analysis using PHATE

library(patchwork)
library(dplyr)
library(ggplot2)
library(ade4)
library(phateR)

Le chargement a nécessité le package : Matrix

devtools::load_all(reset = FALSE)

ℹ Loading gutzilla

load genus abundance

genus_path = system.file("data-raw/qiime/generated-files-20190512/taxa/genus.qza", package = "gutzilla")

genus = qiime2R::read_qza(genus_path)$data %>% as.data.frame %>% tibble::rownames_to_column("taxa")  %>% as_tibble()

import outliers file

outliers = readLines(con="outliers_samples.txt")

load enterotypes set from DMM analysis

enterotypes = readr::read_csv2("enterotypes_prediction_outliers.csv")[,-1]

ℹ Using "','" as decimal and "'.'" as grouping mark. Use `read_delim()` for more control.
New names:Rows: 17600 Columns: 5── Column specification ───────────────────────────────────────────────────────────
Delimiter: ";"
chr (2): sample_name, set
dbl (3): ...1, Enterotypes_id, value
ℹ Use `spec()` to retrieve the full column specification for this data.
ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

read mass based filtering

select based on top 30 read mass genus and remove outliers

genus %>%
  #select(1:10) %>%
  mutate_at(-1, ~./sum(.)) -> genus_prop

top_genus_mass = 
  genus_prop %>% 
  select(-all_of(outliers)) %>%
  tibble::column_to_rownames("taxa") %>% 
  as.matrix %>% 
  apply(1,sum) %>% 
  sort %>% rev %>% head(30)


genus %>%
  select(-all_of(outliers)) %>%
  tibble::column_to_rownames("taxa") %>% .[names(top_genus_mass),]-> genus

genus_prop %>%
  select(-all_of(outliers)) %>%
  tibble::column_to_rownames("taxa") %>% .[names(top_genus_mass),]-> genus_prop

PHATE computation

#genus_L1 = phateR::library.size.normalize(genus %>% t)

genus_phate = 
  genus_prop %>%
  t() %>%
  merge(enterotypes %>% filter(set != "outliers", value>0.80) %>% select(sample_name), by.x="row.names", by.y="sample_name") %>% 
  tibble::column_to_rownames("Row.names") %>%
  phateR::phate(gamma=0, t=60, seed=666)

Calculating PHATE...
  Running PHATE on 11253 observations and 30 variables.
  Calculating graph and diffusion operator...
    Calculating KNN search...
    Calculated KNN search in 3.65 seconds.
    Calculating affinities...
    Calculated affinities in 0.11 seconds.
  Calculated graph and diffusion operator in 3.77 seconds.
  Calculating landmark operator...
    Calculating SVD...
    Calculated SVD in 1.23 seconds.
    Calculating KMeans...
    Calculated KMeans in 8.27 seconds.
  Calculated landmark operator in 11.47 seconds.
  Calculating diffusion potential...
  Calculated diffusion potential in 1.71 seconds.
  Calculating metric MDS...
  Calculated metric MDS in 4.85 seconds.
Calculated PHATE in 21.80 seconds.

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(Enterotypes_id = Enterotypes_id %>% as.character) %>%
  group_by(Enterotypes_id) %>%
  summarise(PHATE1=mean(PHATE1), PHATE2=mean(PHATE2)) -> enterotypes_phate_centroid

enterotypes_phate_centroid %>%
  arrange(PHATE1)

enterotypes_phate_centroid %>%
  arrange(PHATE2)

NA

PHATE plot

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(branch ="Clostridiales DMM types") %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(18,14,16,17,7), "Prevotella DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(11,15,6,8,10,3,4,2), "Bacteroides DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(13), "Akkermansia DMM types",branch)) %>%
  #filter(Enterotypes_id %in% c(11,15,6,8,10,3,4,2)) %>%
  ggplot() + geom_point(aes(x=PHATE1, y=PHATE2, col=branch), size=1, alpha=0.5) +
  scale_color_brewer("main taxa\nDMM partitions",type="qual") + theme_classic() +
  ggrepel::geom_label_repel(data = enterotypes_phate_centroid, aes(x=PHATE1, y=PHATE2, label=Enterotypes_id)) + cowplot::theme_cowplot() -> fig3C #+
  #facet_wrap(~branch)
  
  #+ facet_wrap(~Enterotypes_id%>%as.character)

#save(genus_phate, file="genus_phate.rda")

fig3C

ggsave("AGP_branches_DMM_types.pdf")

