Marcin Kosiński MarcinKosinski

## import an unexported function from another package
predict_lda <- function(...)
  get('predict.lda', envir = asNamespace('MASS'), inherits = FALSE)(...)

## use get to substiture function name
# what it was
{if({my_stat} == "avg") {dplyr::summarise(., stat = mean(var_agg, na.rm = TRUE)) %>%
        dplyr::pull(stat) %>% formattable::comma(label_digits)}
      else if({my_stat} == "max") {dplyr::summarise(., stat = max(var_agg, na.rm = TRUE)) %>%
          dplyr::pull(stat) %>% formattable::comma(label_digits)}
      else if({my_stat} == "min") {dplyr::summarise(., stat = min(var_agg, na.rm = TRUE))

# what it can be
possible values of my_stat are renamed to so that `avg` is now `mean`

## survival.bib
@Article{assel,
	author = {Asselain, B. and Mould, R. F.},
	title = {Methodology of the {Cox} proportional hazards model},
	journal = {Journal of Oncology},
	year = {2010},
	volume = {60},
	number = {5},
	pages = {403--409}}

@Book{boxst,

## mail_through_mailR
library(mailR)
sender <- "hello@mail.com"
recipient <- "m.p.kosinski@gmail.com"
  send.mail(from = sender,
            to = recipient,
            subject = "Subject",
            body = "Hello World!",
            smtp = list(host.name = "smtp.gmail.com", port = 465,
                        user.name = "hello@gmail.com",
                        passwd = pwd,

## polish stemming
download.file('https://github.com/MarcinKosinski/trigeR5/raw/master/dicts/polimorfologik-2.1.zip', destfile = 'poli.zip')
unzip('poli.zip', exdir = 'dicts')
library(data.table);library(dplyr)
polimorfologik <- fread('dicts/polimorfologik-2.1.txt', data.table = FALSE) %>% set_colnames(c('stem', 'words', 'random_stuff')) %>% select(1:2)
random_polish_text <-
  'Wbrew wcześniejszym doniesieniom mediów, w bazie pod Latok I (szczyt w masywie w grupie Panmah Muztagh, części Karakorum), gdzie organizowana jest pomoc dla Aleksandra Gukowa (rosyjski himalaista nadał sygnał SOS i musi zostać ewakuowany, bo jest pozbawiony ekwipunku), nie ma też Andrzeja Bargiela. - Andrzej zgłosił chęć pomocy i wzięcia udziału w akcji ratunkowej. Jednak obecnie znajduje się w Skardu, gdzie dotarł wczoraj z bazy pod K2 - czytamy na twitterowym koncie pierwszego człowieka w historii, który zjechał z wierzchołka K2.'

(polish_stop_words <- readLines('https://raw.githubusercontent.com/MarcinKosinski/trigeR5/master/dicts/polish_stopwords.

## generate_ids_from_csv
\documentclass[15pt]{scrartcl}
\usepackage[a6paper,left=1cm,right=1cm,top=2cm,bottom=1cm,heightrounded]{geometry}
\usepackage[svgnames]{xcolor}
\usepackage{pdflscape}
\usepackage{setspace}
\usepackage[utf8]{inputenc}
\usepackage[T1]{fontenc}
\usepackage{graphicx}
\usepackage{wallpaper}
\usepackage[normalem]{ulem}

## add data.frame to CrunchDataset
library(dplyr);library(crunch)
iris_ds <-
  newDataset(iris, name = 'iris')

# how to add the following data.frame as a CrunchCube or something similar to the Array?
iris_ds$some_statistics <-
  iris %>%
  group_by(Species) %>%
  summarize_all(funs(mean))

## ggsurvplot_example.R
ggsurv <- ggsurvplot(
  fit,                     # survfit object with calculated statistics.
  data = BRCAOV.survInfo,  # data used to fit survival curves.
  risk.table = TRUE,       # show risk table.
  pval = TRUE,             # show p-value of log-rank test.
  conf.int = TRUE,         # show confidence intervals
  xlim = c(0,2000),        # present narrower X axis, but not affect
  # survival estimates.
  xlab = "Time in days",   # customize X axis label.
  break.time.by = 500,     # break X axis in time intervals by 500.

