Not enough memory at reduce_dimentionality step

Before the reduce_dimentioality step, I've done several steps to change my input dataset:

Using gather() to transform my dataset to the correct format ( 39,543,942 entries, 3 total columns)
Before proceeding to reduce dimentionality sfunction, I transformed my expression data to "matrix" type
Then my program stops here, telling that it needs 294.6GB to process the vectors.

Anyone has any suggestions for this?

Thank you so much!!

Can you show me the head of your dataset? You may want to run Matrix::sparseMatrix(...) to create a sparse matrix from your input data.

Do you mean instead of using matrix, I can substitute for sparseMatrix?

Attach the screenshot for my head of the dataset, also the code below.

`
data2 <- read.table("~/Downloads/Exp_BM_cluster_EC.txt", row.names = NULL)

library (tidyr)
data_long <- gather(data2, key = "sample_info", value = "expression", 2:1290)
(coerce1 <- as.matrix(data_long$expression))

space <- reduce_dimensionality(coerce1, ndim = 2)
traj <- infer_trajectory(space)
`

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