revised README

README.md

@@ -62,40 +62,64 @@ GETTING STARTED
 Below is an example for getting MIPgen up and running and designing probes to EGFR, TERT and BRAF
 
 first extract the tar file to make a MIPgen directory
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     tar -xf mipgen.tgz
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 enter the directory to compile the source code
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     cd MIPGEN/
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 use make to compile -- make sure you have a C++ compiler
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     make
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 make a directory for practicing designs
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     mkdir ../mipgen_practice
     cd ../mipgen_practice
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 create a new file and type a list of gene symbols you would like to tile
 with MIPs
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     vim practice_genes.txt
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 you can use one of the scripts in the tools subdirectory and a refGene text
 file listing gene exons to pull out the genomic coordinates of your genes of
 interest
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     sh ../MIPGEN/tools/extract_coding_gene_exons.sh practice_genes.txt ../refGene.txt > practice_genes.bed
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 check to make sure the coordinates are what you expect and that no errors
 occurred
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     less practice_genes.bed
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 now you can perform designs with MIPgen
 here are some very basic options
 make sure you have the dependencies installed or accessible through a given
 path (BWA, tabix, samtools)
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     ../MIPGEN/mipgen -regions_to_scan practice_genes.bed -project_name practice_design -min_capture_size 162 -max_capture_size 162 -bwa_genome_index $hg19ref
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 the final selection of MIPs is located in the picked MIPs file
 review the scores to make sure the MIPs stand a good chance of success
 (logistic scores below 0.6 are unlikely to provide usable data)
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     less practice_design.picked_mips.txt
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 by default all tested MIPs are output; this is a lot of output! (Turn it off with the silent_mode option)
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     rm practice_design.all_mips.txt
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 sai, fq (and sam) files are not deleted automatically and can also take up
 space
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     rm -f *.sai *.fq
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 generate a UCSC track with another tools script to visualize online
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     python ../MIPGEN/tools/generate_ucsc_track.py practice_design.picked_mips.txt practice_ucsc_track
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 look at the other files in this directory to see designs for TERT, BRAF and
 EGFR (we have not tested these designs experimentally so we cannot precisely
 assess predicted performance