From 0806dacb44cac8872ded00d6ebbcfc8913804005 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Hadrien=20Gourl=C3=A9?= Date: Thu, 10 May 2018 12:26:27 +0200 Subject: [PATCH 1/4] initial ubiome commit install necessary packages build data frame from the api and public data info try to import json --- ubiome.ipynb | 316 +++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 316 insertions(+) create mode 100644 ubiome.ipynb diff --git a/ubiome.ipynb b/ubiome.ipynb new file mode 100644 index 0000000..e0e3c3b --- /dev/null +++ b/ubiome.ipynb @@ -0,0 +1,316 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Ubiome data analysis - draft\n", + "\n", + "## Introduction\n", + "\n", + "this notebook is being written as part of the Mozilla Global Sprint 2018. \n", + "It aims at providing to openhumans members with a walkthrough on how to analyse their microbiome data from ubiome.\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Data import\n", + "\n", + "First, we load and install the necessary packages (be patient!):" + ] + }, + { + "cell_type": "code", + "execution_count": 138, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Bioconductor version 3.6 (BiocInstaller 1.28.0), ?biocLite for help\n", + "A new version of Bioconductor is available after installing the most recent\n", + " version of R; see http://bioconductor.org/install\n", + "BioC_mirror: https://bioconductor.org\n", + "Using Bioconductor 3.6 (BiocInstaller 1.28.0), R 3.4.1 (2017-06-30).\n", + "Installing package(s) ‘phyloseq’\n", + "Updating HTML index of packages in '.Library'\n", + "Making 'packages.html' ... done\n", + "Old packages: 'bindrcpp', 'bit64', 'config', 'DBI', 'dbplyr', 'ddalpha',\n", + " 'digest', 'forecast', 'foreign', 'git2r', 'hms', 'htmlwidgets', 'httpuv',\n", + " 'kernlab', 'lattice', 'lmtest', 'lubridate', 'MASS', 'Matrix', 'nlme',\n", + " 'pbdZMQ', 'pillar', 'plogr', 'prodlim', 'psych', 'randomForest', 'Rcpp',\n", + " 'RcppArmadillo', 'RCurl', 'readxl', 'repr', 'rmarkdown', 'robustbase',\n", + " 'RSQLite', 'selectr', 'sfsmisc', 'sourcetools', 'sparklyr', 'stringi',\n", + " 'survival', 'tidyverse', 'timeDate', 'tseries', 'viridisLite', 'withr',\n", + " 'xml2', 'yaml'\n" + ] + } + ], + "source": [ + "source('http://bioconductor.org/biocLite.R')\n", + "biocLite('phyloseq')" + ] + }, + { + "cell_type": "code", + "execution_count": 113, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Updating HTML index of packages in '.Library'\n", + "Making 'packages.html' ... done\n", + "Bioconductor version 3.6 (BiocInstaller 1.28.0), ?biocLite for help\n", + "A new version of Bioconductor is available after installing the most recent\n", + " version of R; see http://bioconductor.org/install\n", + "BioC_mirror: https://bioconductor.org\n", + "Using Bioconductor 3.6 (BiocInstaller 1.28.0), R 3.4.1 (2017-06-30).\n", + "Installing package(s) ‘phyloseq’\n", + "also installing the dependencies ‘zlibbioc’, ‘rhdf5’, ‘S4Vectors’, ‘IRanges’, ‘XVector’, ‘permute’, ‘mgcv’, ‘ade4’, ‘ape’, ‘Biobase’, ‘BiocGenerics’, ‘biomformat’, ‘Biostrings’, ‘cluster’, ‘data.table’, ‘igraph’, ‘multtest’, ‘vegan’\n", + "\n", + "Updating HTML index of packages in '.Library'\n", + "Making 'packages.html' ... done\n", + "Old packages: 'bindrcpp', 'bit64', 'config', 'DBI', 'dbplyr', 'ddalpha',\n", + " 'digest', 'forecast', 'foreign', 'git2r', 'hms', 'htmlwidgets', 'httpuv',\n", + " 'kernlab', 'lattice', 'lmtest', 'lubridate', 'MASS', 'Matrix', 'nlme',\n", + " 'pbdZMQ', 'pillar', 'plogr', 'prodlim', 'psych', 'randomForest', 'Rcpp',\n", + " 'RcppArmadillo', 'RCurl', 'readxl', 'repr', 'rmarkdown', 'robustbase',\n", + " 'RSQLite', 'selectr', 'sfsmisc', 'sourcetools', 'sparklyr', 'stringi',\n", + " 'survival', 'tidyverse', 'timeDate', 'tseries', 'viridisLite', 'withr',\n", + " 'xml2', 'yaml'\n" + ] + } + ], + "source": [ + "library(httr)\n", + "library(tidyverse)\n", + "library(phyloseq)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "I do not have my own Ubiome data, so I'll import a public dataset using the public API" + ] + }, + { + "cell_type": "code", + "execution_count": 110, + "metadata": {}, + "outputs": [], + "source": [ + "url <- paste0(\"https://www.openhumans.org/api/\",\n", + " \"public-data/?source=direct-sharing-132\")\n", + "resp <- GET(url)\n", + "results <- content(resp, as = \"parsed\", type = \"application/json\")$results\n", + "results <- bind_rows(lapply(results, as.data.frame.list, stringsAsFactors=FALSE))" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "The Ubiome data is apparently available as a raw fastq file or a json result file \n", + "We'll first explore the content of the json files. \n", + "We are not interested in the names of the users, so let's \"anonimize\" our dataframe first by dropping some columns" + ] + }, + { + "cell_type": "code", + "execution_count": 111, + "metadata": {}, + "outputs": [], + "source": [ + "jsons <- filter(results, metadata.tags..json. == 'json') %>%\n", + " select(-metadata.tags..fastq., -user.name, -user.username,\n", + " -metadata.tags..uBiome., -metadata.tags..16S.,\n", + " -source, -metadata.description, -metadata.tags..json.)" + ] + }, + { + "cell_type": "code", + "execution_count": 112, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
idbasenamecreateddownload_urluser.idmetadata.user_notes
37844 taxonomy.json 2018-04-10T19:21:12.089631Z https://www.openhumans.org/data-management/datafile-download/37844/ 08868768 NA
37870 taxonomy-1.json 2018-04-10T19:21:42.698608Z https://www.openhumans.org/data-management/datafile-download/37870/ 35269294 GENITAL (F)\r\n", + "Sampled on\r\n", + "12/03/2015\r\n", + "Kit No. 407-018-198 Registered on 12/03/2015
37872 taxonomy-2.json 2018-04-10T19:21:42.709555Z https://www.openhumans.org/data-management/datafile-download/37872/ 35269294 GENITAL (F)\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016
37874 taxonomy-3.json 2018-04-10T19:21:42.723138Z https://www.openhumans.org/data-management/datafile-download/37874/ 35269294 SKIN\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016 EXPLORE SAMPLE
37876 taxonomy-4.json 2018-04-10T19:21:42.734174Z https://www.openhumans.org/data-management/datafile-download/37876/ 35269294 MOUTH SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016
37878 taxonomy-5.json 2018-04-10T19:21:42.746854Z https://www.openhumans.org/data-management/datafile-download/37878/ 35269294 GUT SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016