Saving 7.26 x 4.49 in image

to put in B&W

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(branch ="Clostridiales DMM types") %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(18,14,16,17,7), "Prevotella DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(11,15,6,8,10,3,4,2), "Bacteroides DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(13), "Akkermansia DMM types",branch)) %>%
  #filter(Enterotypes_id %in% c(11,15,6,8,10,3,4,2)) %>%
  ggplot() + geom_point(aes(x=PHATE1, y=PHATE2, col=branch, shape=branch), size=1, alpha=0.5) +
  scale_color_grey("main taxa\nDMM partitions") + scale_shape("main taxa\nDMM partitions") + theme_classic() +
  ggrepel::geom_label_repel(data = enterotypes_phate_centroid, aes(x=PHATE1, y=PHATE2, label=Enterotypes_id)) + cowplot::theme_cowplot()

NA
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genus_phate_clostridiales = 
  genus_prop %>%
  t() %>%
  merge(enterotypes %>% filter(set != "outliers", value>0.80) %>% select(sample_name,Enterotypes_id), by.x="row.names", by.y="sample_name") %>% 
  mutate(branch ="Clostridiales DMM types") %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(18,14,16,17,7), "Prevotella DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(11,15,6,8,10,3,4,2), "Bacteroides DMM types",branch)) %>%
  filter(branch == "Clostridiales DMM types" ) %>%
  select(-Enterotypes_id, -branch) %>%
  tibble::column_to_rownames("Row.names") %>%
  phateR::phate(gamma=0, t=60, seed=666)

Calculating PHATE...
  Running PHATE on 3843 observations and 30 variables.
  Calculating graph and diffusion operator...
    Calculating KNN search...
    Calculated KNN search in 0.54 seconds.
    Calculating affinities...
    Calculated affinities in 0.03 seconds.
  Calculated graph and diffusion operator in 0.58 seconds.
  Calculating landmark operator...
    Calculating SVD...
    Calculated SVD in 0.59 seconds.
    Calculating KMeans...
    Calculated KMeans in 5.16 seconds.
  Calculated landmark operator in 7.54 seconds.
  Calculating diffusion potential...
  Calculated diffusion potential in 1.56 seconds.
  Calculating metric MDS...
  Calculated metric MDS in 4.56 seconds.
Calculated PHATE in 14.24 seconds.

genus_phate_clostridiales$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(Enterotypes_id = Enterotypes_id %>% as.character) %>%
  group_by(Enterotypes_id) %>%
  summarise(PHATE1=mean(PHATE1), PHATE2=mean(PHATE2)) -> enterotypes_phate_centroid

enterotypes_phate_centroid %>%
  arrange(PHATE1)

enterotypes_phate_centroid %>%
  arrange(PHATE2)

genus_phate_clostridiales$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(branch ="Clostridiales DMM types") %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(18,14,16,17,7), "Prevotella DMM types",branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(11,15,6,8,10,3,4,2), "Bacteroides DMM types",branch)) %>%
  #filter(Enterotypes_id %in% c(11,15,6,8,10,3,4,2)) %>%
  ggplot() + geom_point(aes(x=PHATE1, y=PHATE2, col=Enterotypes_id%>%as.character), size=1, alpha=0.5) +
  scale_color_brewer("Clostridiales-Akkermansia\nDMM types",type="qual") + theme_classic() +
  ggrepel::geom_label_repel(data = enterotypes_phate_centroid, aes(x=PHATE1, y=PHATE2, label=Enterotypes_id)) #+

  #facet_wrap(~branch)
  
  #+ facet_wrap(~Enterotypes_id%>%as.character)

#save(genus_phate, file="genus_phate.rda")

compute bacteroides prevotella ratio

genus_bact_prev_ratio =
genus %>% 
  #select(sample_select) %>%
  t %>% as.data.frame() %>% 
  tibble::rownames_to_column("sample_id") %>%
  select(sample_id, "k__Bacteria;p__Bacteroidetes;c__Bacteroidia;o__Bacteroidales;f__Bacteroidaceae;g__Bacteroides","k__Bacteria;p__Bacteroidetes;c__Bacteroidia;o__Bacteroidales;f__Prevotellaceae;g__Prevotella") %>%
  #head() %>%
  dplyr::rename(Bacteroides=2, Prevotella=3) %>%
  mutate(prev_bact_ratio = log2((Prevotella+1)/(Bacteroides+1))) %>%
  select(sample_id,prev_bact_ratio)

