ___RUN DIFFERENTIAL ANALYSIS ####
tabItem(tabName = "RunDiff",
fluidRow(
column(width=3,valueBoxOutput("RowTarget",width=NULL)),
column(width=3,infoBoxOutput("InfoTaxo",width=NULL)),
column(width=3,infoBoxOutput("InfoDESeq",width=NULL)),
column(width=3,infoBoxOutput("InfoContrast",width=NULL))
),
fluidRow(
column(width=5,
box(title="Experimental design",width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed = FALSE,
fluidRow(
column(width=5,fileInput('fileTarget', h6(strong('Select your target file')),width="100%"),
tags$script('$( "#fileTarget" ).on( "click", function() { this.value = null; });')
),
column(width=3,selectInput("septarget", h6(strong("Separator:")), c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";"))),
column(width=4,uiOutput("SelectTaxo"))
),
fluidRow(
column(width=6,uiOutput("SelectInterestVar")),
column(width=6,uiOutput("SelectInteraction2"))
),
fluidRow(
column(width=6,uiOutput('SaveExperiment')),
column(width=6,uiOutput("VisButton"),uiOutput("RunButton"))
)
),
fluidRow(uiOutput("InfoModel"),uiOutput("InfoModelHowTo")),
uiOutput("BoxTarget"),
uiOutput("BoxCountsMerge")
),
column(width=7,
box(title="Options",width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed = TRUE,
tabBox(title="", id="tabsetOption", width=NULL,
tabPanel("Statistical model",
fluidRow(
column(width=3,
radioButtons("TransType",h6(strong("Type of transformation")),choices = c("VST"="VST","rlog"="rlog"))
),
column(width=3,
radioButtons("IndFiltering",h6(strong("Independent filtering")),choices = c("True"=TRUE,"False"=FALSE))
),
column(width=3,
radioButtons("AdjMeth",h6(strong("p-value adjustement")),choices = c("BH"="BH","BY"="BY"))
),
column(width=3,
textInput("AlphaVal",h6(strong("Level of significance")),value=0.05)
)
),
fluidRow(
column(width=3,
radioButtons("CooksCutOff",h6(strong("Cooks cut-off")),choices = c("Auto"='Auto',"No cut-off"=Inf,"Value"="val")),
conditionalPanel(condition="input.CooksCutOff=='val'",textInput("CutOffVal",h6("Cut-off:"),value=0))
),
column(width=3,
radioButtons("locfunc",h6(strong("Local function")),choices = c("Median"="median","Shorth"="shorth"))
),
column(width=3,
radioButtons("fitType",h6(strong("Relationship")),choices = c("Parametric"="parametric","Local"="local", "Mean"="mean"))
)
# column(width=3,uiOutput("RefSelect"))
)
),
tabPanel("Normalization",
fluidRow(
column(width=3,
selectizeInput("AccountForNA", h6(strong("Normalization method")),choices = c("DESeq2"="All", "Non-null normalization"="NonNull", "Weighted non-null normalization"="Weighted","Total counts"="Total counts"),selected = "Weighted")),
column(width=3,
uiOutput("SelectVarNorm")),
column(width=3,
fileInput('fileSizeFactors', h6(strong('Define your own size factors')),width="100%"),
tags$script('$( "#fileSizeFactors" ).on( "click", function() { this.value = null; });')
),
column(width=3, selectInput("sepsize", h6(strong("Separator:")), c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";"))),
column(width=3,br(),htmlOutput("InfoSizeFactor"))
)
),
tabPanel("Filtering",
fluidRow(
column(width=3,
checkboxInput("AddFilter","Add a filtering step",value = FALSE),
bsTooltip("AddFilter", "If your count matrix is very sparse, you can add a filter on your data","bottom",trigger = "hover", options = list(container = "body"))
)
),
fluidRow(
conditionalPanel(condition="input.AddFilter",
column(width=6,
plotOutput("Plot_ThSamp"),
column(width=10,uiOutput("ThSamp"),offset = 1)
),
column(width=6,
plotOutput("Plot_ThAb"),
column(width=10,uiOutput("ThAb"),offset = 1)
),
column(width=12,
scatterD3Output("Plot_Scatter_Filter")
)
)
)
)
)
),
fluidRow(
column(width=8,
uiOutput("contrastBox"),
uiOutput("contrastBoxAdvanced")
),
column(width=4,
uiOutput("contrastDefined"),
uiOutput("InfoContrast_box")
)
)
)
)
),
#### ___DIAGNOSTIC PLOTS ####
tabItem(tabName = "DiagPlotTab",
fluidRow(