## america_is_on_the_move.R

library(rgdal)    # read and store spatial data
library(dplyr)    # manipulate data frames for data wrangling
library(leaflet)  # connect to LeafletJS library from R
library(magrittr) # pipe workflows
library(openxlsx) # read xlsx files
library(readxl)   # read xls  files

# prepare the data ------------------------------------------------------------
# read MSA layer

## provide_genomic_analysis_on_tcga_mutations_data.R
extractSurvival <- function(cohorts){

  survivalData <- list()
  for(i in cohorts){
    get(paste0(i, ".clinical"), envir = .GlobalEnv) %>%
				select(patient.bcr_patient_barcode,
							 patient.vital_status,
							 patient.days_to_last_followup,
							 patient.days_to_death ) %>%
				mutate(bcr_patient_barcode = toupper(patient.bcr_patient_barcode),
	predict_lda <- function(...)
	get('predict.lda', envir = asNamespace('MASS'), inherits = FALSE)(...)
	# what it was
	{if({my_stat} == "avg") {dplyr::summarise(., stat = mean(var_agg, na.rm = TRUE)) %>%
	dplyr::pull(stat) %>% formattable::comma(label_digits)}
	else if({my_stat} == "max") {dplyr::summarise(., stat = max(var_agg, na.rm = TRUE)) %>%
	dplyr::pull(stat) %>% formattable::comma(label_digits)}
	else if({my_stat} == "min") {dplyr::summarise(., stat = min(var_agg, na.rm = TRUE))

	# what it can be
	possible values of my_stat are renamed to so that `avg` is now `mean`
	@Article{assel,
	author = {Asselain, B. and Mould, R. F.},
	title = {Methodology of the {Cox} proportional hazards model},
	journal = {Journal of Oncology},
	year = {2010},
	volume = {60},
	number = {5},
	pages = {403--409}}

	@Book{boxst,
	library(mailR)
	sender <- "hello@mail.com"
	recipient <- "m.p.kosinski@gmail.com"
	send.mail(from = sender,
	to = recipient,
	subject = "Subject",
	body = "Hello World!",
	smtp = list(host.name = "smtp.gmail.com", port = 465,
	user.name = "hello@gmail.com",
	passwd = pwd,
	download.file('https://github.com/MarcinKosinski/trigeR5/raw/master/dicts/polimorfologik-2.1.zip', destfile = 'poli.zip')
	unzip('poli.zip', exdir = 'dicts')
	library(data.table);library(dplyr)
	polimorfologik <- fread('dicts/polimorfologik-2.1.txt', data.table = FALSE) %>% set_colnames(c('stem', 'words', 'random_stuff')) %>% select(1:2)
	random_polish_text <-
	'Wbrew wcześniejszym doniesieniom mediów, w bazie pod Latok I (szczyt w masywie w grupie Panmah Muztagh, części Karakorum), gdzie organizowana jest pomoc dla Aleksandra Gukowa (rosyjski himalaista nadał sygnał SOS i musi zostać ewakuowany, bo jest pozbawiony ekwipunku), nie ma też Andrzeja Bargiela. - Andrzej zgłosił chęć pomocy i wzięcia udziału w akcji ratunkowej. Jednak obecnie znajduje się w Skardu, gdzie dotarł wczoraj z bazy pod K2 - czytamy na twitterowym koncie pierwszego człowieka w historii, który zjechał z wierzchołka K2.'

	(polish_stop_words <- readLines('https://raw.githubusercontent.com/MarcinKosinski/trigeR5/master/dicts/polish_stopwords.
	\documentclass[15pt]{scrartcl}
	\usepackage[a6paper,left=1cm,right=1cm,top=2cm,bottom=1cm,heightrounded]{geometry}
	\usepackage[svgnames]{xcolor}
	\usepackage{pdflscape}
	\usepackage{setspace}
	\usepackage[utf8]{inputenc}
	\usepackage[T1]{fontenc}
	\usepackage{graphicx}
	\usepackage{wallpaper}
	\usepackage[normalem]{ulem}
	library(dplyr);library(crunch)
	iris_ds <-
	newDataset(iris, name = 'iris')

	# how to add the following data.frame as a CrunchCube or something similar to the Array?
	iris_ds$some_statistics <-
	iris %>%
	group_by(Species) %>%
	summarize_all(funs(mean))
	ggsurv <- ggsurvplot(
	fit, # survfit object with calculated statistics.
	data = BRCAOV.survInfo, # data used to fit survival curves.
	risk.table = TRUE, # show risk table.
	pval = TRUE, # show p-value of log-rank test.
	conf.int = TRUE, # show confidence intervals
	xlim = c(0,2000), # present narrower X axis, but not affect
	# survival estimates.
	xlab = "Time in days", # customize X axis label.
	break.time.by = 500, # break X axis in time intervals by 500.

	library(rgdal) # read and store spatial data
	library(dplyr) # manipulate data frames for data wrangling
	library(leaflet) # connect to LeafletJS library from R
	library(magrittr) # pipe workflows
	library(openxlsx) # read xlsx files
	library(readxl) # read xls files

	# prepare the data ------------------------------------------------------------
	# read MSA layer
	extractSurvival <- function(cohorts){

	survivalData <- list()
	for(i in cohorts){
	get(paste0(i, ".clinical"), envir = .GlobalEnv) %>%
	select(patient.bcr_patient_barcode,
	patient.vital_status,
	patient.days_to_last_followup,
	patient.days_to_death ) %>%
	mutate(bcr_patient_barcode = toupper(patient.bcr_patient_barcode),