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---
title: "CHCO R Training"
subtitle: "Hands-on Experience using swirl"
author: "Tiffany J. Callahan"
output: html_notebook
---

# Purpose
This [R Markdown Notebook](http://rmarkdown.rstudio.com) is intended to be used for all [swirl](https://swirlstats.com/) lessons as part of the CHCO R Training. It contains all the code needed to download and install all R swirl lessons. It also includes. Participants in the training are encouraged to create a new code chunk for each lesson. Participants should this to document their progress and to note areas for improvement.

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/* DEMOGRAPHICS */

SELECT DISTINCT pat.pat_id, pat.pat_mrn_id AS mrn, pat.pat_last_name AS last_name, pat.pat_first_name AS first_name,
substr(pat.pat_middle_name,1,1) AS mid_initial, pat2.maiden_name AS maiden_name, pat.birth_date AS dob, c.name AS county,
s.name AS state, pat.zip AS zip, enc.contact_date AS encounter_date, floor(months_between(enc.contact_date, pat.birth_date)/12) AS age,

(CASE WHEN sex.abbr='oth' THEN 'o' ELSE sex.abbr END) AS sex, 

(SELECT listagg(race.name, ',') WITHIN GROUP (ORDER BY pr.line)
FROM clarity.patient_race pr, clarity.zc_patient_race race

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# install list of packages
install.packages(c("dplyr", "dbplyr", "swirl", "odbc", "RODBC", "knitr", "DBI", "packrat", "rstudioapi", "rmarkdown", "codetools", "devtools", "ggplot2"))

# load installed packages
my_packages <- c("dplyr", "dbplyr", "swirl", "odbc", "RODBC", "knitr", "DBI", "packrat", "rstudioapi", "rmarkdown", "codetools", "devtools", "ggplot2")

lapply(my_packages, library, character.only = TRUE)

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---
title: "CHCO R Training"
subtitle: "Hands-on Experience Importing and Exporting Data"
author: "Tiffany J. Callahan"
output: html_notebook
---

# Purpose
This [R Markdown Notebook](http://rmarkdown.rstudio.com) is intended to be used for practicing importing and exporting different kinds of data. This Notebook contains code for importing the following types of data:  
    * [Flat Files](#txt)  

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---
title: 'MetaOmic: Transcriptomic Data Analysis'
author: 'Tiffany J. Callahan'
date: 'July 27, 2018'
output:
  html_notebook: default
  html_document: default
---

---

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##########################################################################################
# Concept_Annotator.py
# Purpose: script annotates clinical concepts to ontology terms using the NCBO API
# version 1.0.0
##########################################################################################


import urllib2
import json

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SELECT
  DISTINCT r.relationship_id,
  c1.concept_id AS SOURCE_CONCEPT_ID,
  c1.concept_name AS SOURCE_CONCEPT_LABEL,
  c2.concept_id AS TARGET_CONCEPT_ID,
  c2.concept_name AS TARGET_CONCEPT_LABEL,
FROM
  sandbox-omop.oct_2020.concept_relationship r
  JOIN sandbox-omop.oct_2020.concept c1 ON c1.concept_id = r.concept_id_1
  JOIN sandbox-omop.oct_2020.concept c2 ON c2.concept_id = r.concept_id_2

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-- Query Template: find exact matches between source vocabulary code strings and an OMOP standard terminology concept code 
SELECT DISTINCT
CONCAT('"', c.concept_code, '"') AS source_code,
c.concept_name AS source_name,
c.domain_id AS source_domain,
c.vocabulary_id AS source_vocabulary,
CONCAT('"', c1.concept_code, '"') AS standard_code,
c1.concept_name AS standard_name,
c1.domain_id AS standard_domain,
c1.vocabulary_id AS standard_vocabulary

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-- Query Template: find OMOP concept codes with a label that partially matches a source string
SELECT
source_string,
CONCAT('"', source_code, '"') AS source_code,
source_name,
source_domain,
source_vocabulary

FROM
(SELECT DISTINCT

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-- Query Template: find descendants of OMOP standard terminology concepts
SELECT DISTINCT
CONCAT('"', c.concept_code, '"') AS source_code,
c.concept_name AS standard_name,
c.domain_id AS standard_domain,
c.vocabulary_id AS standard_vocabulary,
CONCAT('"', dc.concept_code, '"') AS desc_standard_code,
dc.concept_name AS desc_standard_name,
dc.domain_id AS desc_standard_domain,
dc.vocabulary_id AS desc_standard_vocabulary