From 7e2f99572f6153a70ddb498bcabcbd55bd52372b Mon Sep 17 00:00:00 2001 From: wbaopaul Date: Mon, 13 Feb 2023 10:20:21 -0500 Subject: [PATCH] update readme for 1.5.1 --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9d6fd55..2506608 100644 --- a/README.md +++ b/README.md @@ -51,7 +51,7 @@ Updates - Now provide [scATAC-pro tutorial in R](https://scatacpro-in-r.netlify.app/index.html) for access QC metrics and perform downstream analysis - Current version: 1.5.1 - Highlighted updates - * **integrate** module takes input as a [SanokeSheet.csv](SampleSheet.csv file) (since v1.5.1), in which sample names, paths of peaks, fragments and cell barcodes files for each sample can be specified. Other parameters for integration are specified in the [configure_user](configure_user.txt) file + * **integrate** module takes input as a [SampleSheet](SampleSheet.csv file), in which sample names, paths of peaks, fragments and cell barcodes files for each sample can be specified. Other parameters for integration are specified in the [configure_user](configure_user.txt) file (v1.5.1) * New module **reprocess_cellranger_output** added, to reprocess 10x scATAC-seq data (including atac in 10x multiome assay) originally processed by cellranger, taking cellranger processed .bam and .fragments.tsv.gz files as input (v1.4.3) * More friendly to single-end sequencing data (v1.4.2) * New module *labelTransfer* added, to do label trasfer (for cell annotation) from cell annotation of scRNA-seq data. First construct a gene by cell activity matrix, then use *FindTransferAnchors* and *TransferData* function from Seurat R package to predicted cell type annotation from the cell annotaiton in scRNA-seq data (v1.4.0)