\n" + ], + "text/latex": [ + "\\begin{tabular}{r|llllll}\n", + " id & basename & created & download\\_url & user.id & metadata.user\\_notes\\\\\n", + "\\hline\n", + "\t 37844 & taxonomy.json & 2018-04-10T19:21:12.089631Z & https://www.openhumans.org/data-management/datafile-download/37844/ & 08868768 & NA \\\\\n", + "\t 37870 & taxonomy-1.json & 2018-04-10T19:21:42.698608Z & https://www.openhumans.org/data-management/datafile-download/37870/ & 35269294 & GENITAL (F)\r\n", + "Sampled on\r\n", + "12/03/2015\r\n", + "Kit No. 407-018-198 Registered on 12/03/2015 \\\\\n", + "\t 37872 & taxonomy-2.json & 2018-04-10T19:21:42.709555Z & https://www.openhumans.org/data-management/datafile-download/37872/ & 35269294 & GENITAL (F)\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016 \\\\\n", + "\t 37874 & taxonomy-3.json & 2018-04-10T19:21:42.723138Z & https://www.openhumans.org/data-management/datafile-download/37874/ & 35269294 & SKIN\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016 EXPLORE SAMPLE\\\\\n", + "\t 37876 & taxonomy-4.json & 2018-04-10T19:21:42.734174Z & https://www.openhumans.org/data-management/datafile-download/37876/ & 35269294 & MOUTH SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016 \\\\\n", + "\t 37878 & taxonomy-5.json & 2018-04-10T19:21:42.746854Z & https://www.openhumans.org/data-management/datafile-download/37878/ & 35269294 & GUT SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016 \\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "id | basename | created | download_url | user.id | metadata.user_notes | \n", + "|---|---|---|---|---|---|\n", + "| 37844 | taxonomy.json | 2018-04-10T19:21:12.089631Z | https://www.openhumans.org/data-management/datafile-download/37844/ | 08868768 | NA | \n", + "| 37870 | taxonomy-1.json | 2018-04-10T19:21:42.698608Z | https://www.openhumans.org/data-management/datafile-download/37870/ | 35269294 | GENITAL (F)\r\n", + "Sampled on\r\n", + "12/03/2015\r\n", + "Kit No. 407-018-198 Registered on 12/03/2015 | \n", + "| 37872 | taxonomy-2.json | 2018-04-10T19:21:42.709555Z | https://www.openhumans.org/data-management/datafile-download/37872/ | 35269294 | GENITAL (F)\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016 | \n", + "| 37874 | taxonomy-3.json | 2018-04-10T19:21:42.723138Z | https://www.openhumans.org/data-management/datafile-download/37874/ | 35269294 | SKIN\r\n", + "Sampled on\r\n", + "5/09/2016\r\n", + "Kit No. 620-054-275 Registered on 5/10/2016 EXPLORE SAMPLE | \n", + "| 37876 | taxonomy-4.json | 2018-04-10T19:21:42.734174Z | https://www.openhumans.org/data-management/datafile-download/37876/ | 35269294 | MOUTH SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016 | \n", + "| 37878 | taxonomy-5.json | 2018-04-10T19:21:42.746854Z | https://www.openhumans.org/data-management/datafile-download/37878/ | 35269294 | GUT SET DATE\r\n", + "Kit No. 938-066-987 Registered on 7/31/2016 | \n", + "\n", + "\n" + ], + "text/plain": [ + " id basename created \n", + "1 37844 taxonomy.json 2018-04-10T19:21:12.089631Z\n", + "2 37870 taxonomy-1.json 2018-04-10T19:21:42.698608Z\n", + "3 37872 taxonomy-2.json 2018-04-10T19:21:42.709555Z\n", + "4 37874 taxonomy-3.json 2018-04-10T19:21:42.723138Z\n", + "5 37876 taxonomy-4.json 2018-04-10T19:21:42.734174Z\n", + "6 37878 taxonomy-5.json 2018-04-10T19:21:42.746854Z\n", + " download_url user.id \n", + "1 https://www.openhumans.org/data-management/datafile-download/37844/ 08868768\n", + "2 https://www.openhumans.org/data-management/datafile-download/37870/ 35269294\n", + "3 https://www.openhumans.org/data-management/datafile-download/37872/ 35269294\n", + "4 https://www.openhumans.org/data-management/datafile-download/37874/ 35269294\n", + "5 https://www.openhumans.org/data-management/datafile-download/37876/ 35269294\n", + "6 https://www.openhumans.org/data-management/datafile-download/37878/ 35269294\n", + " metadata.user_notes \n", + "1 NA \n", + "2 GENITAL (F)\\r\\nSampled on\\r\\n12/03/2015\\r\\nKit No. 407-018-198 Registered on 12/03/2015 \n", + "3 GENITAL (F)\\r\\nSampled on\\r\\n5/09/2016\\r\\nKit No. 620-054-275 Registered on 5/10/2016 \n", + "4 SKIN\\r\\nSampled on\\r\\n5/09/2016\\r\\nKit No. 620-054-275 Registered on 5/10/2016 EXPLORE SAMPLE\n", + "5 MOUTH SET DATE\\r\\nKit No. 938-066-987 Registered on 7/31/2016 \n", + "6 GUT SET DATE\\r\\nKit No. 938-066-987 Registered on 7/31/2016 " + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "head(jsons)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We download the first json file and try to import it" + ] + }, + { + "cell_type": "code", + "execution_count": 140, + "metadata": {}, + "outputs": [ + { + "ename": "ERROR", + "evalue": "Error in parse_con(txt, bigint_as_char): lexical error: invalid char in json text.\n { download_time_utc: \"2016-04-21T\n (right here) ------^\n\n", + "output_type": "error", + "traceback": [ + "Error in parse_con(txt, bigint_as_char): lexical error: invalid char in json text.\n { download_time_utc: \"2016-04-21T\n (right here) ------^\n\nTraceback:\n", + "1. jsonlite::fromJSON(\"test.json\")", + "2. fromJSON_string(txt = txt, simplifyVector = simplifyVector, simplifyDataFrame = simplifyDataFrame, \n . simplifyMatrix = simplifyMatrix, flatten = flatten, ...)", + "3. parseJSON(txt, bigint_as_char)", + "4. parse_con(txt, bigint_as_char)" + ] + } + ], + "source": [ + "download.file(jsons$download_url[1], destfile = \"test.json\")\n", + "jsonlite::fromJSON(\"test.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "metadata": { + "kernelspec": { + "display_name": "R", + "language": "R", + "name": "ir" + }, + "language_info": { + "codemirror_mode": "r", + "file_extension": ".r", + "mimetype": "text/x-r-source", + "name": "R", + "pygments_lexer": "r", + "version": "3.4.1" + } + }, + "nbformat": 4, + "nbformat_minor": 2 +} From d8a0769080fa210d94db1ab52e785569a54f210e Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Hadrien=20Gourl=C3=A9?= Date: Thu, 10 May 2018 16:49:34 +0200 Subject: [PATCH 2/4] fixed public data upload the notebook can now import the public data in (valid) json, tsv and csv --- ubiome.ipynb | 666 ++++++++++++++++++++++++++++++++++++++++++++------- 1 file changed, 584 insertions(+), 82 deletions(-) diff --git a/ubiome.ipynb b/ubiome.ipynb index e0e3c3b..c183b5e 100644 --- a/ubiome.ipynb +++ b/ubiome.ipynb @@ -24,73 +24,12 @@ }, { "cell_type": "code", - "execution_count": 138, + "execution_count": 150, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Bioconductor version 3.6 (BiocInstaller 1.28.0), ?biocLite for help\n", - "A new version of Bioconductor is available after installing the most recent\n", - " version of R; see http://bioconductor.org/install\n", - "BioC_mirror: https://bioconductor.org\n", - "Using Bioconductor 3.6 (BiocInstaller 1.28.0), R 3.4.1 (2017-06-30).