data analysis

Useful R techniques 1

Kazu Nozue / 2020-12-24
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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("/Volumes","data_personal","Kazu_blog14","resources","日刊スポーツ・サッカー担当の19年J1順位予想と結果.csv")) ## ## ── Column specification ──────────────────────────────────────────────────────── ## cols( ## rank =…
EV

Needs more cargo space in electric vehicles!

Kazu Nozue / 2019-03-30
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Electric vehicle (EV) became popular in California. Recently I can find more than one Tesla car during my daily commute. There are a couple of advantages of EV compared with gas powered vehicles; (1) higher cost efficiency (higher MPGe1), (2) lower maintainance cost, and (3) tax incentives and…
data analysis

Confirming genotypes by visualizing mutations from RNAseq data

Kazu Nozue / 2019-01-08
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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
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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 ─────────────────────────────────────── tidyverse…
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…