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  #merge(as.data.frame(genus_mada), by.x="Row.names", by.y="row.names") %>%
  merge(genus_bact_prev_ratio, by.x="Row.names", by.y="sample_id") %>%
  ggplot() + geom_point(aes(x=PHATE1, y=PHATE2, col=prev_bact_ratio), size=1, alpha=0.5) +
  scale_color_viridis_c("Prevotella/\nBacteroides\nratio (log2)",option="cividis") + 
  cowplot::theme_cowplot() -> fig3D
fig3D
ggsave("genus_phate_prevotella_ratio.pdf")

Saving 7.26 x 4.49 in image

import shannon

shannon_path = system.file("data-raw/qiime/generated-files-20190512/alpha/shannon.qza", package = "gutzilla")

shannon = qiime2R::read_qza(shannon_path)$data %>% as.data.frame

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  mutate(Enterotypes_id = Enterotypes_id %>% as.character) %>%
  group_by(Enterotypes_id) %>%
  summarise(PHATE1=mean(PHATE1), PHATE2=mean(PHATE2)) -> enterotypes_phate_centroid

genus_phate$embedding %>%
  merge(enterotypes, by.x="row.names", by.y="sample_name") %>%
  #merge(as.data.frame(genus_mada), by.x="Row.names", by.y="row.names") %>%
  merge(genus_bact_prev_ratio, by.x="Row.names", by.y="sample_id") %>%
  merge(shannon, by.x="Row.names", by.y="row.names") %>%
  ggplot() + geom_point(aes(x=PHATE1, y=PHATE2, col=shannon), size=1, alpha=0.5) +
  scale_color_viridis_c("Shannon", option="cividis") +
  #ggrepel::geom_label_repel(data = enterotypes_phate_centroid, aes(x=PHATE1, y=PHATE2, label=Enterotypes_id)) +
  cowplot::theme_cowplot() -> fig3B
  
fig3B
ggsave("genus_phate_shannon.pdf")

Saving 7.26 x 4.49 in image

export fig data

save(fig3B, file="figures/fig3B_agp_shannon_PHATE.rda")
save(fig3D, file="figures/fig3D_agp_prevotella_bacteroides_PHATE.rda")
save(fig3C, file="figures/fig3C_agp_branches_PHATE.rda")

figure 3 heatmap apg/curated and branches

add DIET INDEX

exploration

explore bacteroides and prevotella path

```r

genus_phate$embedding %>%
  merge(enterotypes, by.x=\row.names\, by.y=\sample_name\) %>%
  #merge(as.data.frame(genus_mada), by.x=\Row.names\, by.y=\row.names\) %>%
  merge(genus_bact_prev_ratio, by.x=\Row.names\, by.y=\sample_id\) %>%
  merge(shannon, by.x=\Row.names\, by.y=\row.names\) %>%
   mutate(branch =\Clostridiales DMM types\) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(18,14,16,17,7), \Prevotella DMM types\,branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(11,15,6,8,10,3,4,2), \Bacteroides DMM types\,branch)) %>%
  mutate(branch = ifelse(Enterotypes_id %in% c(13), \Akkermansia DMM types\,branch)) %>%
  #filter(PHATE1<0) %>%
  mutate(PHATE1=PHATE1%>%rank()) %>%
  #filter(branch==\Prevotella DMM types\) %>%
  ggplot() + geom_density(aes(x=PHATE1, col=Enterotypes_id%>%as.character))# + 

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" />

<!-- rnb-plot-end -->

<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuYGBgclxuICAjZmFjZXRfd3JhcCh+YnJhbmNoLCBzY2FsZT1cXGZyZWVcXCkgKyBzY2FsZV9maWxsX2JyZXdlcih0eXBlPVxccXVhbFxcLCBwYWxldHRlID0gMilcblxuXG5gYGBcbmBgYCJ9 -->

```r
```r
  #facet_wrap(~branch, scale=\free\) + scale_fill_brewer(type=\qual\, palette = 2)

<!-- rnb-source-end -->

<!-- rnb-chunk-end -->


<!-- rnb-text-begin -->






<!-- rnb-text-end -->


<!-- rnb-chunk-begin -->


<!-- rnb-source-begin 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 -->