\n", - "Installing package(s) ‘phyloseq’\n", - "Updating HTML index of packages in '.Library'\n", - "Making 'packages.html' ... done\n", - "Old packages: 'bindrcpp', 'bit64', 'config', 'DBI', 'dbplyr', 'ddalpha',\n", - " 'digest', 'forecast', 'foreign', 'git2r', 'hms', 'htmlwidgets', 'httpuv',\n", - " 'kernlab', 'lattice', 'lmtest', 'lubridate', 'MASS', 'Matrix', 'nlme',\n", - " 'pbdZMQ', 'pillar', 'plogr', 'prodlim', 'psych', 'randomForest', 'Rcpp',\n", - " 'RcppArmadillo', 'RCurl', 'readxl', 'repr', 'rmarkdown', 'robustbase',\n", - " 'RSQLite', 'selectr', 'sfsmisc', 'sourcetools', 'sparklyr', 'stringi',\n", - " 'survival', 'tidyverse', 'timeDate', 'tseries', 'viridisLite', 'withr',\n", - " 'xml2', 'yaml'\n" - ] - } - ], - "source": [ - "source('http://bioconductor.org/biocLite.R')\n", - "biocLite('phyloseq')" - ] - }, - { - "cell_type": "code", - "execution_count": 113, - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Updating HTML index of packages in '.Library'\n", - "Making 'packages.html' ... done\n", - "Bioconductor version 3.6 (BiocInstaller 1.28.0), ?biocLite for help\n", - "A new version of Bioconductor is available after installing the most recent\n", - " version of R; see http://bioconductor.org/install\n", - "BioC_mirror: https://bioconductor.org\n", - "Using Bioconductor 3.6 (BiocInstaller 1.28.0), R 3.4.1 (2017-06-30).\n", - "Installing package(s) ‘phyloseq’\n", - "also installing the dependencies ‘zlibbioc’, ‘rhdf5’, ‘S4Vectors’, ‘IRanges’, ‘XVector’, ‘permute’, ‘mgcv’, ‘ade4’, ‘ape’, ‘Biobase’, ‘BiocGenerics’, ‘biomformat’, ‘Biostrings’, ‘cluster’, ‘data.table’, ‘igraph’, ‘multtest’, ‘vegan’\n", - "\n", - "Updating HTML index of packages in '.Library'\n", - "Making 'packages.html' ... done\n", - "Old packages: 'bindrcpp', 'bit64', 'config', 'DBI', 'dbplyr', 'ddalpha',\n", - " 'digest', 'forecast', 'foreign', 'git2r', 'hms', 'htmlwidgets', 'httpuv',\n", - " 'kernlab', 'lattice', 'lmtest', 'lubridate', 'MASS', 'Matrix', 'nlme',\n", - " 'pbdZMQ', 'pillar', 'plogr', 'prodlim', 'psych', 'randomForest', 'Rcpp',\n", - " 'RcppArmadillo', 'RCurl', 'readxl', 'repr', 'rmarkdown', 'robustbase',\n", - " 'RSQLite', 'selectr', 'sfsmisc', 'sourcetools', 'sparklyr', 'stringi',\n", - " 'survival', 'tidyverse', 'timeDate', 'tseries', 'viridisLite', 'withr',\n", - " 'xml2', 'yaml'\n" - ] - } - ], + "outputs": [], "source": [ "library(httr)\n", - "library(tidyverse)\n", - "library(phyloseq)" + "library(tidyverse)" ] }, { @@ -248,45 +187,608 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We download the first json file and try to import it" + "We download and read all the public data" + ] + }, + { + "cell_type": "code", + "execution_count": 244, + "metadata": {}, + "outputs": [], + "source": [ + "# this function assumes a valid data format and fails on unquoted json.\n", + "read_json_or_tbl_or_csv <- function(data_file) {\n", + " tryCatch({\n", + " jsonlite::fromJSON(data_file)$ubiome_bacteriacounts %>%\n", + " select(taxon, parent, tax_name, tax_rank, count, count_norm) %>%\n", + " mutate(id = strsplit(basename(data_file), \".\", fixed = TRUE)[[1]][1])\n", + " },\n", + " error = function(cond) {\n", + " paste(cond)\n", + " tryCatch({\n", + " tab <- read_table2(data_file) %>%\n", + " select(taxon, parent, tax_name, tax_rank, count, count_norm) %>%\n", + " mutate(id = strsplit(basename(data_file), \".\", fixed = TRUE)[[1]][1])\n", + " assertthat::assert_that(ncol(tab) > 1)\n", + " return(tab)\n", + " },\n", + " error = function(bla) {\n", + " paste(bla)\n", + " csv <- read_csv(data_file) %>%\n", + " select(taxon, parent, tax_name, tax_rank, count, count_norm) %>%\n", + " mutate(id = strsplit(basename(data_file), \".\", fixed = TRUE)[[1]][1])\n", + " return(csv)\n", + " })\n", + " } \n", + " )}" ] }, { "cell_type": "code", - "execution_count": 140, + "execution_count": 210, "metadata": {}, "outputs": [ { - "ename": "ERROR", - "evalue": "Error in parse_con(txt, bigint_as_char): lexical error: invalid char in json text.\n { download_time_utc: \"2016-04-21T\n (right here) ------^\n\n", - "output_type": "error", - "traceback": [ - "Error in parse_con(txt, bigint_as_char): lexical error: invalid char in json text.\n { download_time_utc: \"2016-04-21T\n (right here) ------^\n\nTraceback:\n", - "1. jsonlite::fromJSON(\"test.json\")", - "2. fromJSON_string(txt = txt, simplifyVector = simplifyVector, simplifyDataFrame = simplifyDataFrame, \n . simplifyMatrix = simplifyMatrix, flatten = flatten, ...)", - "3. parseJSON(txt, bigint_as_char)", - "4. 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A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/37852.json' file 2 11 6 columns 7 columns 'data/37852.json' row 3 14 6 columns 7 columns 'data/37852.json' col 4 15 6 columns 7 columns 'data/37852.json' expected 5 16 6 columns 7 columns 'data/37852.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“7 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 8 6 columns 7 columns 'data/37870.json' file 2 9 6 columns 7 columns 'data/37870.json' row 3 12 6 columns 7 columns 'data/37870.json' col 4 13 6 columns 7 columns 'data/37870.json' expected 5 15 6 columns 8 columns 'data/37870.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“9 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 3 6 columns 7 columns 'data/37872.json' file 2 6 6 columns 7 columns 'data/37872.json' row 3 9 6 columns 7 columns 'data/37872.json' col 4 10 6 columns 8 columns 'data/37872.json' expected 5 13 6 columns 7 columns 'data/37872.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“16 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 3 6 columns 8 columns 'data/37874.json' file 2 4 6 columns 7 columns 'data/37874.json' row 3 7 6 columns 8 columns 'data/37874.json' col 4 19 6 columns 8 columns 'data/37874.json' expected 5 20 6 columns 8 columns 'data/37874.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“103 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 8 6 columns 7 columns 'data/37876.json' file 2 9 6 columns 7 columns 'data/37876.json' row 3 10 6 columns 7 columns 'data/37876.json' col 4 12 6 columns 7 columns 'data/37876.json' expected 5 16 6 columns 7 columns 'data/37876.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“78 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/37878.json' file 2 6 6 columns 7 columns 'data/37878.json' row 3 18 6 columns 7 columns 'data/37878.json' col 4 20 6 columns 7 columns 'data/37878.json' expected 5 23 6 columns 7 columns 'data/37878.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“73 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/37880.json' file 2 6 6 columns 7 columns 'data/37880.json' row 3 19 6 columns 7 columns 'data/37880.json' col 4 22 6 columns 7 columns 'data/37880.json' expected 5 24 6 columns 7 columns 'data/37880.