Last updated: 2021-01-14
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Knit directory: esoph-micro-cancer-workflow/
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The goal here is to double check that there is indeed no microbiome data for those samples that say N/A. To help with this, I recoded the N/A values from the excel sheet to -999 so that R’s internal NA system doesn’t confuse us.
# melt data down for use
dat.16s <- psmelt(phylo.data.nci.umd)
# subset to fuso. nuc. only
# Streptococcus sanguinis
# Campylobacter concisus
# Prevotella spp.
dat.16s <- filter(
dat.16s,
OTU %in% c(
"Fusobacterium_nucleatum",
unique(dat.16s$OTU[dat.16s$OTU %like% "Streptococcus_"]),
unique(dat.16s$OTU[dat.16s$OTU %like% "Campylobacter_"]),
"Prevotella_melaninogenica")
)
# rename bacteria
dat.16s$OTU <- factor(
dat.16s$OTU,
levels = c(
"Fusobacterium_nucleatum",
"Streptococcus_dentisani:Streptococcus_infantis:Streptococcus_mitis:Streptococcus_oligofermentans:Streptococcus_oralis:Streptococcus_pneumoniae:Streptococcus_pseudopneumoniae:Streptococcus_sanguinis",
"Campylobacter_rectus:Campylobacter_showae",
"Prevotella_melaninogenica"
),
labels = c(
"Fusobacterium_nucleatum",
"Streptococcus_spp.",
"Campylobacter_concisus",
"Prevotella_melaninogenica"
)
)
# make tumor vs normal variable
dat.16s$tumor.cat <- factor(dat.16s$tissue, levels=c("BO", "N", "T"), labels = c("Non-Tumor", "Non-Tumor", "Tumor"))
# relabel as (0/1) for analysis
dat.16s$tumor <- as.numeric(factor(dat.16s$tissue, levels=c("BO", "N", "T"), labels = c("Non-Tumor", "Non-Tumor", "Tumor"))) - 1
# presence- absence
dat.16s$pres <- ifelse(dat.16s$Abundance > 0, 1, 0)
dat.16s$pres[is.na(dat.16s$pres)] <- 0
# make wide
dat.16s2 <- dat.16s %>%
pivot_wider(
id_cols = c(Sample, accession.number, tissue, tumor.cat),
names_from = OTU,
values_from = Abundance
) %>%
mutate(
Accession = accession.number
)
dat.16s2 <- dat.16s2[, c(1,2,3,6)]
colnames(dat.16s2) <- c("Sample", "Accession", "Tissue", "Fusobacterium_nucleatum_biomfile")
# data from scope
dat.scope <- readxl::read_xlsx("data/EAC tumors for RNAscope.xlsx", sheet = 2)
dat.scope$Fusobacterium_nucleatum[is.na(dat.scope$Fusobacterium_nucleatum)] <- -999
dat.scope <- dat.scope[, c(1,2,16, 19)]
colnames(dat.scope) <- c("Accession", "Tissue", "Fusobacterium_nucleatum_RNAscopefile", "BLACKLINE")
# merge the two files together to see (non)overlap of -999 to NA
dat.16s3 <- full_join(dat.16s2, dat.scope, keep=T)Joining, by = c("Accession", "Tissue")dat.16s3 %>%
arrange(-desc(Accession.x)) %>%
kable(format="html", digits=2)%>%
kable_styling(full_width = T)%>%
scroll_box(width = "100%", height = "500px")| Sample | Accession.x | Tissue.x | Fusobacterium_nucleatum_biomfile | Accession.y | Tissue.y | Fusobacterium_nucleatum_RNAscopefile | BLACKLINE |
|---|---|---|---|---|---|---|---|
| 18.S35.Jun172016 | 10147 | N | 0 | NA | NA | NA | NA |
| 7.A08.S8.Jul202017 | 10153 | N | 0 | NA | NA | NA | NA |
| 17.S14.Jun172016 | 10215 | N | 0 | NA | NA | NA | NA |
| 4.S13.Jun172016 | 10215 | T | 0 | NA | NA | NA | NA |
| 11.B08.S20.Jun232016 | 10245 | N | 0 | NA | NA | NA | NA |
| 5.S4.Jun172016 | 11049 | N | 1 | NA | NA | NA | NA |
| 2.S16.Jun172016 | 11049 | T | 2 | NA | NA | NA | NA |
| 19.S25.Jun172016 | 11229 | N | 2 | NA | NA | NA | NA |
| 8.S8.Jun172016 | 11267 | T | 0 | 11267 | T | 0.0 | Above |
| 16.S38.Jun172016 | 11271 | T | 190 | 11271 | T | 37.2 | Above |
| 1.S37.Jun172016 | 11271 | N | 62 | NA | NA | NA | NA |
| 13.S20.Jun172016 | 11362 | N | 0 | NA | NA | NA | NA |
| 20.A09.S9.Jun232016 | 11394 | N | 0 | NA | NA | NA | NA |
| 6.A10.S10.Jun232016 | 11394 | T | 0 | NA | NA | NA | NA |
| 26.H04.S88.Jun232016 | 11639 | N | 0 | NA | NA | NA | NA |
| 28.S87.Jun172016 | 11677 | N | 0 | NA | NA | NA | NA |
| 42.A04.S4.Jul202017 | 11738 | T | 4 | NA | NA | NA | NA |
| 35.A03.S3.Jul202017 | 11738 | N | 0 | NA | NA | NA | NA |
| 43.S49.Jun172016 | 11743 | T | 0 | NA | NA | NA | NA |
