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xaXpygKB5dWVlFrb5mQOydwB7i0J6ubFjh7npdh1XXdKUdEAmoj3W5Db4m4QE1LVCapO1XgH2D%2FkB08JF83SNM9ZhZf5I9%2B7Rz8J%2FI3IIfrMb5LHcjByu%2BUvGUKxQ%2FkcaLYdZ40f8JWOkw%2BA4iEBtlYSmddP1HFw%2FdKtShd1YQrncW61ZeqsIAcmYleEIEKAhx1ry8ND6aFh%2F8V9VHtiPdBPGObFcRVTzQgcz40RO7WEpW0ba3k2z3i6zBvlL9xO4ka%2F1EVnLTSa%2Buo%2BmkNzrwWDyPcz4lWOAxAp2%2BTrKORXoPGvm6d5aKpzt50u4573rAOfhP1CUXfpbjl36l4XWpysmXBCr6PbGqqsTnSRvReJFj4Xl9rvYfHFko%2FqPrb9YYEpV1CsKxTiSrXhisap%2F%2BC%2B6uu%2F8CZVz1iWlY7fGdnKxd2eM7WS2lcof2ANfjrBHRsoomvoE%2BuiF%2FpXpsCFnJYVZIVk7UsM85PYeLXYofPYf9H42YsMdtUq%2FMTd79Ho4bf2S7Gq9PVRxDC6lKG1VpVBV9cvFXGr6oVycSFZ%2FauXWquCnKooTpFvcfy0YiWVX%2BI%2FD8UOPXvp%2BE5%2Bom3JHt0IXP6MxS5U%2FAqovYd3l62%2BltAxkkq6q7T7LR3xT%2Bcz8gICtekEZU28Hq3d9JkEXhcfclufMmmZusgqh%2B5ww%2B7k3Vwcd9XbHh1JbiELt3Fu67QYbvmRs%2FCg5by%2Fr3TnRlZXhu7ijl5o6qlZ%2BrQrpkGp3PTVTZFKpwyqWabnH%2Fce5T6T%2Ba%2BNhiV5b7vOiQWG1XNvGNzngqewJWX%2BO7%2BPupIVbDas6n8HPju1ZMXmrvkcJ%2FhQ1Ya89RaqlV9P%2Bu0DacBdfrcx5rlPXMqW5%2B%2FVv8cfLHuP4t%2F6ZgDdhPFR8DGRmRoMk6R6Yc9MgU65TdN%2BKH32y1gyJruJn9x3%2BQ4%2B1zUvkZZYoyqq52HfJR1T3OUca8Ss9VrVhgoR1nngEaUXl%2BEwnEj%2B5Lg7fIsNx%2FsEWwXdT%2BI%2FD8UOO75zqXdKad2WS2XFS9L3XHH%2FH3m9r4nePnO%2F7Ys%2Fk6qErLYy0lJ6agZeeN%2FwwccYGT1QoEPwJqvCIveWiGhaw0jqw4olppFhqa8b%2FC%2BdTSMfJ8SlX%2Fp%2B918A8%2Bor5fxP%2FNTuvM3TtoeHe%2FThlVC9NKslFVNwNc6blq86mEHcyuYlSiOqOvmLPKAkLhPzbxCP6j62%2B9f0qwwjHOiiWI80kKVVktH0mD79lpNHuEPZ9yx6Q3iKpAKUiIS%2BdKK4ZmEpg0z1gZ%2FjhD12TDPydq2A6DMfTF%2FCCSlRZO0fLXPJsLM9o5%2FJ%2BS1UU8jHffrIaAVo2H93qXRX3g%2FV5fZeaqtAxwpeeqH3Trtr4z%2Boo5qyzjqus%2FuvixZ5JszVn3T9bAuDz2jM54qngC1XyGupJhFtiO%2BapVZZeFqvBG9bLT64cJ8zEW2juBk3sMRUbTMA9ggQX%2FxuNExVKRpvwrklXWFA5ZaUTl2d%2FRNOseP4pZYB18QoGHvnMyyNx5aXCbSf9x47s%2BV9Vv%2FQ2nBFacueFU%2BfxH298aemcj%2BAollosRz0QwI9ygM56qmBNbdKZpA5nYorobKAtV1yzEXc4xMjWQ2Xzu%2BE7FzK0BZnfYN3ezIOaa7cYL%2BL91Kw6%2BwooX2cJdqES1Yl3fwkumIJzZeGJX6gvVmzcdfOOV0JL6h1jjlZuVAa78e1Xd1scYiWP5mRhHlc9%2F9PFYhwhrwqz%2BfBOLKP8AaClJVcxhKRb%2FbHAgM5D5bBD67tR1UFX8XUSS8JcpqS8QN340V4kWuHQHNRnlvBhKfbH7Vr8H6fkKWPUwq6eGeuYgy1ZNqcPGOz6%2BR9SZ1V7of6CvfPi4Z0Y6zuSjamFa6bv2XhUpNzRDI2ruGXdyLNC1U%2FVs9fxHH4912DsxkOnMds9tPgd%2FPNEpvw99qvKrPL3r8FZaC3Vl26BE558ratV5h5brrxqrSjZWe2oL%2FbGSS62BPrSGWgP31eFR1ZYP7%2F23Jv5tWjqelgG%2BMe9VoU1C5X6i5fIfCh7GYRjtwIM65C%2FhnJc6S%2F9XnldPHdKgJoWtn6q6WQa0qq4yZuwG%2BY%2FxN2PGjBkzZsyYMWPGjBkzZsyYMWPGjBkzZsyYMWPGjBkzZsyYseVnpcgqGjNm7EYTNd1MEGK0kaUITo7BMiNUZj1D6RBgIRmWfxAO%2FFpHr1Vl6qOHh2WCxTJWwxWpzzycMW1rU6TJ5QMexTRpz5cqLpp7Tvw4WJlhBGp%2BBo7p79qA4m5Bmngs%2F5fXJWZFOsN86VmYRFb3agsKnuuswqLabGc2wig6q2t%2BjKX3TfZN4tc1P6Y0CV1XT7c%2Buvjor4tXpcgXo5daH5QVaUf8fJhRy0f8ShZltOdLW1lj1bW5cG1qRVxmL77HjjgmvE9R%2FzPNIBmL4pz2%2FS4zGXS56nQyJ70tVuA43%2FnhhXCDWLVTsHLHWSNKIav78VHwuOp%2FIIMipCx1YtdARq2zGvoUS986vnXcXu35aXmpqlsfXTwuQ3eviwCdg68rVx9cjSm%2F72K8qp0Ka69yLaEXBOWD7i5NogZ0pBfagNRNqJFxxsqEFfWPwLL%2B09uwHqe3jaYjJJ1eWCSe0SKcjaeJvbvxVmCVVIo0mRsZbeHSfvd3JVC1cDG3mnyFKyZVeNRZBYmKOKvFKsJysjg6o%2BzmrAAX9OBrN1HQg9KAVKq66wPik8r6uPCT1iQBH4jbAtCO9c7Gmb8KgVM%2BfqdTH%2Fyu9bWEasxz4a06Nd5xLnewJl9aLgT0WD2Vqon8Ot6IYncG62CUwRrSIF%2FgCGtkgnsnosow2zrYZMcO3HPU%2FiPwqxhxq40cvmkhMjI00%2FaV%2FG5xiVySOYQtkapLVRdU5HNTVb3sG3VWD28VlUA7vFWus3rbPl76oT28l06y2%2FaVj6ru%2BnC8vD4Cb%2FWFUMG%2FT4XH2hcKkKBASfsT6vpA4Buj1ydHk5BqNakbb68qVa4%2BFe7kXqsqkWWbd4sS5D7Nq8qnh9fhq6ASUbCGlDUMzYSvyueGPCTnI541tkrS2bvxqGrS9jZl7inw218N%2Fe75%2B2RdsdMygrCWQjrAh6pe8igqsjo4SsrB0VkV1VPprIau8tLvS92Xk%2BgMXVU0X8ZyaqQIe9z14TWS14fjYceRL%2B1585dWnQL%2FP5PsR790%2F%2BRHvwQRrA%2FU9YliQHhQVZ%2FkNwJPM6d8qumNqgkP%2F0mw8lE1zh7dUfyzR3fECSoZKDuzd6IZZrcwKtdQ8FVVjzwQWaTGlIj%2F8bZ2hrK8%2FmKhznTC9jV7MiHrLH2pir3s0qaWj5Q6KQe3zmoyT2uZzqoVE5InEAzWijBJLnFcKMQlb2pRH8sWpuLEltWH42E86rbr1I2LlGV43EFndIv7J6NbZDvXuNsHHvmrqvpgcshjZLvsG56mlmoIoIpQuUZV3SSUF1VlSr