column(width=9,
tags$head(tags$style(HTML(spincss))),
div(id = "plot-container",
tags$img(src = "gears.gif",id ="loading-spinner"),
plotOutput("PlotDiag",height="100%")
),
br(),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
box(title = "Size factors", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
DT::dataTableOutput("SizeFactTable"),
fluidRow(
column(width=3,downloadButton('ExportSizeFactor', 'Export table')),
column(width=3,selectInput("sepsizef", h6(strong("Separator:")), c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";")))
),
tags$style(type='text/css', "#ExportSizeFactor { margin-top: 37px;}")
)
),
fluidRow(
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotEigen",height="100%")
)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'",
box(title = "Eigen values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotpcoaEigen",height="100%")
)
),
conditionalPanel(condition=" (input.DiagPlot=='pcoaPlot' && input.labelPCOA == input.TaxoSelect) || (input.DiagPlot=='pcaPlot' && (input.radioPCA == 2 || input.radioPCA == 3))",
box(title = "Contribution", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotContrib",height="100%")
)
),
conditionalPanel(condition="input.DiagPlot=='nmdsPlot'",
box(title = "Stress plot", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
plotOutput("PlotnmdsStress",height="100%")
)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot' || (input.DiagPlot=='pcaPlot' && input.radioPCA == 1)",
uiOutput("ResPermaTestBox")
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot'",
br(),
box(title = "Distance values", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
DT::dataTableOutput("Distancetable"),
fluidRow(
column(width = 3, offset = 0, style = "margin-top: 55px", downloadButton('ExportDistancetable', 'Export table')),
column(width = 3, offset = 1, style = "margin-top: 30px", selectInput("sepdistance", "Separator:", c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";")))
),
tags$style(".leftAlign{float:left};")
)
),
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
br(),
box(title = "Matrix coordinates", width = 6, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
DT::dataTableOutput("MatrixCoordinatetable"),
fluidRow(
column(width = 3, offset = 0, style = "margin-top: 55px", downloadButton('ExportDistancetablePCA', 'Export table')),
column(width = 3, offset = 1, style = "margin-top: 30px", selectInput("sepdistancePCA", "Separator:", c("Tab" = "\t", "Comma" = ",", "Semicolon" = ";")))
),
tags$style(".leftAlign{float:left};")
)
)
)
),
column(width=3,
box(title = "Select your plot", width = NULL, status = "primary", solidHeader = TRUE,collapsible = FALSE,collapsed= FALSE,
selectInput("DiagPlot","",c("Total barplot"="barplotTot","Nul barplot"="barplotNul",
"Maj. taxonomy"="MajTax","Boxplots" = "boxplotNorm", "Density"="densityPlot", "Dispersion" = "DispPlot",
"Size factors VS total"="SfactorsVStot", "PCA"="pcaPlot", "PCoA"="pcoaPlot", "NMDS"="nmdsPlot","Clustering" = "clustPlot", "UMAP"= "umapPlot"))
),
box(title = "Options", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
conditionalPanel(condition="input.DiagPlot!='clustPlot' && input.DiagPlot!='pcaPlot' && input.DiagPlot!='SfactorsVStot' && input.DiagPlot!='DispPlot'",
radioButtons("CountsType","Counts:",c("Normalized"="Normalized","Raw"="Raw"),inline = TRUE)
),
conditionalPanel(condition="input.DiagPlot=='boxplotNorm'",
checkboxInput("RemoveNullValue","Remove 0",value = TRUE)
),
conditionalPanel(condition="input.DiagPlot!='Sfactors' && input.DiagPlot!='SfactorsVStot' ",uiOutput("VarIntDiag")),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='pcaPlot' || input.DiagPlot=='nmdsPlot' || input.DiagPlot == 'umapPlot'",
h5(strong("Select the modalities")),
uiOutput("ModMat"),
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='pcaPlot' || input.DiagPlot=='nmdsPlot'",