| 29.S31.Jun172016 | 11816 | N | 0 | NA | NA | NA | NA |
| 37.S32.Jun172016 | 11816 | T | 0 | NA | NA | NA | NA |
| 38.C09.S33.Jun232016 | 11833 | T | 28 | NA | NA | NA | NA |
| 34.C10.S34.Jun232016 | 11833 | N | 0 | NA | NA | NA | NA |
| 46.C04.S28.Jul202017 | 11839 | T | 37 | NA | NA | NA | NA |
| 25.C03.S27.Jul202017 | 11839 | N | 4 | NA | NA | NA | NA |
| 48.S43.Jun172016 | 11949 | T | 0 | 11949 | T | 0.0 | Above |
| 47.S44.Jun172016 | 11949 | N | 0 | NA | NA | NA | NA |
| 239.D09.S45.Jun232016 | 11952 | BO | 0 | 11952 | BO | 0.0 | Above |
| 49.S47.Jun172016 | 11987 | N | 0 | NA | NA | NA | NA |
| 23.S75.Jun172016 | 12023 | T | 5 | NA | NA | NA | NA |
| 22.C07.S31.Jun232016 | 12262 | N | 1 | NA | NA | NA | NA |
| 31.C08.S32.Jun232016 | 12262 | T | 5 | NA | NA | NA | NA |
| 50.S56.Jun172016 | 12291 | N | 0 | NA | NA | NA | NA |
| 51.S55.Jun172016 | 12291 | T | 0 | 12291 | T | -999.0 | Below |
| 51.S55.Jun172016 | 12291 | T | 0 | 12291 | T | -999.0 | Below |
| 53.E09.S57.Jun232016 | 12306 | T | 0 | 12306 | T | 0.0 | Above |
| 52.E10.S58.Jun232016 | 12306 | N | 0 | NA | NA | NA | NA |
| 54.G11.S83.Jul202017 | 12328 | N | 0 | NA | NA | NA | NA |
| 55.E03.S51.Jul202017 | 12460 | T | 42 | NA | NA | NA | NA |
| 57.S68.Jun172016 | 12631 | N | 0 | NA | NA | NA | NA |
| 58.S67.Jun172016 | 12631 | T | 2 | NA | NA | NA | NA |
| 59.S72.Jun172016 | 12637 | N | 1 | NA | NA | NA | NA |
| 27.F09.S69.Jun232016 | 12672 | N | 53 | NA | NA | NA | NA |
| 32.S52.Jun172016 | 12672 | T | 0 | 12672 | T | 0.0 | Above |
| 60.C10.S34.Jul202017 | 12705 | N | 0 | NA | NA | NA | NA |
| 62.G10.S82.Jun232016 | 12733 | T | 1 | 12733 | T | -999.0 | Below |
| 61.G09.S81.Jun232016 | 12733 | N | 0 | NA | NA | NA | NA |
| 36.F04.S64.Jul202017 | 12758 | T | 4 | NA | NA | NA | NA |
| 33.F03.S63.Jul202017 | 12758 | N | 0 | NA | NA | NA | NA |
| 226.S50.Jun172016 | 12767 | BO | 0 | 12767 | BO | 0.0 | Above |
| 229.S79.Jun172016 | 12779 | T | 0 | NA | NA | NA | NA |
| 63.D03.S39.Jul202017 | 12779 | N | 0 | NA | NA | NA | NA |
| 66.G04.S76.Jul202017 | 12841 | T | 0 | 12841 | T | -999.0 | Below |
| 67.D10.S46.Jul202017 | 12897 | N | 1 | NA | NA | NA | NA |
| 24.S92.Jun172016 | 12936 | T | 30 | NA | NA | NA | NA |
| 68.S91.Jun172016 | 12936 | N | 0 | NA | NA | NA | NA |
| 71.H10.S94.Jun232016 | 12944 | T | 330 | NA | NA | NA | NA |
| 70.H09.S93.Jun232016 | 12944 | N | 0 | NA | NA | NA | NA |
| 74.H03.S87.Jul202017 | 13008 | T | 236 | 13008 | T | 32.2 | Above |
| 73.H04.S88.Jul202017 | 13008 | N | 224 | NA | NA | NA | NA |
| 77.S10.Jun172016 | 13103 | N | 2 | NA | NA | NA | NA |
| 79.S3.Jun172016 | 13128 | T | 0 | NA | NA | NA | NA |
| 81.A02.S2.Jun232016 | 13202 | T | 15 | NA | NA | NA | NA |
| 80.A01.S1.Jun232016 | 13202 | N | 1 | NA | NA | NA | NA |
| 83.A06.S6.Jul202017 | 13211 | T | 0 | NA | NA | NA | NA |
| 82.A05.S5.Jul202017 | 13211 | N | 0 | NA | NA | NA | NA |
| 84.S22.Jun172016 | 13220 | N | 0 | NA | NA | NA | NA |
| 86.B02.S14.Jun232016 | 13266 | N | 4 | NA | NA | NA | NA |
| 87.B01.S13.Jun232016 | 13266 | T | 21 | NA | NA | NA | NA |
| 88.B05.S17.Jul202017 | 13270 | N | 0 | NA | NA | NA | NA |
| 89.B06.S18.Jul202017 | 13270 | T | 0 | 13270 | T | 0.0 | Above |
| 90.S33.Jun172016 | 13318 | N | 0 | NA | NA | NA | NA |
| 95.C06.S30.Jul202017 | 13367 | T | 0 | NA | NA | NA | NA |
| 97.S45.Jun172016 | 13406 | T | 80 | NA | NA | NA | NA |
| 96.S46.Jun172016 | 13406 | N | 3 | NA | NA | NA | NA |
| 99.D01.S37.Jun232016 | 13430 | T | 0 | NA | NA | NA | NA |
| 98.D02.S38.Jun232016 | 13430 | N | 0 | NA | NA | NA | NA |
| 100.D06.S42.Jul202017 | 13460 | N | 0 | NA | NA | NA | NA |
| 102.S57.Jun172016 | 13462 | N | 1 | NA | NA | NA | NA |
| 103.S58.Jun172016 | 13462 | T | 19 | NA | NA | NA | NA |
| 104.S23.Jun172016 | 13523 | N | 12 | NA | NA | NA | NA |
| 106.E02.S50.Jun232016 | 13553 | T | 0 | 13553 | T | 0.0 | Above |
| 106.E02.S50.Jun232016 | 13553 | T | 0 | 13553 | T | 0.0 | Below |
| 108.E06.S54.Jul202017 | 13622 | BO | 6 | 13622 | BO | 0.0 | Above |
