# TF-IDF normalization Latent semantic indexing (LSI) was first introduced for the analysis of scATAC-seq data by [Cusanovich et al. 2018](https://www.nature.com/articles/nature25981)\[1]. LSI combines steps of frequency-inverse document frequency (TF-IDF) normalization followed by singular value decomposition (SVD). Connected Multiomics wrapped Signac's TF-IDF normalization for single cell ATAC-seq dataset. It is a two-step normalization procedure that both normalizes across cells to correct for differences in cellular sequencing depth, and across peaks to give higher values to more rare peaks\[2]. To run **TF-IDF normalization**, * Click a **single cell ATAC counts** data node * Click the **Normalization and scaling** section in the toolbox * Click **TF-IDF normalization** The output of **TF-IDF normalization** is a new data node that has been normalized by log(*TF x IDF*). We can then use this new normalized matrix for downstream differential analysis and/or visualization. ## References 1. Cusanovich, D., Reddington, J., Garfield, D. *et al.* The *cis*-regulatory dynamics of embryonic development at single-cell resolution. *Nature* **555,** 538–542 (2018). 2. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://help.multiomics.illumina.com/icm/analyses/analysis-functionality/task-menu/normalization-and-scaling/tf-idf-normalization.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.