Data Filtering

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## GeneFamilies analysis 
## Date - 27 September 2024
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# (1) Install the required package
install.packages("readr")
# Load the installed Package
library(readr)

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## (2) set working directory 
setwd("C:/Users/smeeta.shrestha/Desktop/2024_human_choline_bgi_2/humann3_genefam/")

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## (3)  Load in the genefamilies relab 
genefam <- read.csv("merge_genefamilies_relab_uniref90.tsv", stringsAsFactors = FALSE, header = TRUE);head(dat)

# Reading the contents of TSV file using read_tsv() method
genefam<-readr::read_tsv("merge_genefamilies_relab.tsv")
dim(genefam)
# Read tsv files using read.delim() method
df<-read.delim("merge_genefamilies_relab_uniref90.tsv",sep="\t")
dim(df)
head(df)
class(df)
columns <- colnames(df);columns

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## (4) clean the data 
## (4a) Filter - remove the row where we see the word "unclassified"

## How do I drop rows that contain a specific string in R?
df1 <- df[!grepl('unclassified', df$X..Gene.Family),]
dim(df1)
head(df1)
## (4b) Filter - remove the row where we see the word "NO_NAME"
df2 <- df1[!grepl('NO_NAME',df1$X..Gene.Family),]
dim(df2)
head(df2)
## (4c) Keep only those rows which have bacteria/taxa information along with the uniref90 gene name 
# Selecting rows in dataframe in R  based on partial row content.
# Selecting data frame rows based on partial string match in a column
library(data.table)
df3 <- df2[df2$X..Gene.Family %like% "g__", ]
dim(df3)
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## (5) export 
write.csv(df3,"genefam_uniref90_tax_clean.csv")

## End of Cleaning script 
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