| 110.S69.Jun172016 | 13658 | T | 0 | NA | NA | NA | NA |
| 109.S70.Jun172016 | 13658 | N | 1 | NA | NA | NA | NA |
| 112.F02.S62.Jun232016 | 13702 | N | 24 | NA | NA | NA | NA |
| 113.F01.S61.Jun232016 | 13702 | T | 6 | 13702 | T | 0.0 | Above |
| 118.S82.Jun172016 | 13850 | T | 0 | NA | NA | NA | NA |
| 234.C07.S31.Jul202017 | 13922 | BO | 4 | 13922 | BO | 0.8 | Above |
| 119.G01.S73.Jun232016 | 13927 | N | 0 | NA | NA | NA | NA |
| 121.G05.S77.Jul202017 | 13987 | N | 0 | NA | NA | NA | NA |
| 124.S93.Jun172016 | 14033 | T | 38 | NA | NA | NA | NA |
| 125.H06.S90.Jul202017 | 14066 | N | 0 | NA | NA | NA | NA |
| 128.S5.Jun172016 | 14081 | T | 11 | NA | NA | NA | NA |
| 127.S6.Jun172016 | 14081 | N | 22 | NA | NA | NA | NA |
| 130.A02.S2.Jul202017 | 14130 | T | 9 | NA | NA | NA | NA |
| 129.A01.S1.Jul202017 | 14130 | N | 0 | NA | NA | NA | NA |
| 131.S62.Jun172016 | 14146 | T | 3 | NA | NA | NA | NA |
| 134.F11.S71.Jun172016 | 14378 | T | 0 | NA | NA | NA | NA |
| 135.B06.S18.Jun232016 | 14403 | N | 92 | NA | NA | NA | NA |
| 137.F09.S69.Jul202017 | 14423 | N | 0 | NA | NA | NA | NA |
| 139.F07.S67.Jun232016 | 14466 | N | 10 | NA | NA | NA | NA |
| 140.B02.S14.Jul202017 | 14495 | N | 1 | NA | NA | NA | NA |
| 142.E08.S56.Jul202017 | 14510 | N | 0 | NA | NA | NA | NA |
| 143.G08.S80.Jul202017 | 14523 | N | 0 | NA | NA | NA | NA |
| 146.S29.Jun172016 | 14717 | N | 1 | NA | NA | NA | NA |
| 148.S30.Jun172016 | 14717 | T | 0 | NA | NA | NA | NA |
| 145.D09.S45.Jul202017 | 14751 | T | 0 | NA | NA | NA | NA |
| 150.C06.S30.Jun232016 | 14827 | T | 3 | NA | NA | NA | NA |
| 149.C05.S29.Jun232016 | 14827 | N | 0 | NA | NA | NA | NA |
| 151.E03.S51.Jun232016 | 15180 | N | 0 | NA | NA | NA | NA |
| 152.H07.S91.Jun232016 | 15232 | T | 0 | NA | NA | NA | NA |
| 154.C02.S26.Jul202017 | 15239 | T | 4 | 15239 | T | 0.8 | Above |
| 155.C09.S33.Jul202017 | 15501 | T | 1 | NA | NA | NA | NA |
| 114.S41.Jun172016 | 15707 | N | 72 | NA | NA | NA | NA |
| 156.S42.Jun172016 | 15707 | T | 168 | NA | NA | NA | NA |
| 157.D05.S41.Jun232016 | 15725 | N | 2 | NA | NA | NA | NA |
| 158.D06.S42.Jun232016 | 15725 | T | 70 | NA | NA | NA | NA |
| 159.B10.S22.Jul202017 | 15752 | T | 6 | NA | NA | NA | NA |
| 160.E04.S52.Jun232016 | 15770 | N | 0 | NA | NA | NA | NA |
| 162.G04.S76.Jun232016 | 15876 | N | 1 | NA | NA | NA | NA |
| 165.S54.Jun172016 | 16210 | T | 0 | NA | NA | NA | NA |
| 167.E05.S53.Jun232016 | 16243 | T | 19 | 16243 | T | 0.0 | Below |
| 166.E06.S54.Jun232016 | 16243 | N | 1 | NA | NA | NA | NA |
| 168.S59.Jun172016 | 16418 | N | 3 | NA | NA | NA | NA |
| 170.E02.S50.Jul202017 | 16549 | N | 0 | NA | NA | NA | NA |
| 173.S66.Jun172016 | 16590 | T | 97 | NA | NA | NA | NA |
| 172.S65.Jun172016 | 16590 | N | 11 | NA | NA | NA | NA |
| 174.S76.Jun172016 | 16592 | N | 61 | NA | NA | NA | NA |
| 175.S88.Jun172016 | 16592 | T | 39 | 16592 | T | 7.6 | Above |
| 175.S88.Jun172016 | 16592 | T | 39 | 16592 | T | 7.6 | Below |
| 176.H07.S91.Jul202017 | 16608 | N | 0 | NA | NA | NA | NA |
| 179.F01.S61.Jul202017 | 16736 | T | 12 | NA | NA | NA | NA |
| 178.F02.S62.Jul202017 | 16736 | N | 0 | NA | NA | NA | NA |
| 181.D02.S38.Jul202017 | 16745 | T | 0 | NA | NA | NA | NA |
| 227.S74.Jun172016 | 16745 | N | 1 | NA | NA | NA | NA |
| 184.S61.Jun172016 | 16981 | N | 5 | NA | NA | NA | NA |
| 185.G08.S80.Jun232016 | 17002 | N | 0 | NA | NA | NA | NA |
| 186.S77.Jun172016 | 17206 | N | 21 | NA | NA | NA | NA |
| 187.S78.Jun172016 | 17206 | T | 0 | 17206 | T | 0.0 | Below |
| 189.G05.S77.Jun232016 | 17223 | T | 0 | 17223 | T | -999.0 | Below |
| 188.G06.S78.Jun232016 | 17223 | N | 1 | NA | NA | NA | NA |
| 191.G02.S74.Jul202017 | 17285 | T | 4 | NA | NA | NA | NA |
| 190.G01.S73.Jul202017 | 17285 | N | 0 | NA | NA | NA | NA |
| 194.H05.S89.Jun232016 | 17304 | N | 0 | NA | NA | NA | NA |
| 195.H06.S90.Jun232016 | 17304 | T | 0 | 17304 | T | 0.0 | Above |
| 196.D08.S44.Jun232016 | 17353 | N | 0 | NA | NA | NA | NA |