```r
```r


genus_phate$embedding %>%
  merge(enterotypes, by.x=\row.names\, by.y=\sample_name\) %>%
  #merge(as.data.frame(genus_mada), by.x=\Row.names\, by.y=\row.names\) %>%
  merge(genus_bact_prev_ratio, by.x=\Row.names\, by.y=\sample_id\) %>%
  merge(shannon, by.x=\Row.names\, by.y=\row.names\) %>%
  mutate(PHATE1=PHATE1%>%rank()) %>%
  mutate(bin = cut(PHATE1, seq(min(PHATE1), max(PHATE1) + 150, 150), right = FALSE)) %>% 
  group_by(bin) %>%
  summarise(prev_bact_ratio=median(prev_bact_ratio), shannon=median(shannon)) -> phate_richness_bins

<!-- rnb-source-end -->

<!-- rnb-output-begin eyJkYXRhIjoiYHN1bW1hcmlzZSgpYCB1bmdyb3VwaW5nIG91dHB1dCAob3ZlcnJpZGUgd2l0aCBgLmdyb3Vwc2AgYXJndW1lbnQpXG4ifQ== -->

summarise() ungrouping output (override with .groups argument)

<!-- rnb-output-end -->

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```r
```r
genus_phate_enterotypes_plot=
genus_phate$embedding %>%
  merge(enterotypes, by.x=\row.names\, by.y=\sample_name\) %>%
  #merge(as.data.frame(genus_mada), by.x=\Row.names\, by.y=\row.names\) %>%
  merge(genus_bact_prev_ratio, by.x=\Row.names\, by.y=\sample_id\) %>%
  merge(shannon, by.x=\Row.names\, by.y=\row.names\) %>%
  mutate(PHATE1=PHATE1%>%rank()) %>%
  mutate(bin = cut(PHATE1, seq(min(PHATE1), max(PHATE1) + 150, 150), right = FALSE)) %>% 
  #group_by(bin) %>%
  ggplot() + geom_bar(aes(x=bin,fill=Enterotypes_id%>%as.character), position=position_fill(), width=1) + 
  theme_classic()+
  theme(axis.text.x = element_blank())
  
  genus_phate_enterotypes_plot

<!-- rnb-source-end -->

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<img 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" />

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<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuYGBgclxuICBnZ3NhdmUoZ2VudXNfcGhhdGVfZW50ZXJvdHlwZXNfcGxvdCwgZmlsZT1cXGdlbnVzX3BoYXRlX2VudGVyb3R5cGVzX3Bsb3QucGRmXFwsIGg9NSwgdz0xMilcblxuXG5gYGBcbmBgYCJ9 -->

```r
```r
  ggsave(genus_phate_enterotypes_plot, file=\genus_phate_enterotypes_plot.pdf\, h=5, w=12)

<!-- rnb-source-end -->

<!-- rnb-chunk-end -->


<!-- rnb-text-begin -->






<!-- rnb-text-end -->


<!-- rnb-chunk-begin -->


<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuYGBgclxuXG5waGF0ZV9yaWNobmVzc19wbG90PVxucGhhdGVfcmljaG5lc3NfYmlucyAlPiUgXG4gIHJlc2hhcGUyOjptZWx0KGlkLnZhcnM9YyhcXGJpblxcKSkgJT4lXG4gIGdyb3VwX2J5KHZhcmlhYmxlKSAlPiVcbiAgbXV0YXRlKHZhbHVlPXNjYWxlKHZhbHVlKSkgJT4lXG4gIGdncGxvdCgpICsgZ2VvbV90aWxlKGFlcyh4PWJpbix5PXZhcmlhYmxlLCBmaWxsPXZhbHVlKSkgKyBcbiAgc2NhbGVfZmlsbF92aXJpZGlzX2MoKSArXG4gIHRoZW1lX2NsYXNzaWMoKStcbiAgdGhlbWUoYXhpcy50ZXh0LnggPSBlbGVtZW50X2JsYW5rKCkpXG5cblxucGhhdGVfcmljaG5lc3NfcGxvdFxuYGBgXG5gYGAifQ== -->

```r
```r

phate_richness_plot=
phate_richness_bins %>% 
  reshape2::melt(id.vars=c(\bin\)) %>%
  group_by(variable) %>%
  mutate(value=scale(value)) %>%
  ggplot() + geom_tile(aes(x=bin,y=variable, fill=value)) + 
  scale_fill_viridis_c() +
  theme_classic()+
  theme(axis.text.x = element_blank())


phate_richness_plot

<!-- rnb-source-end -->

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<img 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" />

