Update README.md

clarified file format for peak.info data frame

README.md

@@ -94,11 +94,11 @@ Further information on Inputs and Outputs of SCENT are detailed below:
 | 1    | rna (sparse matrix) | A gene-by-cell count matrix from multimodal RNA-seq data. This is a raw count matrix without any normalization. The row names should be the gene names used in the `peak.info` file. The column names are the cell names which should be the same names used in the `cell`column of the dataframe specified for `meta.data`. Sparse matrix format is required. |
 | 2    | atac (sparse matrix) | A peak-by-cell count matrix from multimodal ATAC-seq data. This is a raw count matrix without any normalization. The row names should be the peak names used in the `peak.info` file. The column names are the cell names which should be the same names used in `rna` and the `cell`column of dataframe specified for `meta.data`. The matrix may not be binarized while it will be binarized within the function. Sparse matrix format is required. |
 | 3    | meta.data (dataframe)     | A meta data frame for cells (rows are cells, and **cell names should be in the column named as "cell"**; see below example). Additionally, this text should include covariates to use in the model. Examples include: % mitochondrial reads, log(nUMI), sample, and batch as covariates. Dataframe format is required. |
-| 4    | peak.info (dataframe) | A textfile indicating which gene-peak pairs you want to test in this chunk (see below example). We highly recommend splitting gene-peak pairs into many chunks to increase computational efficiency (See Parallelized Jobs Info in Section 2). List(Dataframe) format which is a list of multiple data frames for parallelization is required. \* |
+| 4    | peak.info (dataframe) | A textfile indicating which gene-peak pairs you want to test in this chunk (see below example) **genes should be in the 1st column and peaks in the 2nd column**. We highly recommend splitting gene-peak pairs into many chunks to increase computational efficiency (See Parallelized Jobs Info in Section 2). List(Dataframe) format which is a list of multiple data frames for parallelization is required. \* |
 | 5    | covariates (a vector of character) | A vector of character fields that denote the covariates listed in the meta.data. For example, a set of covariates can be: %mitochondrial reads, log_nUMI, sample, and batch. Additionally the user can specify transformations to the covariates such as log transformation on nUMI counts for direct usage in the SCENT algorithm invoking poisson glm. **We recommend users to at least use log(number_of_total_RNA_UMI_count_per_cell) as the base model is Poisson regression and we do not include the offset term into the default model.** |
 | 6    | celltypes (character)        | User specified naming of the celltype column in the meta.data file. This column should contain the names of the celltypes you want to test in this association analysis. |
 
-\* Extra Argument: The peak.info.list field can be left blank initially and a created List(Dataframes) can be constructed using the CreatePeakToGeneList function in the SCENT package. This function requires the user to specify a bed file that specifies ~500 kb windows of multiple gene loci to identify cis gene-peak pairs to test. The vignette, SCENT_parallelize.Rmd, will show steps to produce a SCENT object with a peak.info.list field that is used for parallelization in the SCENT_parallelization.R script.
+\* Extra Argument: The peak.info.list field can be left blank initially and a created List(Dataframe) can be constructed using the CreatePeakToGeneList function in the SCENT package. This function requires the user to specify a bed file that specifies ~500 kb windows of multiple gene loci to identify cis gene-peak pairs to test. The vignette, SCENT_parallelize.Rmd, will show steps to produce a SCENT object with a peak.info.list field that is used for parallelization in the SCENT_parallelization.R script.