| 197.G07.S79.Jul202017 | 17435 | N | 0 | NA | NA | NA | NA |
| 198.F03.S63.Jun232016 | 17493 | N | 0 | NA | NA | NA | NA |
| 199.A11.S11.Jun232016 | 17512 | N | 11 | NA | NA | NA | NA |
| 200.S96.Jun172016 | 17525 | N | 0 | NA | NA | NA | NA |
| 201.H02.S86.Jun242016 | 17525 | T | 0 | NA | NA | NA | NA |
| 202.D07.S43.Jul202017 | 17606 | N | 0 | NA | NA | NA | NA |
| 205.S2.Jun172016 | 17683 | T | 385 | 17683 | T | 0.0 | Below |
| 204.S1.Jun172016 | 17683 | N | 159 | NA | NA | NA | NA |
| 206.S51.Jun172016 | 17698 | N | 0 | NA | NA | NA | NA |
| 233.G07.S79.Jun232016 | 17799 | BO | 5 | 17799 | BO | 0.4 | Above |
| 208.D03.S39.Jun232016 | 17842 | N | 1 | NA | NA | NA | NA |
| 211.A07.S7.Jun232016 | 17918 | N | 0 | NA | NA | NA | NA |
| 212.A08.S8.Jun232016 | 17918 | T | 0 | 17918 | T | 0.0 | Above |
| NA | NA | NA | NA | 13732 | BO | -999.0 | Above |
| NA | NA | NA | NA | 16555 | BO | -999.0 | Above |
| NA | NA | NA | NA | 16976 | BO | -999.0 | Above |
| NA | NA | NA | NA | 11802 | BO | -999.0 | Above |
| NA | NA | NA | NA | 14130 | BO | -999.0 | Above |
| NA | NA | NA | NA | 11267 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11271 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11455 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11455 | T | -999.0 | Above |
| NA | NA | NA | NA | 11949 | NT | -999.0 | Above |
| NA | NA | NA | NA | 12306 | NT | -999.0 | Above |
| NA | NA | NA | NA | 12672 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13008 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13103 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13103 | T | -999.0 | Above |
| NA | NA | NA | NA | 13270 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13318 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13318 | T | -999.0 | Above |
| NA | NA | NA | NA | 13553 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13702 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13927 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13927 | T | -999.0 | Above |
| NA | NA | NA | NA | 14719 | NT | -999.0 | Above |
| NA | NA | NA | NA | 14719 | T | -999.0 | Above |
| NA | NA | NA | NA | 15180 | NT | -999.0 | Above |
| NA | NA | NA | NA | 15180 | T | -999.0 | Above |
| NA | NA | NA | NA | 15239 | NT | -999.0 | Above |
| NA | NA | NA | NA | 16034 | NT | -999.0 | Above |
| NA | NA | NA | NA | 16034 | T | -999.0 | Above |
| NA | NA | NA | NA | 16592 | NT | -999.0 | Above |
| NA | NA | NA | NA | 17304 | NT | -999.0 | Above |
| NA | NA | NA | NA | 17918 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13553 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12733 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12291 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12291 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12841 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12997 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12997 | T | -999.0 | Below |
| NA | NA | NA | NA | 13103 | NT | -999.0 | Below |
| NA | NA | NA | NA | 13103 | T | -999.0 | Below |
| NA | NA | NA | NA | 16243 | NT | 0.2 | Below |
| NA | NA | NA | NA | 16592 | NT | 0.0 | Below |
| NA | NA | NA | NA | 16642 | NT | 0.0 | Below |
| NA | NA | NA | NA | 16642 | T | 76.6 | Below |
| NA | NA | NA | NA | 17206 | NT | -999.0 | Below |
| NA | NA | NA | NA | 17223 | NT | 0.0 | Below |
| NA | NA | NA | NA | 17683 | NT | -999.0 | Below |
This is to double check how the .biom file was in read. It appears as nearly all NA values from the
meta.data <- read_excel(
"data/NCI-UMD/UMD Esoph dataset from EB_2019_08_06_AV edits.xlsx",
sheet = "FOR STATA"
)
# subset to unique "sample ids
meta.data <- meta.data %>% distinct(`Sample ID`, .keep_all = T)
#read_xlsx("data/NCI-UMD/NCI_UMD_metadata_2020_09_17.xlsx")
# change "_" in sampleid to "." to match .biome file
meta.data$sampleid <- meta.data$`Sample ID`
meta.data$ID <- stringr::str_replace_all(meta.data$sampleid, "_", ".")