<!-- rnb-plot-end -->

<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuYGBgclxuZ2dzYXZlKHBoYXRlX3JpY2huZXNzX3Bsb3QsZmlsZT1cXHBoYXRlX3JpY2huZXNzX3Bsb3QucGRmXFwsIGg9Mix3PTEwKVxuXG5cblxuYGBgXG5gYGAifQ== -->

```r
```r
ggsave(phate_richness_plot,file=\phate_richness_plot.pdf\, h=2,w=10)

<!-- rnb-source-end -->

<!-- rnb-chunk-end -->


<!-- rnb-text-begin -->


compare PHATE with genus

<!-- rnb-text-end -->


<!-- rnb-chunk-begin -->


<!-- rnb-source-begin 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 -->

```r
```r

genus_path = system.file(\data-raw/qiime/generated-files-20190512/taxa/genus.qza\, package = \agp\)

genus = qiime2R::read_qza(genus_path)$data %>% as.data.frame %>% tibble::rownames_to_column(\taxa\)  %>% as_tibble()



genus_alr_ranked=
genus %>%
  tibble::column_to_rownames(\taxa\) %>%
  SpiecEasi::alr(divcomp=1,removeDivComp=FALSE) %>% as.data.frame() %>%
  tibble::rownames_to_column(\taxa\) %>%
  reshape2::melt() %>%
  group_by(variable) %>%
  mutate(value=rank(value)) 

<!-- rnb-source-end -->

<!-- rnb-output-begin eyJkYXRhIjoiVXNpbmcgdGF4YSBhcyBpZCB2YXJpYWJsZXNcbiJ9 -->

Using taxa as id variables

<!-- rnb-output-end -->

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```r
```r
genus_alr_ranked =
  genus_alr_ranked %>%
  filter(taxa %in% names(top_genus_mass))

genus_phate_plot=
genus_phate$embedding %>%
  merge(enterotypes, by.x=\row.names\, by.y=\sample_name\) %>%
  mutate(PHATE1=PHATE1%>%rank()) %>%
  mutate(bin = cut(PHATE1, seq(min(PHATE1), max(PHATE1) + 150, 150), right = FALSE)) %>% 
  merge(genus_alr_ranked, by.x=\Row.names\, by.y=\variable\) %>%
  group_by(bin,taxa) %>%
  summarise(value=mean(value.y)) %>%
  mutate(taxa = factor(taxa, levels=names(top_genus_mass))) %>%
  ggplot() + geom_tile(aes(x=bin,y=taxa,fill=(value))) + 
  scale_fill_viridis_c() +
  theme_classic()+
  theme(axis.text.x = element_blank())

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summarise() regrouping output by ‘bin’ (override with .groups argument)

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```r
```r
ggsave(genus_phate_plot, file=\genus_phate_plot.pdf\, w=15,h=5)

genus_phate_plot

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" />

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combine plot



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<!-- rnb-source-begin eyJkYXRhIjoiYGBgclxuYGBgclxuXG5jb3dwbG90OjpwbG90X2dyaWQoXG5nZW51c19waGF0ZV9lbnRlcm90eXBlc19wbG90LFxuXG5waGF0ZV9yaWNobmVzc19wbG90LFxuXG5nZW51c19waGF0ZV9wbG90LCBuY29sPTEsIGFsaWduID0gXFx2XFwsIHJlbF9oZWlnaHRzID0gYyg1LDEsNSkpXG5cblxuZ2dzYXZlKGZpbGU9XFxQSEFURV9jb21iaW5lZF9wbG90LnBkZlxcKVxuXG5gYGBcbmBgYCJ9 -->

```r
```r

cowplot::plot_grid(
genus_phate_enterotypes_plot,

phate_richness_plot,

genus_phate_plot, ncol=1, align = \v\, rel_heights = c(5,1,5))


ggsave(file=\PHATE_combined_plot.pdf\)