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“87 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 7 6 columns 7 columns 'data/37882.json' file 2 8 6 columns 7 columns 'data/37882.json' row 3 9 6 columns 7 columns 'data/37882.json' col 4 11 6 columns 7 columns 'data/37882.json' expected 5 20 6 columns 7 columns 'data/37882.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“24 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/37884.json' file 2 6 6 columns 7 columns 'data/37884.json' row 3 9 6 columns 7 columns 'data/37884.json' col 4 19 6 columns 7 columns 'data/37884.json' expected 5 20 6 columns 7 columns 'data/37884.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " `tax_name,tax_rank,count,count_norm,taxon,parent` = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“70 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 11 1 columns 2 columns 'data/37902.json' file 2 14 1 columns 2 columns 'data/37902.json' row 3 15 1 columns 2 columns 'data/37902.json' col 4 16 1 columns 2 columns 'data/37902.json' expected 5 17 1 columns 2 columns 'data/37902.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_integer(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Parsed with column specification:\n", + "cols(\n", + " `tax_name,tax_rank,count,count_norm,taxon,parent` = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“124 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 13 1 columns 2 columns 'data/37904.json' file 2 16 1 columns 2 columns 'data/37904.json' row 3 18 1 columns 2 columns 'data/37904.json' col 4 21 1 columns 2 columns 'data/37904.json' expected 5 22 1 columns 2 columns 'data/37904.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_integer(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Parsed with column specification:\n", + "cols(\n", + " `tax_name,tax_rank,count,count_norm,taxon,parent` = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“79 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 10 1 columns 3 columns 'data/37906.json' file 2 11 1 columns 2 columns 'data/37906.json' row 3 16 1 columns 2 columns 'data/37906.json' col 4 27 1 columns 2 columns 'data/37906.json' expected 5 30 1 columns 5 columns 'data/37906.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_integer(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Parsed with column specification:\n", + "cols(\n", + " `tax_name,tax_rank,count,count_norm,taxon,parent` = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“117 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 6 1 columns 2 columns 'data/37908.json' file 2 10 1 columns 2 columns 'data/37908.json' row 3 13 1 columns 2 columns 'data/37908.json' col 4 14 1 columns 2 columns 'data/37908.json' expected 5 15 1 columns 2 columns 'data/37908.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_integer(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“92 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 11 6 columns 7 columns 'data/37914.json' file 2 12 6 columns 7 columns 'data/37914.json' row 3 13 6 columns 7 columns 'data/37914.json' col 4 17 6 columns 7 columns 'data/37914.json' expected 5 24 6 columns 7 columns 'data/37914.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " `tax_name,tax_rank,count,count_norm,taxon,parent` = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“96 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 10 1 columns 2 columns 'data/37922.json' file 2 11 1 columns 2 columns 'data/37922.json' row 3 12 1 columns 2 columns 'data/37922.json' col 4 13 1 columns 2 columns 'data/37922.json' expected 5 17 1 columns 2 columns 'data/37922.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_integer(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“76 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 9 6 columns 7 columns 'data/37944.json' file 2 12 6 columns 7 columns 'data/37944.json' row 3 13 6 columns 7 columns 'data/37944.json' col 4 14 6 columns 7 columns 'data/37944.json' expected 5 19 6 columns 7 columns 'data/37944.json'\n", + "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", + "See problems(...) for more details.\n", + "”" ] } ], "source": [ - "download.file(jsons$download_url[1], destfile = \"test.json\")\n", - "jsonlite::fromJSON(\"test.json\")" + "data_path <- dir(\"data\", pattern = '.json', full.names = TRUE)\n", + "full_data <- map(data_path, read_json_or_tbl_or_csv)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 246, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "public_data_table <- map(full_data, mutate_all, as.character) %>%\n", + " bind_rows()" + ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 248, "metadata": {}, - "outputs": [], - "source": [] + "outputs": [ + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
taxonparenttax_nametax_rankcountcount_normid
species 2 Finegoldia sp. S9 AA1-5 37944
1392389 186813 Intestinimonas genus 126 3164 37944
1407607 186803 Fusicatenibactergenus 418 10498 37944
1505652 186804 Terrisporobactergenus 133 3340 37944
1505657 186804 Intestinibacter genus 203 5098 37944
1505660 186804 Asaccharospora genus 47 1180 37944
\n" + ], + "text/latex": [ + "\\begin{tabular}{r|lllllll}\n", + " taxon & parent & tax\\_name & tax\\_rank & count & count\\_norm & id\\\\\n", + "\\hline\n", + "\t species & 2 & Finegoldia & sp. & S9 & AA1-5 & 37944 \\\\\n", + "\t 1392389 & 186813 & Intestinimonas & genus & 126 & 3164 & 37944 \\\\\n", + "\t 1407607 & 186803 & Fusicatenibacter & genus & 418 & 10498 & 37944 \\\\\n", + "\t 1505652 & 186804 & Terrisporobacter & genus & 133 & 3340 & 37944 \\\\\n", + "\t 1505657 & 186804 & Intestinibacter & genus & 203 & 5098 & 37944 \\\\\n", + "\t 1505660 & 186804 & Asaccharospora & genus & 47 & 1180 & 37944 \\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "taxon | parent | tax_name | tax_rank | count | count_norm | id | \n", + "|---|---|---|---|---|---|\n", + "| species | 2 | Finegoldia | sp. | S9 | AA1-5 | 37944 | \n", + "| 1392389 | 186813 | Intestinimonas | genus | 126 | 3164 | 37944 | \n", + "| 1407607 | 186803 | Fusicatenibacter | genus | 418 | 10498 | 37944 | \n", + "| 1505652 | 186804 | Terrisporobacter | genus | 133 | 3340 | 37944 | \n", + "| 1505657 | 186804 | Intestinibacter | genus | 203 | 5098 | 37944 | \n", + "| 1505660 | 186804 | Asaccharospora | genus | 47 | 1180 | 37944 | \n", + "\n", + "\n" + ], + "text/plain": [ + " taxon parent tax_name tax_rank count count_norm id \n", + "1 species 2 Finegoldia sp. S9 AA1-5 37944\n", + "2 1392389 186813 Intestinimonas genus 126 3164 37944\n", + "3 1407607 186803 Fusicatenibacter genus 418 