# get microbiome data
biom.file <- import_biom("data/NCI-UMD/otu_table_even500.biom")
tree.file <- read_tree("data/NCI-UMD/reps_even500.tre")
# create phyloseq object
meta <- sample_data(meta.data)
sample_names(meta) <- meta.data$ID
# update otu table to include "zeros" for non-found samples
phylo.data0 <- merge_phyloseq(biom.file, tree.file, meta)
dat.16s.raw <- psmelt(phylo.data0)
dat.16s.raw <- filter(dat.16s.raw, OTU == "Fusobacterium_nucleatum")
dat.16s.raw <- dat.16s.raw %>% select(Sample, accession.number, tissue, Abundance)
colnames(dat.16s.raw) <- c("Sample", "Accession", "Tissue", "Fusobacterium_nucleatum_biomfile")
# scope data
dat.scope <- readxl::read_xlsx("data/EAC tumors for RNAscope.xlsx", sheet = 2)
dat.scope$Fusobacterium_nucleatum[is.na(dat.scope$Fusobacterium_nucleatum)] <- -999
dat.scope <- dat.scope[, c(1,2,16, 19)]
colnames(dat.scope) <- c("Accession", "Tissue", "Fusobacterium_nucleatum_RNAscopefile", "BLACKLINE")
# merge with the "scope data"
dat.16s.raw2 <- full_join(dat.16s.raw, dat.scope, keep = T)Joining, by = c("Accession", "Tissue")dat.16s.raw2 %>%
arrange(-desc(Accession.x)) %>%
kable(format="html", digits=2)%>%
kable_styling(full_width = T)%>%
scroll_box(width = "100%", height = "500px")| Sample | Accession.x | Tissue.x | Fusobacterium_nucleatum_biomfile | Accession.y | Tissue.y | Fusobacterium_nucleatum_RNAscopefile | BLACKLINE |
|---|---|---|---|---|---|---|---|
| 18.S35.Jun172016 | 10147 | N | 0 | NA | NA | NA | NA |
| 7.A08.S8.Jul202017 | 10153 | N | 0 | NA | NA | NA | NA |
| 4.S13.Jun172016 | 10215 | T | 0 | NA | NA | NA | NA |
| 17.S14.Jun172016 | 10215 | N | 0 | NA | NA | NA | NA |
| 11.B08.S20.Jun232016 | 10245 | N | 0 | NA | NA | NA | NA |
| 2.S16.Jun172016 | 11049 | T | 2 | NA | NA | NA | NA |
| 5.S4.Jun172016 | 11049 | N | 0 | NA | NA | NA | NA |
| 19.S25.Jun172016 | 11229 | N | 0 | NA | NA | NA | NA |
| 8.S8.Jun172016 | 11267 | T | 0 | 11267 | T | 0.0 | Above |
| 16.S38.Jun172016 | 11271 | T | 186 | 11271 | T | 37.2 | Above |
| 1.S37.Jun172016 | 11271 | N | 41 | NA | NA | NA | NA |
| 13.S20.Jun172016 | 11362 | N | 0 | NA | NA | NA | NA |
| 20.A09.S9.Jun232016 | 11394 | N | 0 | NA | NA | NA | NA |
| 6.A10.S10.Jun232016 | 11394 | T | 0 | NA | NA | NA | NA |
| 26.H04.S88.Jun232016 | 11639 | N | 0 | NA | NA | NA | NA |
| 28.S87.Jun172016 | 11677 | N | 0 | NA | NA | NA | NA |
| 42.A04.S4.Jul202017 | 11738 | T | 1 | NA | NA | NA | NA |
| 35.A03.S3.Jul202017 | 11738 | N | 0 | NA | NA | NA | NA |
| 43.S49.Jun172016 | 11743 | T | 0 | NA | NA | NA | NA |
| 29.S31.Jun172016 | 11816 | N | 0 | NA | NA | NA | NA |
| 37.S32.Jun172016 | 11816 | T | 0 | NA | NA | NA | NA |
| 38.C09.S33.Jun232016 | 11833 | T | 12 | NA | NA | NA | NA |
| 34.C10.S34.Jun232016 | 11833 | N | 0 | NA | NA | NA | NA |
| 25.C03.S27.Jul202017 | 11839 | N | 4 | NA | NA | NA | NA |
| 46.C04.S28.Jul202017 | 11839 | T | 0 | NA | NA | NA | NA |
| 48.S43.Jun172016 | 11949 | T | 0 | 11949 | T | 0.0 | Above |
| 47.S44.Jun172016 | 11949 | N | 0 | NA | NA | NA | NA |
| 239.D09.S45.Jun232016 | 11952 | BO | 0 | 11952 | BO | 0.0 | Above |
| 49.S47.Jun172016 | 11987 | N | 0 | NA | NA | NA | NA |
| 23.S75.Jun172016 | 12023 | T | 4 | NA | NA | NA | NA |
| 22.C07.S31.Jun232016 | 12262 | N | 0 | NA | NA | NA | NA |
| 31.C08.S32.Jun232016 | 12262 | T | 0 | NA | NA | NA | NA |
| 50.S56.Jun172016 | 12291 | N | 0 | NA | NA | NA | NA |
| 51.S55.Jun172016 | 12291 | T | 0 | 12291 | T | -999.0 | Below |
| 51.S55.Jun172016 | 12291 | T | 0 | 12291 | T | -999.0 | Below |
| 53.E09.S57.Jun232016 | 12306 | T | 0 | 12306 | T | 0.0 | Above |
| 52.E10.S58.Jun232016 | 12306 | N | 0 | NA | NA | NA | NA |
| 54.G11.S83.Jul202017 | 12328 | N | 0 | NA | NA | NA | NA |
| 55.E03.S51.Jul202017 | 12460 | T | 0 | NA | NA | NA | NA |
| 57.S68.Jun172016 | 12631 | N | 0 | NA | NA | NA | NA |
| 58.S67.Jun172016 | 12631 | T | 0 | NA | NA | NA | NA |
| 59.S72.Jun172016 | 12637 | N | 1 | NA | NA | NA | NA |
| 32.S52.Jun172016 | 12672 | T | 0 | 12672 | T | 0.0 | Above |
| 27.F09.S69.Jun232016 | 12672 | N | 0 | NA | NA | NA | NA |
