CODEWITHSUNDEEP
rdataframematrixassign
beginner
beginner

Reputation: 1059

How to create a matrix based on information in other dataframe in R?

I have a dataframe with gene names and miRNA interaction information. The dataframe looks like below:

df:

Gene      miRNA
ACP1    hsa-let-7a-5p
AGO4    hsa-let-7a-5p
AMMECR1 hsa-let-7a-5p
ATM     hsa-miR-100-5p
BMPR2   hsa-miR-100-5p
AGO1    hsa-miR-107
AGO2    hsa-miR-107
AGO3    hsa-miR-107

Using the above information which is gene-miRNA interaction information, I wanted to create a matrix. If there is interaction I would like to assign 1 if not 0. The matrix should look like below:

          hsa-let-7a-5p hsa-miR-100-5p  hsa-miR-107
ACP1           1              0              0
AGO4           1              0              0
AMMECR1        1              0              0
ATM            0              1              0
BMPR2          0              1              0
AGO1           0              0              1
AGO2           0              0              1 
AGO3           0              0              1

I tried using xtabs for this. Couldn't use it correctly. 

xtabs(c(1L, 0L)[miRNA] ~ ., data=df)

Result looks like below:

Gene
   ACP1    AGO1    AGO2    AGO3    AGO4 AMMECR1     ATM   BMPR2 
      1       0       0       0       1       1       0       0

Any help is appreciated. thanq.

Upvotes: 2

Views: 47

Answers (1)

Ronak Shah
Ronak Shah

Reputation: 388817

We can create a dummy column with mutate and use pivot_wider to cast data into wide format.

library(dplyr)
library(tidyr) # version ‘1.0.0’

df %>%
  mutate(n = 1) %>%
  pivot_wider(names_from = miRNA, values_from = n, values_fill = list(n = 0))
  #OR
  #spread(miRNA, n, fill = 0) in old tidyr


#  Gene    `hsa-let-7a-5p` `hsa-miR-100-5p` `hsa-miR-107`
#  <fct>             <dbl>            <dbl>         <dbl>
#1 ACP1                  1                0             0
#2 AGO4                  1                0             0
#3 AMMECR1               1                0             0
#4 ATM                   0                1             0
#5 BMPR2                 0                1             0
#6 AGO1                  0                0             1
#7 AGO2                  0                0             1
#8 AGO3                  0                0             1

If there is more than one row for each Gene and miRNA use distinct first.

df %>%
  distinct() %>%
  mutate(n = 1) %>%
  pivot_wider(names_from = miRNA, values_from = n, values_fill = list(n = 0))

Upvotes: 2

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