fluidRow(
column(width=5,uiOutput("PC1_sel")),
column(width=2,br(),br(),p("VS")),
column(width=5,uiOutput("PC2_sel"))
)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot' || input.DiagPlot=='SERE' || input.DiagPlot=='clustPlot'",
uiOutput("DistList")
),
conditionalPanel(condition="input.DistClust=='Unifrac' && (input.DiagPlot=='pcoaPlot' || input.DiagPlot=='nmdsPlot' || input.DiagPlot=='clustPlot')",
column(width=12,
selectInput("DistClustUnifrac","Which unifrac distance ?",c("Weighted UniFrac"="WU", "Unweighted UniFrac"="UWU", "Variance adjusted weighted UniFrac"="VAWU"))
)
),
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
column(width = 8, radioButtons("radioPCA", label = h5(strong("Visualizing principal component analysis")), choices = list("Samples" = 1, "Biplot" = 2, "Variables" = 3), selected = 1))
),
conditionalPanel(condition="input.DiagPlot=='pcaPlot' && input.radioPCA != 3",
column(width = 4, checkboxInput("ellipsePCA", label = strong("Show groups"), value = TRUE))
),
conditionalPanel(condition=" (input.DiagPlot=='pcoaPlot' && input.labelPCOA == input.TaxoSelect) || (input.DiagPlot=='pcaPlot' && (input.radioPCA == 2 || input.radioPCA == 3)) ",
fluidRow(column(12,sliderInput("varSlider", "Select the contribution threshold", min = 0, max = 1, value = 0.8, step = 0.05)),
column(12,checkboxInput("sumContrib", h5(strong("Display the sum of the contributions of each variable")))))
),
conditionalPanel(condition="input.DiagPlot=='umapPlot'",
selectInput("distanceUMAP", "Distance", c("Cosine" = "cosine", "Euclidean" = "euclidean", "Manhattan" = "manhattan", "Pearson" = "pearson", "Pearson2"= "pearson2"), selected = "euclidean"),
sliderInput("neighborsKNN", "Select the number of neighbors", min = 4, max = 15, value = 4, step = 1)
)
# conditionalPanel(condition="input.RadioPlotBi=='Nuage'",selectInput("ColorBiplot", "Couleur",choices=c("Bleue" = 'blue',"Rouge"='red',"Vert"='green', "Noir"='black'),width="50%")),
# sliderInput("TransAlphaBi", "Transparence",min=1, max=100, value=50, step=1),
# conditionalPanel(condition="input.RadioPlotBi!='Nuage'", radioButtons("SensGraphBi","Sens du graph",choices=c("Vertical"="Vert","Horizontal"="Hori"))),
# conditionalPanel(condition="input.RadioPlotBi=='box'", checkboxInput("CheckAddPointsBoxBi","Ajouter les données",value=FALSE))
),
box(
title = "Appearance", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= FALSE,
# conditionalPanel(condition="input.DiagPlot=='Sfactors'",
# h6(strong("Layout")),
# numericInput("NbcolSfactors", h6("Columns"),min=1,value = NA)
# ),
sliderInput("heightDiag", "Height",min=100,max=1500,value = 500,step =10),
checkboxInput("modifwidthDiag","Set width",FALSE),
conditionalPanel(condition="input.modifwidthDiag",
sliderInput("widthDiag", "Width",min=100,max=2500,value = 800,step =10)),
selectInput("colorsdiag", label=h6(strong("Gradient of colors")),choices = c("retro palette", "easter palette", "warm palette", "basic palette (1)", "basic palette (2)", "basic palette (3)", "basic palette (4)"),selected = "retro palette"),
#plotHelper(colours = c("red", "#123ABC")),
#fluidRow(
# ),
conditionalPanel(condition="input.DiagPlot=='clustPlot'",
h6(strong("Layout")),
selectInput("typeHculst", h6("Type"),c("Horizontal"="hori","Fan"="fan")),
checkboxInput("colorHC","Add color",value=TRUE)
),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot'",
checkboxInput("addLabelSFact","Add label",FALSE)
),
conditionalPanel(condition="input.DiagPlot=='pcaPlot' || input.DiagPlot=='pcoaPlot' || input.DiagPlot== 'umapPlot'",
uiOutput("centeringButton")
),
conditionalPanel(condition="input.DiagPlot== 'umapPlot'",
checkboxInput("labelSamplesUMAP", label = strong("Display label"))
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot'", selectInput("labelPCOA","Label type",c("Group", "Sample"),selected="Group"),