| 60.C10.S34.Jul202017 | 12705 | N | 0 | NA | NA | NA | NA |
| 62.G10.S82.Jun232016 | 12733 | T | 1 | 12733 | T | -999.0 | Below |
| 61.G09.S81.Jun232016 | 12733 | N | 0 | NA | NA | NA | NA |
| 36.F04.S64.Jul202017 | 12758 | T | 1 | NA | NA | NA | NA |
| 33.F03.S63.Jul202017 | 12758 | N | 0 | NA | NA | NA | NA |
| 226.S50.Jun172016 | 12767 | BO | 0 | 12767 | BO | 0.0 | Above |
| 229.S79.Jun172016 | 12779 | T | 0 | NA | NA | NA | NA |
| 63.D03.S39.Jul202017 | 12779 | N | 0 | NA | NA | NA | NA |
| 66.G04.S76.Jul202017 | 12841 | T | 0 | 12841 | T | -999.0 | Below |
| 67.D10.S46.Jul202017 | 12897 | N | 1 | NA | NA | NA | NA |
| 24.S92.Jun172016 | 12936 | T | 1 | NA | NA | NA | NA |
| 68.S91.Jun172016 | 12936 | N | 0 | NA | NA | NA | NA |
| 71.H10.S94.Jun232016 | 12944 | T | 324 | NA | NA | NA | NA |
| 70.H09.S93.Jun232016 | 12944 | N | 0 | NA | NA | NA | NA |
| 74.H03.S87.Jul202017 | 13008 | T | 161 | 13008 | T | 32.2 | Above |
| 73.H04.S88.Jul202017 | 13008 | N | 149 | NA | NA | NA | NA |
| 77.S10.Jun172016 | 13103 | N | 2 | NA | NA | NA | NA |
| 79.S3.Jun172016 | 13128 | T | 0 | NA | NA | NA | NA |
| 81.A02.S2.Jun232016 | 13202 | T | 14 | NA | NA | NA | NA |
| 80.A01.S1.Jun232016 | 13202 | N | 0 | NA | NA | NA | NA |
| 82.A05.S5.Jul202017 | 13211 | N | 0 | NA | NA | NA | NA |
| 83.A06.S6.Jul202017 | 13211 | T | 0 | NA | NA | NA | NA |
| 84.S22.Jun172016 | 13220 | N | 0 | NA | NA | NA | NA |
| 87.B01.S13.Jun232016 | 13266 | T | 20 | NA | NA | NA | NA |
| 86.B02.S14.Jun232016 | 13266 | N | 4 | NA | NA | NA | NA |
| 88.B05.S17.Jul202017 | 13270 | N | 0 | NA | NA | NA | NA |
| 89.B06.S18.Jul202017 | 13270 | T | 0 | 13270 | T | 0.0 | Above |
| 90.S33.Jun172016 | 13318 | N | 0 | NA | NA | NA | NA |
| 95.C06.S30.Jul202017 | 13367 | T | 0 | NA | NA | NA | NA |
| 96.S46.Jun172016 | 13406 | N | 3 | NA | NA | NA | NA |
| 97.S45.Jun172016 | 13406 | T | 0 | NA | NA | NA | NA |
| 99.D01.S37.Jun232016 | 13430 | T | 0 | NA | NA | NA | NA |
| 98.D02.S38.Jun232016 | 13430 | N | 0 | NA | NA | NA | NA |
| 100.D06.S42.Jul202017 | 13460 | N | 0 | NA | NA | NA | NA |
| 103.S58.Jun172016 | 13462 | T | 19 | NA | NA | NA | NA |
| 102.S57.Jun172016 | 13462 | N | 1 | NA | NA | NA | NA |
| 104.S23.Jun172016 | 13523 | N | 4 | NA | NA | NA | NA |
| 106.E02.S50.Jun232016 | 13553 | T | 0 | 13553 | T | 0.0 | Above |
| 106.E02.S50.Jun232016 | 13553 | T | 0 | 13553 | T | 0.0 | Below |
| 108.E06.S54.Jul202017 | 13622 | BO | 0 | 13622 | BO | 0.0 | Above |
| 110.S69.Jun172016 | 13658 | T | 0 | NA | NA | NA | NA |
| 109.S70.Jun172016 | 13658 | N | 0 | NA | NA | NA | NA |
| 113.F01.S61.Jun232016 | 13702 | T | 0 | 13702 | T | 0.0 | Above |
| 112.F02.S62.Jun232016 | 13702 | N | 0 | NA | NA | NA | NA |
| 118.S82.Jun172016 | 13850 | T | 0 | NA | NA | NA | NA |
| 234.C07.S31.Jul202017 | 13922 | BO | 4 | 13922 | BO | 0.8 | Above |
| 119.G01.S73.Jun232016 | 13927 | N | 0 | NA | NA | NA | NA |
| 121.G05.S77.Jul202017 | 13987 | N | 0 | NA | NA | NA | NA |
| 124.S93.Jun172016 | 14033 | T | 38 | NA | NA | NA | NA |
| 125.H06.S90.Jul202017 | 14066 | N | 0 | NA | NA | NA | NA |
| 127.S6.Jun172016 | 14081 | N | 1 | NA | NA | NA | NA |
| 128.S5.Jun172016 | 14081 | T | 0 | NA | NA | NA | NA |
| 130.A02.S2.Jul202017 | 14130 | T | 1 | NA | NA | NA | NA |
| 129.A01.S1.Jul202017 | 14130 | N | 0 | NA | NA | NA | NA |
| 131.S62.Jun172016 | 14146 | T | 1 | NA | NA | NA | NA |
| 134.F11.S71.Jun172016 | 14378 | T | 0 | NA | NA | NA | NA |
| 135.B06.S18.Jun232016 | 14403 | N | 0 | NA | NA | NA | NA |
| 137.F09.S69.Jul202017 | 14423 | N | 0 | NA | NA | NA | NA |
| 139.F07.S67.Jun232016 | 14466 | N | 0 | NA | NA | NA | NA |
| 140.B02.S14.Jul202017 | 14495 | N | 1 | NA | NA | NA | NA |
| 142.E08.S56.Jul202017 | 14510 | N | 0 | NA | NA | NA | NA |
| 143.G08.S80.Jul202017 | 14523 | N | 0 | NA | NA | NA | NA |
| 146.S29.Jun172016 | 14717 | N | 1 | NA | NA | NA | NA |
| 148.S30.Jun172016 | 14717 | T | 0 | NA | NA | NA | NA |
| 145.D09.S45.Jul202017 | 14751 | T | 0 | NA | NA | NA | NA |
