data-analysis

Heart_rate_data_analysis1

Kazu Nozue / 2021-01-01

library(XML) library(tidyverse) library(lubridate) library(scales) library(ggthemes) Reading downloaded health data from an Apple watch. path="/Volumes/data_personal/Kazu_blog/resources" #zip <- paste(path, 'export_Mana_101320.zip', sep = '/') zip <- paste(path, …

data-analysis

Useful R techniques 1

Kazu Nozue / 2020-12-24

mtcars %>% rownames_to_column() %>% filter(str_detect(rowname,"Mazda")) ## rowname mpg cyl disp hp drat wt qsec vs am gear carb ## 1 Mazda RX4 21 6 160 110 3.9 2.620 16.46 0 1 4 4 ## 2 Mazda RX4 Wag 21 6 160 110 3.9 2.875 17.02 0 1 4 4 mtcars %>% rownames_to_column() %>% …

data-analysis

Evaluation of team rank prediction in sports league by sum of residuals

Kazu Nozue / 2019-12-29

J1_2019_pred_results<-read_csv(file.path("2019-12-29-evaluation-of-team-rank-prediction-in-sports-league-by-sum-of-residuals_files","日刊スポーツ・サッカー担当の19年J1順位予想と結果.csv")) ## Parsed with column specification: ## cols( ## rank = col_double(), ## Hamamoto = col_character(), ## No = …

data-analysis

Confirming genotypes by visualizing mutations from RNAseq data

Kazu Nozue / 2019-01-08

RNAseq is a powerful tool for transcriptome analysis. It is also useful for genotyping (for example, 1). Here I demonstrated an example of confirmation of genotype used for RNAseq. There are some unavoidable errors due to unexpected mistakes in many steps (eg. contamination of seeds, contamination …

data-analysis

VennDiagram with differentially expressed genes

Kazu Nozue / 2018-12-28

The last time I posted how to draw a VennDiagram with a simulated data. This time I would like to explain how to draw a VennDiagram from differentially expressed genes (DEGs). […] library(limma) library(tidyverse) ## ── Attaching packages …

data-analysis

List to data frame in R tidyverse

Kazu Nozue / 2018-12-20

Converting list object to a data frame object is common in R. There are many ways and here is another way using tidyverse packages. […] This is an efficient implementation of the common pattern of do.call(rbind, dfs) or do.call(cbind, dfs) for binding many data frames into one (cited from …