#checkboxInput("colorgroup","Same color for the group",value=FALSE),
#sliderInput("cexpoint", "Point size",min=0,max=3,value = 1,step =0.1)
# sliderInput("cexstar", "Star height",min=0,max=1,value = 0.95,step =0.1)
),
conditionalPanel(condition="input.DiagPlot=='pcoaPlot' && input.labelPCOA == input.TaxoSelect",
radioButtons("ellipsePCoA", label = h5(strong("Select the ellipse shape")), choices = list("Panels" = "panels", "Without panels" = "w_panels"), selected = "panels")
),
conditionalPanel(condition = "input.ellipsePCoA == 'w_panels'",
sliderInput("cexcircle", "Circle size",min=0,max=1,value = 0.25,step =0.05)
),
#Display the label button only for individual or correlation plot
conditionalPanel(condition="input.DiagPlot=='pcaPlot'",
uiOutput("labelBiplotButton")
),
conditionalPanel(condition="input.DiagPlot=='pcaPlot' && input.radioPCA != 3 && input.ellipsePCA",
sliderInput("cexcirclePCA", "Circle size",min=0,max=1,value = 0.25,step =0.05)
),
fluidRow(
shinyjs::useShinyjs(),
column(width=12, p(strong("Size"))),
column(width=6,sliderInput("cexTitleDiag", h6("Axis"),min=0,max=5,value = 1,step =0.1)),
conditionalPanel(condition="input.DiagPlot=='SfactorsVStot' || input.DiagPlot=='nmdsPlot' || input.DiagPlot=='umapPlot' || input.DiagPlot == 'pcoaPlot' || (input.DiagPlot=='pcaPlot' && input.radioPCA != 3)",
column(width=6,sliderInput("cexLabelDiag", h6("Points"),min=0,max=5,value = 1,step =0.1))),
conditionalPanel(condition="input.DiagPlot=='pcaPlot' || input.DiagPlot=='pcoaPlot' || input.DiagPlot=='umapPlot'",
column(width=6, sliderInput("cexAxisLabelDiag", h6("Axis label"), min=0,max=5,value=1,step=0.1)),
column(width=6, sliderInput("cexScaleLabelDiag", h6("X-scale and Y-scale labels"),min=0,max=5,value=1,step=0.1)),
column(width=6, sliderInput("cexTitlePlotDiag", h6("Title"),min=0,max=5,value=1,step=0.1)),
column(width=6, sliderInput("cexSubtitleDiag", h6("Subtitle"),min=0,max=5,value=1,step=0.1)),
column(width=6, sliderInput("cexLegendDiag", h6("Legend"),min=0,max=5,value=1,step=0.1))
),
conditionalPanel(
condition = " (input.DiagPlot=='pcaPlot' && (input.checkLabelSamples == true || $('input[name=checkLabelBiplot]:checked').length > 0)) || input.DiagPlot=='pcoaPlot' || (input.DiagPlot=='umapPlot' && input.labelSamplesUMAP == true)",
column(width=6, sliderInput("cexPointsLabelDiag", h6("Data label"), min = 0, max = 5, value = 2, step = 0.5))
)
)
# sliderInput("widthDiag", "width",min=100,max=1500,value = 1000,step =10)
),
box(title = "Export", width = NULL, status = "primary", solidHeader = TRUE,collapsible = TRUE,collapsed= TRUE,
fluidRow(
conditionalPanel(condition=" (input.DiagPlot == 'pcaPlot') || (input.DiagPlot == 'pcoaPlot') ",
column(width = 6,selectInput("Exp_plot", h5(strong("Select the plot to export")), choices= c("Main", "Contribution"), multiple = FALSE))),
column(width = 6, selectInput("Exp_format",h5(strong("Export format")),c("png"="png","pdf"="pdf","eps"="eps","svg"="svg"), multiple = FALSE)),
),
fluidRow(
column(width=6,numericInput("heightDiagExport", "Height (in px)",min=100,max=NA,value = 500,step =1)),
column(width=6,numericInput("widthDiagExport", "Width (in px)",min=100,max=NA,value = 500,step =1))
),
downloadButton("exportdiag", "Export")
# downloadButton("exportPDFdiag", "Download pdf"),
# downloadButton("exportPNGdiag", "Download png"),
# downloadButton("exportEPSdiag", "Download eps"),
# downloadButton("exportSVGdiag", "Download svg"),
)
)
)
),
#### ___TABLES ####
tabItem(tabName = "TableDiff",
fluidRow(
### _____Tables and plots ####
column(width=9,
div(id = "plot-container", tags$img(src = "gears.gif",id ="loading-spinner"),tags$head(tags$style(HTML(spincss))),
div(
uiOutput("TabBoxDataDiff"),
tabBox(id = "tabBoxPlotTables",
width = NULL,
height = 430,
selected = "Bar chart",
#selected = "Volcano plot",