| 150.C06.S30.Jun232016 | 14827 | T | 3 | NA | NA | NA | NA |
| 149.C05.S29.Jun232016 | 14827 | N | 0 | NA | NA | NA | NA |
| 151.E03.S51.Jun232016 | 15180 | N | 0 | NA | NA | NA | NA |
| 152.H07.S91.Jun232016 | 15232 | T | 0 | NA | NA | NA | NA |
| 154.C02.S26.Jul202017 | 15239 | T | 4 | 15239 | T | 0.8 | Above |
| 155.C09.S33.Jul202017 | 15501 | T | 0 | NA | NA | NA | NA |
| 156.S42.Jun172016 | 15707 | T | 133 | NA | NA | NA | NA |
| 114.S41.Jun172016 | 15707 | N | 54 | NA | NA | NA | NA |
| 158.D06.S42.Jun232016 | 15725 | T | 5 | NA | NA | NA | NA |
| 157.D05.S41.Jun232016 | 15725 | N | 0 | NA | NA | NA | NA |
| 159.B10.S22.Jul202017 | 15752 | T | 2 | NA | NA | NA | NA |
| 160.E04.S52.Jun232016 | 15770 | N | 0 | NA | NA | NA | NA |
| 162.G04.S76.Jun232016 | 15876 | N | 0 | NA | NA | NA | NA |
| 165.S54.Jun172016 | 16210 | T | 0 | NA | NA | NA | NA |
| 166.E06.S54.Jun232016 | 16243 | N | 0 | NA | NA | NA | NA |
| 167.E05.S53.Jun232016 | 16243 | T | 0 | 16243 | T | 0.0 | Below |
| 168.S59.Jun172016 | 16418 | N | 1 | NA | NA | NA | NA |
| 170.E02.S50.Jul202017 | 16549 | N | 0 | NA | NA | NA | NA |
| 172.S65.Jun172016 | 16590 | N | 0 | NA | NA | NA | NA |
| 173.S66.Jun172016 | 16590 | T | 0 | NA | NA | NA | NA |
| 174.S76.Jun172016 | 16592 | N | 61 | NA | NA | NA | NA |
| 175.S88.Jun172016 | 16592 | T | 38 | 16592 | T | 7.6 | Above |
| 175.S88.Jun172016 | 16592 | T | 38 | 16592 | T | 7.6 | Below |
| 176.H07.S91.Jul202017 | 16608 | N | 0 | NA | NA | NA | NA |
| 179.F01.S61.Jul202017 | 16736 | T | 5 | NA | NA | NA | NA |
| 178.F02.S62.Jul202017 | 16736 | N | 0 | NA | NA | NA | NA |
| 227.S74.Jun172016 | 16745 | N | 1 | NA | NA | NA | NA |
| 181.D02.S38.Jul202017 | 16745 | T | 0 | NA | NA | NA | NA |
| 184.S61.Jun172016 | 16981 | N | 4 | NA | NA | NA | NA |
| 185.G08.S80.Jun232016 | 17002 | N | 0 | NA | NA | NA | NA |
| 186.S77.Jun172016 | 17206 | N | 0 | NA | NA | NA | NA |
| 187.S78.Jun172016 | 17206 | T | 0 | 17206 | T | 0.0 | Below |
| 189.G05.S77.Jun232016 | 17223 | T | 0 | 17223 | T | -999.0 | Below |
| 188.G06.S78.Jun232016 | 17223 | N | 0 | NA | NA | NA | NA |
| 191.G02.S74.Jul202017 | 17285 | T | 4 | NA | NA | NA | NA |
| 190.G01.S73.Jul202017 | 17285 | N | 0 | NA | NA | NA | NA |
| 194.H05.S89.Jun232016 | 17304 | N | 0 | NA | NA | NA | NA |
| 195.H06.S90.Jun232016 | 17304 | T | 0 | 17304 | T | 0.0 | Above |
| 196.D08.S44.Jun232016 | 17353 | N | 0 | NA | NA | NA | NA |
| 197.G07.S79.Jul202017 | 17435 | N | 0 | NA | NA | NA | NA |
| 198.F03.S63.Jun232016 | 17493 | N | 0 | NA | NA | NA | NA |
| 199.A11.S11.Jun232016 | 17512 | N | 3 | NA | NA | NA | NA |
| 200.S96.Jun172016 | 17525 | N | 0 | NA | NA | NA | NA |
| 201.H02.S86.Jun242016 | 17525 | T | 0 | NA | NA | NA | NA |
| 202.D07.S43.Jul202017 | 17606 | N | 0 | NA | NA | NA | NA |
| 205.S2.Jun172016 | 17683 | T | 383 | 17683 | T | 0.0 | Below |
| 204.S1.Jun172016 | 17683 | N | 158 | NA | NA | NA | NA |
| 206.S51.Jun172016 | 17698 | N | 0 | NA | NA | NA | NA |
| 233.G07.S79.Jun232016 | 17799 | BO | 2 | 17799 | BO | 0.4 | Above |
| 208.D03.S39.Jun232016 | 17842 | N | 0 | NA | NA | NA | NA |
| 212.A08.S8.Jun232016 | 17918 | T | 0 | 17918 | T | 0.0 | Above |
| 211.A07.S7.Jun232016 | 17918 | N | 0 | NA | NA | NA | NA |
| NA | NA | NA | NA | 13732 | BO | -999.0 | Above |
| NA | NA | NA | NA | 16555 | BO | -999.0 | Above |
| NA | NA | NA | NA | 16976 | BO | -999.0 | Above |
| NA | NA | NA | NA | 11802 | BO | -999.0 | Above |
| NA | NA | NA | NA | 14130 | BO | -999.0 | Above |
| NA | NA | NA | NA | 11267 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11271 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11455 | NT | -999.0 | Above |
| NA | NA | NA | NA | 11455 | T | -999.0 | Above |
| NA | NA | NA | NA | 11949 | NT | -999.0 | Above |
| NA | NA | NA | NA | 12306 | NT | -999.0 | Above |
| NA | NA | NA | NA | 12672 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13008 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13103 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13103 | T | -999.0 | Above |