10498 37944\n", + "4 1505652 186804 Terrisporobacter genus 133 3340 37944\n", + "5 1505657 186804 Intestinibacter genus 203 5098 37944\n", + "6 1505660 186804 Asaccharospora genus 47 1180 37944" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "tail(public_data_table)" + ] + }, + { + "cell_type": "code", + "execution_count": 254, + "metadata": {}, + "outputs": [ + { + "data": {}, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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HTUV68JEzz3Lf+ZQNTZA779LvNJj43F3wt0PhgUgNapxwvFGYxlm8/XwErThSml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\nUJp0VVZWLl68mF+N7T8e48aNe/LkyYsXL06cOGFoaMi+pVR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+ "text/plain": [ + "plot without title" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "phyla <- public_data_table %>% filter(tax_rank == \"phylum\")\n", + "\n", + "ggplot(phyla) +\n", + " geom_point(aes(tax_name, as.numeric(count), colour = id)) +\n", + " theme_minimal() +\n", + " theme(axis.text.x = element_text(angle = 30, hjust = 1)) +\n", + " scale_y_log10()" + ] }, { "cell_type": "code", From 4a46f00e736965b0a57ef5332030be802df1ab11 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Hadrien=20Gourl=C3=A9?= Date: Fri, 11 May 2018 15:55:58 +0200 Subject: [PATCH 3/4] compare my private data to public datasets --- ubiome.ipynb | 372 +++++++++++++++++++++++++++++++++++++-------------- 1 file changed, 268 insertions(+), 104 deletions(-) diff --git a/ubiome.ipynb b/ubiome.ipynb index c183b5e..1005266 100644 --- a/ubiome.ipynb +++ b/ubiome.ipynb @@ -4,13 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Ubiome data analysis - draft\n", + "# What's in my gut? Comparing your *ubiome* data to public datasets\n", "\n", "## Introduction\n", "\n", - "this notebook is being written as part of the Mozilla Global Sprint 2018. \n", - "It aims at providing to openhumans members with a walkthrough on how to analyse their microbiome data from ubiome.\n", - "\n" + "This notebook uses your *ubiome* data to visualise and compare your microbiome to other people's microbiome.\n", + "\n", + "The analyses presented in this notebook are exploratory and only descriptive. Our microbiomes are not yet well understood, and are vastly different between people. Do not be suprised to see differ from the public ones!" ] }, { @@ -19,12 +19,12 @@ "source": [ "## Data import\n", "\n", - "First, we load and install the necessary packages (be patient!):" + "First, we load the necessary packages:" ] }, { "cell_type": "code", - "execution_count": 150, + "execution_count": 128, "metadata": {}, "outputs": [], "source": [ @@ -36,46 +36,15 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "I do not have my own Ubiome data, so I'll import a public dataset using the public API" - ] - }, - { - "cell_type": "code", - "execution_count": 110, - "metadata": {}, - "outputs": [], - "source": [ - "url <- paste0(\"https://www.openhumans.org/api/\",\n", - " \"public-data/?source=direct-sharing-132\")\n", - "resp <- GET(url)\n", - "results <- content(resp, as = \"parsed\", type = \"application/json\")$results\n", - "results <- bind_rows(lapply(results, as.data.frame.list, stringsAsFactors=FALSE))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "The Ubiome data is apparently available as a raw fastq file or a json result file \n", - "We'll first explore the content of the json files. \n", + "The Ubiome data is available as a raw fastq file or a json result file \n", + "The fastq files are the \"raw\" data that contain the DNA sequences from a bacterial gene called \"16S\". While we could analyse those files and retrieve the bacterial composition of your samples, we will rather use the json file, which contains the result, as analysed by *ubiome*\n", + "\n", "We are not interested in the names of the users, so let's \"anonimize\" our dataframe first by dropping some columns" ] }, { "cell_type": "code", - "execution_count": 111, - "metadata": {}, - "outputs": [], - "source": [ - "jsons <- filter(results, metadata.tags..json. == 'json') %>%\n", - " select(-metadata.tags..fastq., -user.name, -user.username,\n", - " -metadata.tags..uBiome., -metadata.tags..16S.,\n", - " -source, -metadata.description, -metadata.tags..json.)" - ] - }, - { - "cell_type": "code", - "execution_count": 112, + "execution_count": 134, "metadata": {}, "outputs": [ { @@ -180,19 +149,22 @@ } ], "source": [ + "# download the public data and store in a data_frame\n", + "url <- paste0(\"https://www.openhumans.org/api/\",\n", + " \"public-data/?source=direct-sharing-132\")\n", + "resp <- GET(url)\n", + "results <- content(resp, as = \"parsed\", type = \"application/json\")$results\n", + "results <- bind_rows(lapply(results, as.data.frame.list, stringsAsFactors=FALSE))\n", + "jsons <- filter(results, metadata.tags..json. == 'json') %>%\n", + " select(-metadata.tags..fastq., -user.name, -user.username,\n", + " -metadata.tags..uBiome., -metadata.tags..16S.,\n", + " -source, -metadata.description, -metadata.tags..json.)\n", "head(jsons)" ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We download and read all the public data" - ] - }, { "cell_type": "code", - "execution_count": 244, + "execution_count": 130, "metadata": {}, "outputs": [], "source": [ @@ -225,7 +197,7 @@ }, { "cell_type": "code", - "execution_count": 210, + "execution_count": 135, "metadata": {}, "outputs": [ { @@ -256,6 +228,8 @@ "\t
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    • \n", "\n" ], "text/latex": [ @@ -284,6 +258,8 @@ "\\item 0\n", "\\item 0\n", "\\item 0\n", + "\\item 0\n", + "\\item 0\n", "\\end{enumerate}\n" ], "text/markdown": [ @@ -311,6 +287,8 @@ "22. 0\n", "23. 0\n", "24. 0\n", + "25. 0\n", + "26. 0\n", "\n", "\n" ], @@ -385,22 +363,36 @@ "[1] 0\n", "\n", "[[24]]\n", + "[1] 0\n", + "\n", + "[[25]]\n", + "[1] 0\n", + "\n", + "[[26]]\n", "[1] 0\n" ] }, "metadata": {}, "output_type": "display_data" - } - ], - "source": [ - "map2(jsons$download_url, paste0(\"data/\", jsons$id, \".json\"), download.file)" - ] - }, - { - "cell_type": "code", - "execution_count": 245, - "metadata": {}, - "outputs": [ + }, + { + "data": { + "text/html": [ + "TRUE" + ], + "text/latex": [ + "TRUE" + ], + "text/markdown": [ + "TRUE" + ], + "text/plain": [ + "[1] TRUE" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, { "name": "stderr", "output_type": "stream", @@ -677,29 +669,93 @@ "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 9 6 columns 7 columns 'data/37944.json' file 2 12 6 columns 7 columns 'data/37944.json' row 3 13 6 columns 7 columns 'data/37944.json' col 4 14 6 columns 7 columns 'data/37944.json' expected 5 19 6 columns 7 columns 'data/37944.json'\n", "... ................. ... ................................................... ........ ................................................... ...... ................................................... .... ................................................... ... ................................................... ... ................................................... ........ ...................................................\n", "See problems(...) for more details.\n", + "”Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“20 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/my_microbiome.json' file 2 11 6 columns 7 columns 'data/my_microbiome.json' row 3 14 6 columns 7 columns 'data/my_microbiome.json' col 4 15 6 columns 7 columns 'data/my_microbiome.json' expected 5 16 6 columns 7 columns 'data/my_microbiome.json'\n", + "... ................. ... ........................................................... ........ ........................................................... ...... ........................................................... .... ........................................................... ... ........................................................... ... ........................................................... ........ ...........................................................\n", + "See problems(...) for more details.\n", "”" ] + }, + { + "data": { + "text/html": [ + "\n", + "\n", + "\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\n", + "
    taxonparenttax_nametax_rankcountcount_normid
    1 0 root root 82710 1000024 37852
    2 131567 Bacteria superkingdom 82708 1000000 37852
    481 206351 Neisseriaceae family 2 24 37852
    482 481 Neisseria genus 2 24 37852
    24 496 Neisseria macacae species 2 37852
    543 91347 Enterobacteriaceaefamily 853 10313 37852
    \n" + ], + "text/latex": [ + "\\begin{tabular}{r|lllllll}\n", + " taxon & parent & tax\\_name & tax\\_rank & count & count\\_norm & id\\\\\n", + "\\hline\n", + "\t 1 & 0 & root & root & 82710 & 1000024 & 37852 \\\\\n", + "\t 2 & 131567 & Bacteria & superkingdom & 82708 & 1000000 & 37852 \\\\\n", + "\t 481 & 206351 & Neisseriaceae & family & 2 & 24 & 37852 \\\\\n", + "\t 482 & 481 & Neisseria & genus & 2 & 24 & 37852 \\\\\n", + "\t 24 & 496 & Neisseria & macacae & species & 2 & 37852 \\\\\n", + "\t 543 & 91347 & Enterobacteriaceae & family & 853 & 10313 & 37852 \\\\\n", + "\\end{tabular}\n" + ], + "text/markdown": [ + "\n", + "taxon | parent | tax_name | tax_rank | count | count_norm | id | \n", + "|---|---|---|---|---|---|\n", + "| 1 | 0 | root | root | 82710 | 1000024 | 37852 | \n", + "| 2 | 131567 | Bacteria | superkingdom | 82708 | 1000000 | 37852 | \n", + "| 481 | 206351 | Neisseriaceae | family | 2 | 24 | 37852 | \n", + "| 482 | 481 | Neisseria | genus | 2 | 24 | 37852 | \n", + "| 24 | 496 | Neisseria | macacae | species | 2 | 37852 | \n", + "| 543 | 91347 | Enterobacteriaceae | family | 853 | 10313 | 37852 | \n", + "\n", + "\n" + ], + "text/plain": [ + " taxon parent tax_name tax_rank count count_norm id \n", + "1 1 0 root root 82710 1000024 37852\n", + "2 2 131567 Bacteria superkingdom 82708 1000000 37852\n", + "3 481 206351 Neisseriaceae family 2 24 37852\n", + "4 482 481 Neisseria genus 2 24 37852\n", + "5 24 496 Neisseria macacae species 2 37852\n", + "6 543 91347 Enterobacteriaceae family 853 10313 37852" + ] + }, + "metadata": {}, + "output_type": "display_data" } ], "source": [ + "map2(jsons$download_url, paste0(\"data/\", jsons$id, \".json\"), download.file)\n", + "file.remove(\"data/37844.json\") # invalid json\n", "data_path <- dir(\"data\", pattern = '.json', full.names = TRUE)\n", - "full_data <- map(data_path, read_json_or_tbl_or_csv)" - ] - }, - { - "cell_type": "code", - "execution_count": 246, - "metadata": {}, - "outputs": [], - "source": [ - "public_data_table <- map(full_data, mutate_all, as.character) %>%\n", + "data_container <- map(data_path, read_json_or_tbl_or_csv)\n", + "full_data <- map(data_container, mutate_all, as.character) %>%\n", " bind_rows()" ] }, { "cell_type": "code", - "execution_count": 248, - "metadata": {}, + "execution_count": 136, + "metadata": { + "scrolled": true + }, "outputs": [ { "data": { @@ -707,12 +763,12 @@ "\n", "\n", "\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", - "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", + "\t\n", "\n", "
    taxonparenttax_nametax_rankcountcount_normid
    species 2 Finegoldia sp. S9 AA1-5 37944
    1392389 186813 Intestinimonas genus 126 3164 37944
    1407607 186803 Fusicatenibactergenus 418 10498 37944
    1505652 186804 Terrisporobactergenus 133 3340 37944
    1505657 186804 Intestinibacter genus 203 5098 37944
    1505660 186804 Asaccharospora genus 47 1180 37944
    1 0 root root 82710 1000024 37852
    2 131567 Bacteria superkingdom 82708 1000000 37852
    481 206351 Neisseriaceae family 2 24 37852
    482 481 Neisseria genus 2 24 37852
    24 496 Neisseria macacae species 2 37852
    543 91347 Enterobacteriaceaefamily 853 10313 37852
    \n" ], @@ -720,35 +776,35 @@ "\\begin{tabular}{r|lllllll}\n", " taxon & parent & tax\\_name & tax\\_rank & count & count\\_norm & id\\\\\n", "\\hline\n", - "\t species & 2 & Finegoldia & sp. & S9 & AA1-5 & 37944 \\\\\n", - "\t 1392389 & 186813 & Intestinimonas & genus & 126 & 3164 & 37944 \\\\\n", - "\t 1407607 & 186803 & Fusicatenibacter & genus & 418 & 10498 & 37944 \\\\\n", - "\t 1505652 & 186804 & Terrisporobacter & genus & 133 & 3340 & 37944 \\\\\n", - "\t 1505657 & 186804 & Intestinibacter & genus & 203 & 5098 & 37944 \\\\\n", - "\t 1505660 & 186804 & Asaccharospora & genus & 47 & 1180 & 37944 \\\\\n", + "\t 1 & 0 & root & root & 82710 & 1000024 & 37852 \\\\\n", + "\t 2 & 131567 & Bacteria & superkingdom & 82708 & 1000000 & 37852 \\\\\n", + "\t 481 & 206351 & Neisseriaceae & family & 2 & 24 & 37852 \\\\\n", + "\t 482 & 481 & Neisseria & genus & 2 & 24 & 37852 \\\\\n", + "\t 24 & 496 & Neisseria & macacae & species & 2 & 37852 \\\\\n", + "\t 543 & 91347 & Enterobacteriaceae & family & 853 & 10313 & 37852 \\\\\n", "\\end{tabular}\n" ], "text/markdown": [ "\n", "taxon | parent | tax_name | tax_rank | count | count_norm | id | \n", "|---|---|---|---|---|---|\n", - "| species | 2 | Finegoldia | sp. | S9 | AA1-5 | 37944 | \n", - "| 1392389 | 186813 | Intestinimonas | genus | 126 | 3164 | 37944 | \n", - "| 1407607 | 186803 | Fusicatenibacter | genus | 418 | 10498 | 37944 | \n", - "| 1505652 | 186804 | Terrisporobacter | genus | 133 | 3340 | 37944 | \n", - "| 1505657 | 186804 | Intestinibacter | genus | 203 | 5098 | 37944 | \n", - "| 1505660 | 186804 | Asaccharospora | genus | 47 | 1180 | 37944 | \n", + "| 1 | 0 | root | root | 82710 | 1000024 | 37852 | \n", + "| 2 | 131567 | Bacteria | superkingdom | 82708 | 1000000 | 37852 | \n", + "| 481 | 206351 | Neisseriaceae | family | 2 | 24 | 37852 | \n", + "| 482 | 481 | Neisseria | genus | 2 | 24 | 37852 | \n", + "| 24 | 496 | Neisseria | macacae | species | 2 | 37852 | \n", + "| 543 | 91347 | Enterobacteriaceae | family | 853 | 10313 | 37852 | \n", "\n", "\n" ], "text/plain": [ - " taxon parent tax_name tax_rank count count_norm id \n", - "1 species 2 Finegoldia sp. S9 AA1-5 37944\n", - "2 1392389 186813 Intestinimonas genus 126 3164 37944\n", - "3 1407607 186803 Fusicatenibacter genus 418 10498 37944\n", - "4 1505652 186804 Terrisporobacter genus 133 3340 37944\n", - "5 1505657 186804 Intestinibacter genus 203 5098 37944\n", - "6 1505660 186804 Asaccharospora genus 47 1180 37944" + " taxon parent tax_name tax_rank count count_norm id \n", + "1 1 0 root root 82710 1000024 37852\n", + "2 2 131567 Bacteria superkingdom 82708 1000000 37852\n", + "3 481 206351 Neisseriaceae family 2 24 37852\n", + "4 482 481 Neisseria genus 2 24 37852\n", + "5 24 496 Neisseria macacae species 2 37852\n", + "6 543 91347 Enterobacteriaceae family 853 10313 37852" ] }, "metadata": {}, @@ -756,12 +812,68 @@ } ], "source": [ - "tail(public_data_table)" + "head(full_data)" ] }, { "cell_type": "code", - "execution_count": 254, + "execution_count": 137, + "metadata": {}, + "outputs": [], + "source": [ + "# now our private data\n", + "access_token <- Sys.getenv(\"OH_ACCESS_TOKEN\")\n", + "url <- paste(\n", + " \"https://www.openhumans.org/api/direct-sharing/\",\n", + " \"project/exchange-member/?access_token=\",\n", + " access_token, sep=\"\")\n", + "resp <- GET(url)\n", + "user <- content(resp, \"parsed\")\n", + "my_files <- c()\n", + "for (data_source in user$data){\n", + " if (data_source$source == \"direct-sharing-132\"){\n", + " my_files <- c(my_files, data_source$download_url)\n", + " }\n", + "}\n", + "my_files <- subset(my_files, grepl(\"json\", my_files))\n", + "download.file(my_files, destfile = \"data/my_microbiome.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": 161, + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Parsed with column specification:\n", + "cols(\n", + " tax_name = col_character(),\n", + " tax_rank = col_character(),\n", + " count = col_character(),\n", + " count_norm = col_character(),\n", + " taxon = col_character(),\n", + " parent = col_character()\n", + ")\n", + "Warning message in rbind(names(probs), probs_f):\n", + "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", + "“76 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 9 6 columns 7 columns 'data/my_microbiome.json' file 2 12 6 columns 7 columns 'data/my_microbiome.json' row 3 13 6 columns 7 columns 'data/my_microbiome.json' col 4 14 6 columns 7 columns 'data/my_microbiome.json' expected 5 19 6 columns 7 columns 'data/my_microbiome.json'\n", + "... ................. ... ........................................................... ........ ........................................................... ...... ........................................................... .... ........................................................... ... ........................................................... ... ........................................................... ........ ...........................................................\n", + "See problems(...) for more details.\n", + "”" + ] + } + ], + "source": [ + "my_data <- read_json_or_tbl_or_csv(\"data/my_microbiome.json\")" + ] + }, + { + "cell_type": "code", + "execution_count": 163, "metadata": {}, "outputs": [ { @@ -771,7 +883,7 @@ }, { "data": { - "image/png": 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HTUV68JEzz3Lf+ZQNTZA779LvNJj43F3wt0PhgUgNapxwvFGYxlm8/XwErThSml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\nQWtr64CAAISQhoa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bAOz4aL5rsIMiYmZtmyZUuXLo2Li2M+xdz3QDuf7sTZGWvDxYnhor02J4mLNb/+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\n5MCBA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"text/plain": [ "plot without title" ] @@ -781,15 +893,67 @@ } ], "source": [ - "phyla <- public_data_table %>% filter(tax_rank == \"phylum\")\n", + "phyla <- full_data %>% filter(tax_rank == \"phylum\")\n", "\n", "ggplot(phyla) +\n", - " geom_point(aes(tax_name, as.numeric(count), colour = id)) +\n", + " geom_boxplot(aes(reorder(tax_name, as.numeric(count)), as.numeric(count)), alpha = 0.8, colour = \"grey30\") +\n", + " geom_jitter(aes(reorder(tax_name, as.numeric(count)), as.numeric(count), colour = id)) +\n", + " scale_colour_grey(start = 0, end = .9) +\n", + " geom_point(data = filter(my_data, tax_rank == \"phylum\"),\n", + " aes(reorder(tax_name, as.numeric(count)), as.numeric(count)), colour = \"red\",\n", + " size = 3, alpha = 0.8) +\n", " theme_minimal() +\n", - " theme(axis.text.x = element_text(angle = 30, hjust = 1)) +\n", + " theme(axis.text.x = element_text(angle = 30, hjust = 1),\n", + " legend.position = \"none\") +\n", + " ggtitle(\"Distribution of phyla in my microbiome\",\n", + " subtitle = \"compared to OpenHuman public datasets\") +\n", + " xlab(\"phyla\") +\n", + " ylab(\"Log of counts\") +\n", " scale_y_log10()" ] }, + { + "cell_type": "code", + "execution_count": 193, + "metadata": {}, + "outputs": [ + { + "data": {}, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "image/png": 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IRCYZNGbGZ8DF38bryhSfEx+/WjbzdVKpVCoRAKhcbi0wqvHyNfDnB0dDS0SS6X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\ngg==", + "text/plain": [ + "plot without title" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# merge both datasets for the stacked bar chart\n", + "data_4_barchart <- bind_rows(full_data, my_data) %>%\n", + " filter(tax_rank == \"phylum\")\n", + "\n", + "# random color scale up to 433 colors\n", + "n <- distinct(data_4_barchart, tax_name)\n", + "color <- grDevices::colors()[grep('gr(a|e)y', grDevices::colors(), invert = T)]\n", + "col <- sample(color, length(n$tax_name))\n", + "\n", + "ggplot(data_4_barchart) +\n", + " geom_bar(aes(id, as.numeric(count), fill = tax_name),\n", + " stat = 'identity', position = 'fill', alpha = 0.6) +\n", + " ggtitle(\"Distribution of phyla between datasets\") +\n", + " theme_minimal() +\n", + " scale_fill_manual(values = col) +\n", + " theme(axis.text.x = element_text(angle = 30, hjust = 1, size = 6)) +\n", + " xlab(\"Dataset\") +\n", + " ylab(\"Percentage\")" + ] + }, { "cell_type": "code", "execution_count": null, From c2534795610b10ad0b18f9871bac5cceb3d0ba3a Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Hadrien=20Gourl=C3=A9?