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library(tidyverse)
library(readr)
library(esquisse)
library(stringr)

Sheet <- read_csv("mmc1-2.csv")

Missing column names filled in: 'X20' [20], 'X21' [21]
── Column specification ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
  .default = col_character(),
  `Days between blood draws` = col_double(),
  `Age (y)` = col_double(),
  `Classical monocytes` = col_double(),
  `Non-classical monocytes` = col_double(),
  `NK cells` = col_double(),
  `Naïve B cells` = col_double(),
  X20 = col_logical(),
  X21 = col_logical()
)
ℹ Use `spec()` for the full column specifications.

Sheet

Data <- select(Sheet, "Donor ID", "Sex", ends_with("monocytes"), ends_with("cells"))
Data

DataF <- filter(Data, Sex == "F")
DataF

DataFf<- as.data.frame(apply(DataF, 2, as.numeric))

NAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercionNAs introduced by coercion

DataFf

DataM <- filter (Data, Sex == "M")
DataM

DataMm<- as.data.frame(apply(DataM, 2, as.numeric))

NAs introduced by coercionNAs introduced by coercion

DataMm

AverageF <- colMeans(DataFf, na.rm = TRUE, dims = 1)
AverageF

               Donor ID                     Sex     Classical monocytes Non-classical monocytes                NK cells           Naïve B cells     Naïve CD4+\nT cells 
             55.6756757                     NaN              17.1886364               1.3727273               6.3113636               5.4568182              12.1928571 
    Naïve CD8+\nT cells       Naïve\nTREG cells      Memory\nTREG cells               TH1 cells            TH1/17 cells              TH17 cells               TH2 cells 
              5.8928571               0.3928571               1.2357143               1.7047619               2.6119048               3.5023810               1.7142857 
              TFH cells 
              3.0095238 

MeanF <- rbind(AverageF, DataFf, deparse.level = 1)
MeanF

MeanFf <- read_csv("Research - Sheet2.csv")

── Column specification ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
  `Cell Type` = col_character(),
  `Gene Expression` = col_double()
)

MeanFf

ggplot(MeanFf) +
 aes(x = `Cell Type`, weight = `Gene Expression`) +
 geom_bar(fill = "#6d9eeb") +
 coord_flip() +
 theme_minimal() +
 ylim(0L, 20L)

AverageM <- colMeans(DataMm, na.rm = FALSE, dims = 1)
AverageM

               Donor ID                     Sex     Classical monocytes Non-classical monocytes                NK cells           Naïve B cells     Naïve CD4+\nT cells 
                     NA                      NA              18.2903226               1.6387097               8.1564516               5.1322581              10.3193548 
    Naïve CD8+\nT cells       Naïve\nTREG cells      Memory\nTREG cells               TH1 cells            TH1/17 cells              TH17 cells               TH2 cells 
              6.4274194               0.4935484               1.2129032               1.3306452               1.7612903               2.9354839               1.8451613 
              TFH cells 
              2.5500000 

MeanM <- rbind(AverageM, DataMm, deparse.level = 1)
MeanM

MeanMm <- read_csv("Research - Sheet3.csv")

── Column specification ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
  `Cell Type` = col_character(),
  `Gene Expression` = col_double()
)

MeanMm

ggplot(MeanMm) +
 aes(x = `Cell Type`, weight = `Gene Expression`) +
 geom_bar(fill = "#bbc9d3") +
 coord_flip() +
 theme_minimal() +
 ylim(0L, 20L)

Sum <- AverageF - AverageM
AbsSum <- abs(Sum)
Total <- rbind(AbsSum, Data, deparse.level = 1)
Total

TotalA <- read_csv("Research - Sheet1.csv")

── Column specification ─────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
cols(
  `Cell Type` = col_character(),
  `Gene Expression` = col_double()
)

TotalA

ggplot(TotalA) +
 aes(x = `Cell Type`, weight = `Gene Expression`) +
 geom_bar(fill = "#00e1c6") +
 coord_flip() +
 theme_minimal() +
 ylim(0L, 2L)

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