Update README.mdUpdating based on PR suggestions from LilyAnderssonLee

Co-authored-by: Lili Andersson-Li <[email protected]>

README.md

@@ -94,7 +94,7 @@ For more details about the full set of output files and reports, please refer to
 
 If you experience any issues, please make sure to reach out on the [#scnanoseq slack channel](https://nfcore.slack.com/archives/C03TUE2K6NS) or [open an issue on our GitHub repository](https://github.com/nf-core/scnanoseq/issues/new/choose). However, some resolutions for common issues will be noted below:
 
-- Due to the nature of the data this pipeline analyzes, some tools can experience increased runtimes. For some of the custom tools made for this pipeline (`preextract_fastq.py` and `correct_barcodes.py`), we have leveraged the splitting that is done via the `split_amount` parameter to decrease their overall runtimes. The `split_amount` parameter will split the input FASTQs into a number of FASTQ files that each have a number of lines based on the value used for this parameter. As a result, it is important not to set this parameter to be too low as it would cause the creation of a large number of files the pipeline will be processed. While this value can be highly dependent on the data, a good starting point for an analysis would be to set this value to `500000`. If you find that `PREEXTRACT_FASTQ` and `CORRECT_BARCODES` are still taking long amounts of time to run, it would be worth reducing this parameter to `200000` or `100000`, but keeping the value on the order of hundred of thousands or tens of thousands should help with with keeping the total number of processes minimal. An example of setting this parameter to be equal to 500000 is shown below:
+- Due to the nature of the data this pipeline analyzes, some tools may experience increased runtimes. For some of the custom tools made for this pipeline (`preextract_fastq.py` and `correct_barcodes.py`), we have leveraged the splitting done via the `split_amount` parameter to decrease their overall runtimes. The `split_amount` parameter will split the input FASTQs into a number of FASTQ files, each containing a number of lines based on the value used for this parameter. As a result, it is important not to set this parameter to be too low as doing so would cause the creation of a large number of files the pipeline will be processed. While this value can be highly dependent on the data, a good starting point for an analysis would be to set this value to `500000`. If you find that `PREEXTRACT_FASTQ` and `CORRECT_BARCODES` are still taking long amounts of time to run, it would be worth reducing this parameter to `200000` or `100000`, but keeping the value on the order of hundred of thousands or tens of thousands should help with keeping the total number of processes minimal. An example of setting this parameter to be equal to 500000 is shown below:
 
 ```yml title="params.yml"
 split_amount: 500000