= Date: Fri, 11 May 2018 16:44:21 +0200 Subject: [PATCH 4/4] added a few explanations --- ubiome.ipynb | 330 ++++++++++++--------------------------------------- 1 file changed, 77 insertions(+), 253 deletions(-) diff --git a/ubiome.ipynb b/ubiome.ipynb index 1005266..41f7392 100644 --- a/ubiome.ipynb +++ b/ubiome.ipynb @@ -24,9 +24,25 @@ }, { "cell_type": "code", - "execution_count": 128, + "execution_count": 1, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Loading tidyverse: ggplot2\n", + "Loading tidyverse: tibble\n", + "Loading tidyverse: tidyr\n", + "Loading tidyverse: readr\n", + "Loading tidyverse: purrr\n", + "Loading tidyverse: dplyr\n", + "Conflicts with tidy packages ---------------------------------------------------\n", + "filter(): dplyr, stats\n", + "lag(): dplyr, stats\n" + ] + } + ], "source": [ "library(httr)\n", "library(tidyverse)" @@ -36,7 +52,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The Ubiome data is available as a raw fastq file or a json result file \n", + "The *ubiome* data is available as a raw fastq file or a json result file \n", "The fastq files are the \"raw\" data that contain the DNA sequences from a bacterial gene called \"16S\". While we could analyse those files and retrieve the bacterial composition of your samples, we will rather use the json file, which contains the result, as analysed by *ubiome*\n", "\n", "We are not interested in the names of the users, so let's \"anonimize\" our dataframe first by dropping some columns" @@ -44,7 +60,7 @@ }, { "cell_type": "code", - "execution_count": 134, + "execution_count": 9, "metadata": {}, "outputs": [ { @@ -162,9 +178,19 @@ "head(jsons)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Now that we have a data frame containing all the public json files, we will read them and combine them in a data frame.\n", + "\n", + "The block below defines a function that parses our data files, and the block below the function applies said function to all the public datasets. \n", + "*Note: the data is quite messy and applying the cuntion will generate several warnings. You can probably ignore them.*" + ] + }, { "cell_type": "code", - "execution_count": 130, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -197,184 +223,9 @@ }, { "cell_type": "code", - "execution_count": 135, + "execution_count": 10, "metadata": {}, "outputs": [ - { - "data": { - "text/html": [ - "
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Once again, you can safely ingore the warnings." + ] + }, { "cell_type": "code", - "execution_count": 137, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ @@ -841,7 +646,7 @@ }, { "cell_type": "code", - "execution_count": 161, + "execution_count": 19, "metadata": {}, "outputs": [ { @@ -853,14 +658,14 @@ " tax_name = col_character(),\n", " tax_rank = col_character(),\n", " count = col_character(),\n", - " count_norm = col_character(),\n", - " taxon = col_character(),\n", - " parent = col_character()\n", + " count_norm = col_integer(),\n", + " taxon = col_integer(),\n", + " parent = col_integer()\n", ")\n", "Warning message in rbind(names(probs), probs_f):\n", "“number of columns of result is not a multiple of vector length (arg 1)”Warning message:\n", - "“76 parsing failures.\n", - "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 9 6 columns 7 columns 'data/my_microbiome.json' file 2 12 6 columns 7 columns 'data/my_microbiome.json' row 3 13 6 columns 7 columns 'data/my_microbiome.json' col 4 14 6 columns 7 columns 'data/my_microbiome.json' expected 5 19 6 columns 7 columns 'data/my_microbiome.json'\n", + "“20 parsing failures.\n", + "row # A tibble: 5 x 5 col row col expected actual file expected actual 1 5 6 columns 7 columns 'data/my_microbiome.json' file 2 11 6 columns 7 columns 'data/my_microbiome.json' row 3 14 6 columns 7 columns 'data/my_microbiome.json' col 4 15 6 columns 7 columns 'data/my_microbiome.json' expected 5 16 6 columns 7 columns 'data/my_microbiome.json'\n", "... ................. ... ........................................................... ........ ........................................................... ...... ........................................................... .... ........................................................... ... ........................................................... ... ........................................................... ........ ...........................................................\n", "See problems(...) for more details.\n", "”" @@ -868,12 +673,22 @@ } ], "source": [ - "my_data <- read_json_or_tbl_or_csv(\"data/my_microbiome.json\")" + "my_data <- read_json_or_tbl_or_csv(\"data/my_microbiome.json\") %>%\n", + " mutate_all(as.character)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Exploratory analysis\n", + "\n", + "We have loaded the datasets! Now we can compare our microbiome data to others'" ] }, { "cell_type": "code", - "execution_count": 163, + "execution_count": 20, "metadata": {}, "outputs": [ { @@ -883,7 +698,7 @@ }, { "data": { - "image/png": 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bAOz4aL5rsIMiYmZtmyZUuXLo2Li2M+xdz3QDuf7sTZGWvDxYnhor02J4mLNb/+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\nAAAYLsMQ7KqqqrZv397R0dHb2xsXF8dkMs3MzFRUVE6dOjV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+Pjn3zySWZ35kC8/5q8/y7sw3Pg4fA9BBkXF7dkyZLFixcnJCQwezHzHmj3y524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Lry3HcU6nM7yVByiKGjFixBX3n4hHH3/8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\n7FhDQ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"text/plain": [ "plot without title" ] @@ -912,9 +727,18 @@ " scale_y_log10()" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "This plot represents the log of the bacteria counts for each phyla found in the samples. Public data is in grey, you are in red!\n", + "\n", + "The public datasets are mostly from gut samples. If you see outlier in grey, they may come from genital or skin samples. " + ] + }, { "cell_type": "code", - "execution_count": 193, + "execution_count": 21, "metadata": {}, "outputs": [ { @@ -924,7 +748,7 @@ }, { "data": { - "image/png": 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IRCYZNGbGZ8DF38bryhSfEx+/WjbzdVKpVCoRAKhcbi0wqvHyNfDnB0dDS0SS6X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\nQcXNDDqrMej7MvENyvfcpUuXzMzM2bNnex0fDCLo9TLxF/Q3qHp9FIPaN9P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Var1WobGxujf2XyBGq1WqVSKRaLbWyMHC+eQCKqqanhOM7o02SBVSYyoFAodDqd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\nz4UOh8NisRiNRqPS2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