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Packstat application output

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Packstat application output


I am trying to use the packstat application for measuring the quality of my model. But, I'm not sure what the terms in output mean? (there is no info in user guide/documentation). I came up with the flags I've used from the RosettaHoles2 paper. As per the paper, it should output some pdb and also output explicit representation of voids. But, I donot see any output files. I only get the commandline output with three score columns.

Could someone clarify?

$ packstat.linuxgccrelease -in:file:s Model_Modeller_ID_9649770* -holes:dalphaball rosetta/main/source/external/DAlpahBall/DAlphaBall.gcc -remember_unrecognized_res -holes:make_pdb  -holes:make_voids
core.init: Rosetta version unknown:exported  from
core.init: command: packstat.linuxgccrelease -in:file:s Model_Modeller_ID_9649770_0001.pdb Model_Modeller_ID_9649770.pdb -holes:dalphaball /usr/local/bin/rosetta_bin_linux_2016.32.58837_bundle/main/source/external/DAlpahBall/DAlphaBall.gcc -remember_unrecognized_res -holes:make_pdb 1 -holes:make_voids -run:repeat 5
core.init: 'RNG device' seed mode, using '/dev/urandom', seed=1257353394 seed_offset=0 real_seed=1257353394
core.init.random: RandomGenerator:init: Normal mode, seed=1257353394 RG_type=mt19937
core.init: Resolved executable path: /usr/local/bin/rosetta_bin_linux_2016.32.58837_bundle/main/source/build/src/release/linux/3.10/64/x86/gcc/4.8/default/packstat.default.linuxgccrelease
core.init: Looking for database based on location of executable: /usr/local/bin/rosetta_bin_linux_2016.32.58837_bundle/main/database/
packstat: packing score: Model_Modeller_ID_9649770_0001.pdb 646 5355 0.5978



Post Situation: 
Mon, 2017-07-03 02:45

Are you talking about the line which looks like this?

packstat: packing score: ../1qys_0001.pdb 92 771 0.571189


From what I understand, the first number after the PDB name is the number of centers (the number of residues), the second is the number of spheres (more-or-less the number of atoms considered), and the final bit is the packing score (0-1 scale, with more packed being closer to 1.0). Read the Sheffler et al. papers to get a better understanding of the details.

Mon, 2017-07-03 09:17