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<!-- rnb-chunk-end -->


<!-- rnb-text-begin -->




## time series within PHATE coord



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<!-- rnb-text-begin -->





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```r


system.file("data-raw/ls_time_series/LS_AGP_local_partitions.tsv", package = "gutzilla") %>% readr::read_tsv() %>% pull(host_subject_id) %>% unique -> ls_subject_id

metadata=read.csv2(system.file("data-raw/Metadata_10317_20191022-112414_curatedv4_VSv1.csv", package = "gutzilla"), stringsAsFactors = FALSE) %>% mutate_all(na_if,"")


genus_phate$embedding %>%
  merge(enterotypes,., by.y="row.names", by.x="sample_name") %>%
  merge(.,metadata %>% 
  filter(SAMPLE_TYPE == "Stool") %>%
  select(HOST_SUBJECT_ID,SAMPLE_NAME, COLLECTION_TIMESTAMP) %>%
  mutate(COLLECTION_TIMESTAMP = COLLECTION_TIMESTAMP %>% lubridate::as_datetime()), 
  by.x="sample_name", by.y="SAMPLE_NAME") -> genus_phate_time_series_df
  

myPalette <- colorRampPalette(rev(RColorBrewer::brewer.pal(11, "Spectral")))





genus_phate_time_series_df %>%
  #mutate(COLLECTION_TIMESTAMP = factor(COLLECTION_TIMESTAMP, labels = dates, ordered = TRUE)) %>%
  ggplot() + 
  geom_point(aes(x=PHATE1, y=PHATE2), alpha=0.1, size=0.5, col="grey") +
  geom_path(data=genus_phate_time_series_df %>% filter(HOST_SUBJECT_ID %in% ls_subject_id) , aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) +
    geom_point(data=genus_phate_time_series_df %>% filter(HOST_SUBJECT_ID %in% ls_subject_id) , aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) +
  scale_color_datetime(name = "Time (Years)",low = "red", high = "blue") +
    cowplot::theme_cowplot()



 
#   genus_phate_time_series_df %>%
#   arrange(COLLECTION_TIMESTAMP) %>%
#     mutate(time_idx = row_number()) %>%
#   #mutate(COLLECTION_TIMESTAMP = factor(COLLECTION_TIMESTAMP, labels = dates, ordered = TRUE)) %>%
#   ggplot() +
#     geom_path(data=genus_phate_time_series_df %>% 
#                 filter(HOST_SUBJECT_ID %in% ls_subject_id) %>% 
#                 arrange(COLLECTION_TIMESTAMP) %>% 
#                 mutate(time_idx = row_number()) , aes(y=PHATE2, x=PHATE1, col=COLLECTION_TIMESTAMP)) +
# geom_point(data=genus_phate_time_series_df %>% 
#              filter(HOST_SUBJECT_ID %in% ls_subject_id) %>% 
#              arrange(COLLECTION_TIMESTAMP) %>%
#              mutate(time_idx = row_number()) , aes(y=PHATE2, x=PHATE1, col=COLLECTION_TIMESTAMP))

genus_phate_time_series_df %>%
  filter(!(HOST_SUBJECT_ID%in%ls_subject_id)) %>%
  group_by(HOST_SUBJECT_ID) %>%
  filter(any(Enterotypes_id %in% c(15))) %>%
  summarise(n=n()) %>%
  top_n(1,n) %>% pull(HOST_SUBJECT_ID) -> select_other_subject




genus_phate_time_series_df %>%
  filter(HOST_SUBJECT_ID %in% select_other_subject[1]) %>%
  ggplot() + 
   geom_point(aes(x=PHATE1, y=PHATE2), alpha=0.1, size=0.5, col="grey", data=genus_phate_time_series_df) +
  geom_path(aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) + 
  geom_point(aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) + 
    scale_color_datetime(name = "Time",low = "red", high = "blue") +
    cowplot::theme_cowplot()

genus_phate_time_series_df %>%
  filter(!(HOST_SUBJECT_ID%in%ls_subject_id)) %>%
  group_by(HOST_SUBJECT_ID) %>%
  filter(any(Enterotypes_id %in% c(18))) %>%
  summarise(n=n()) %>%
  top_n(1,n) %>% pull(HOST_SUBJECT_ID) -> select_other_subject_prevotella


genus_phate_time_series_df %>%
  filter(HOST_SUBJECT_ID %in% select_other_subject_prevotella[1]) %>%
  ggplot() + 
   geom_point(aes(x=PHATE1, y=PHATE2), alpha=0.1, size=0.5, col="grey", data=genus_phate_time_series_df) +
  geom_path(aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) + 
  geom_point(aes(x=PHATE1, y=PHATE2, col=COLLECTION_TIMESTAMP)) + 
    scale_color_datetime(name = "Time",low = "red", high = "blue") +
    cowplot::theme_cowplot()

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