deletions | additions       diff --git a/Library Preparation and Sequencing .md b/Library Preparation and Sequencing .md  index 0bc8b2c..5aa4e70 100644  --- a/Library Preparation and Sequencing .md  +++ b/Library Preparation and Sequencing .md 
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Given the overcapacity of Illumina sequencing for bacterial genomes, sequencing a single genome presents a problem (unless willing to pay the ~$2000 total cost and throw away most of the data). Sequencing facilities will typically not "pool" samples from multiple groups because they don't want to oversee the pooling or deal with the associated accounting hassles. However, collaborating with other groups can be a great option. Many labs sequence genomes or metageomes on a regular basis; adding in one additional sample isn't technically very difficult, but it will entail oversight of the pooling and the associated accounting hassles. This will also entail a discussion of barcode compatibility, to ensure that all barcodes are sufficiently unique for demultiplexing.  ##Downsampling  The number of raw reads/raw nucleotides "Raw reads"/"Raw nt" and error-corrected reads/nucleotides "EC Reads"/"Raw nt" counts are useful for seeing what percentage of the data has been discarded. A very large difference between these numbers ("% reads passing EC"/"% nt passing EC") would indicate either poor quality input data or significant adapter contamination. Adaptor contamination can be high when the insert size is too small or if there were problems during library preparation.  For Illumina data we recommend that this number be between ~30X and 100X. Much less than 30X coverage and the quality of any given base in the assembly may come into question. Conversely, too much coverage can reduce the quality of the assembly and require downsampling. **Instructions or reference for downsampling?** If you have coverage significantly higher than 100x and wish to downsample your data we have written a script (sub_sample_reads) (sub\_sample\_reads) for this purpose. You will first need to calculate how many reads you want the script to sample. We recommend determining how many reads would be equivalent to 100x coverage (divide the genome size by the average read length and multiply by 100). You can download the script using the curl command. Create a new directory containing the reads you wish to downsample. In the terminal navigate the directory you just created and download the script using the following syntax curl https://raw.githubusercontent.com/gjospin/scripts/master/subsample_reads.pl > sub_sample_reads.pl