| NA | NA | NA | NA | 13270 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13318 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13318 | T | -999.0 | Above |
| NA | NA | NA | NA | 13553 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13702 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13927 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13927 | T | -999.0 | Above |
| NA | NA | NA | NA | 14719 | NT | -999.0 | Above |
| NA | NA | NA | NA | 14719 | T | -999.0 | Above |
| NA | NA | NA | NA | 15180 | NT | -999.0 | Above |
| NA | NA | NA | NA | 15180 | T | -999.0 | Above |
| NA | NA | NA | NA | 15239 | NT | -999.0 | Above |
| NA | NA | NA | NA | 16034 | NT | -999.0 | Above |
| NA | NA | NA | NA | 16034 | T | -999.0 | Above |
| NA | NA | NA | NA | 16592 | NT | -999.0 | Above |
| NA | NA | NA | NA | 17304 | NT | -999.0 | Above |
| NA | NA | NA | NA | 17918 | NT | -999.0 | Above |
| NA | NA | NA | NA | 13553 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12733 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12291 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12291 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12841 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12997 | NT | -999.0 | Below |
| NA | NA | NA | NA | 12997 | T | -999.0 | Below |
| NA | NA | NA | NA | 13103 | NT | -999.0 | Below |
| NA | NA | NA | NA | 13103 | T | -999.0 | Below |
| NA | NA | NA | NA | 16243 | NT | 0.2 | Below |
| NA | NA | NA | NA | 16592 | NT | 0.0 | Below |
| NA | NA | NA | NA | 16642 | NT | 0.0 | Below |
| NA | NA | NA | NA | 16642 | T | 76.6 | Below |
| NA | NA | NA | NA | 17206 | NT | -999.0 | Below |
| NA | NA | NA | NA | 17223 | NT | 0.0 | Below |
| NA | NA | NA | NA | 17683 | NT | -999.0 | Below |
sessionInfo()R version 4.0.2 (2020-06-22)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 18363)
Matrix products: default
locale:
[1] LC_COLLATE=English_United States.1252
[2] LC_CTYPE=English_United States.1252
[3] LC_MONETARY=English_United States.1252
[4] LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] car_3.0-8 carData_3.0-4 gvlma_1.0.0.3 patchwork_1.0.1
[5] viridis_0.5.1 viridisLite_0.3.0 gridExtra_2.3 xtable_1.8-4
[9] kableExtra_1.1.0 plyr_1.8.6 data.table_1.13.0 readxl_1.3.1
[13] forcats_0.5.0 stringr_1.4.0 dplyr_1.0.1 purrr_0.3.4
[17] readr_1.3.1 tidyr_1.1.1 tibble_3.0.3 ggplot2_3.3.2
[21] tidyverse_1.3.0 lmerTest_3.1-2 lme4_1.1-23 Matrix_1.2-18
[25] vegan_2.5-6 lattice_0.20-41 permute_0.9-5 phyloseq_1.32.0
[29] workflowr_1.6.2
loaded via a namespace (and not attached):
[1] minqa_1.2.4 colorspace_1.4-1 rio_0.5.16
[4] ellipsis_0.3.1 rprojroot_1.3-2 XVector_0.28.0
[7] fs_1.5.0 rstudioapi_0.11 fansi_0.4.1
[10] lubridate_1.7.9 xml2_1.3.2 codetools_0.2-16
[13] splines_4.0.2 knitr_1.29 ade4_1.7-15
[16] jsonlite_1.7.0 nloptr_1.2.2.2 broom_0.7.0
[19] cluster_2.1.0 dbplyr_1.4.4 BiocManager_1.30.10
[22] compiler_4.0.2 httr_1.4.2 backports_1.1.7
[25] assertthat_0.2.1 cli_2.0.2 later_1.1.0.1
[28] htmltools_0.5.0 tools_4.0.2 igraph_1.2.5
[31] gtable_0.3.0 glue_1.4.1 reshape2_1.4.4
[34] Rcpp_1.0.5 Biobase_2.48.0 cellranger_1.1.0
[37] vctrs_0.3.2 Biostrings_2.56.0 multtest_2.44.0
[40] ape_5.4 nlme_3.1-148 iterators_1.0.12
[43] xfun_0.19 openxlsx_4.1.5 rvest_0.3.6
[46] lifecycle_0.2.0 statmod_1.4.34 zlibbioc_1.34.0
[49] MASS_7.3-51.6 scales_1.1.1 hms_0.5.3
[52] promises_1.1.1 parallel_4.0.2 biomformat_1.16.0
[55] rhdf5_2.32.2 curl_4.3 yaml_2.2.1
[58] stringi_1.4.6 highr_0.8 S4Vectors_0.26.1
[61] foreach_1.5.0 BiocGenerics_0.34.0 zip_2.0.4
[64] boot_1.3-25 rlang_0.4.7 pkgconfig_2.0.3
[67] evaluate_0.14 Rhdf5lib_1.10.1 tidyselect_1.1.0
[70] magrittr_1.5 R6_2.4.1 IRanges_2.22.2
[73] generics_0.0.2 DBI_1.1.0 foreign_0.8-80
[76] pillar_1.4.6 haven_2.3.1 whisker_0.4
[79] withr_2.2.0 mgcv_1.8-31 abind_1.4-5
[82] survival_3.2-3 modelr_0.1.8 crayon_1.3.4
[85] rmarkdown_2.5 grid_4.0.2 blob_1.2.1
[88] git2r_0.27.1 reprex_0.3.0 digest_0.6.25
[91] webshot_0.5.2 httpuv_1.5.4 numDeriv_2016.8-1.1
[94] stats4_4.0.2 munsell_0.5.0