1JNtlU%2FLPJJlp9qqruehS%2F3vUolXr3DHZmdah6zyC%2Fm3sGfdu%2F353R5d2ebHiTzlX1GloX7%2Bisiscu11nlsp9izM7nFX8lu4aOEJeoD253wLdAkNfHqb%2B4Uzne1nzFunMl2j7LFl%2F1byOn%2FJ452FykRVV%2B%2FwUv3dqB93QSKHKdW71RtRSqWnUDmQP7T287sJ%2FL6B3bIU1yVbtd284wVNPqYwVwRMWR1T8ALqz12mMbzupQde2xzeesGEaAsoCZ%2B7I7D5y8HqqKTF%2B5qaqrs4r5U97TYn24Ui%2BMSl%2FL5w4rGd%2FUaKUyJBf1YbWjaZALrVXVx6m%2FuFM5Pr%2BN0IR9NxOqNnLKB6m1enX53u354H7lm700rf1vxKgKMUqcrYAU0Qq1jF6xzJjjwH6jGB6jaR4AQ964gTXA%2FzUUPFDv2r6dcu8vxEe%2BHv9Z62vgq7WUlzWibUsKgIsTMuWnqp7OqjUswt%2FeP%2FExJx8CD9Nqw5NRlPrAcBdU67668PbGCiq8837RST9I1ded8qspOrT6urVcqfn5%2B%2Bj4So%2BqOjPn0bQXVUcVbylY8MQuzMOLvLHqKgJ%2Faotc974YP33f44mOxUd%2BQXtZI8ZXERIvM6rq6ay2vyHKvOOP%2BD3f70P2ZwTFdQkq1P71dV%2F18N6uK6tRZeuDNcJ3rzr4ys9V6Ybqy0upij9VnFeLGzFqXMfGUzUvHTyrAXo3UF7W8PeqPBMsU6QUvxVqiFVVOPzcEKrq6Kx2LIoyh1%2FG74dfFt%2F7adrru4qu7qseXp%2BqpdYHE1IDGTUeXnak9k5sPkfXuV36Z4X%2B9Xf2vHMO%2BW4LelR1Tz2KPy8Pk9Pb%2FXrGsmM%2B2v4Gzp8YYrYjN9a7Y2eS5mu%2F%2Ft6bVJ1VlwJqkPepKi1UPRVd3fro43V1fa%2BjPt2o2k7QrQ3Z%2BA4dnVsNXeKUBzolL1%2BbDK7rU%2Fd6XTZELtRtroeDrMTsRDdVxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjBeb6o%2By0Pt5KEzRo61BQha4rq6dBmzsnnUdfrlhLodptTKuFmDVJLn0sd0ZGdafebSRTli2lRY0tO8OVCkMzSS0VYAfPQuvfUp3VeDG%2BiNKTVLFK3ZU7aM6KnDijC0TqWfiqSo2CGxdvO7TnwP7e2RBZwpo1jB9Nss3n5Eu3rMmwTX%2BdtTuaqr4lULqUjgBkOUvuaJT4gG7ntEQYW3qvxWdWaOgsrn8SpSdDAxm6CnAhXk3WKLNXSzKqWKU%2BVVGCxCXi9rBegxCbcDgJy73WXiOQzpbYhBUUKy5Al9TxZ%2BpD6nolyZQaBC1QcgsKloK4S79Y%2F4gKvIWCpm7TwRa3Pr271z2L1ZTe0ajwxWVTFnZSl9cVo5JMl3qq8r3WNSU5VVFTIKKhAlyMV5HVq9nKS9X2J9xomXApF8O0Ckq3lHKYaKHfDZ7unU0wykYMos4oZh1fpFI18QcvyS8vpwJH7%2BQrGPOqi%2FX%2Bo7EOtngJHDEi6L%2F%2Bs6hlU%2FD6CzWFkAqt1jpU9fZmf77wPSuKNxTJURXJp6cCXIyXk7WyVEWioaCnc%2FzgvKzvcsbf3lmuczj6G5UcJoZr7ez5%2B7b%2FraojcFPVijWdBE3gs1SqYquqRNyKW05noTVR0lxzxxrtADVQQkBb8QA4yaiRVjGqFKqipK%2BsJvamNFdzeR5bmse%2BCp930lWAvfEyslaWqrbu7DcFwcI3lIBq78TU0NTQ3olkXn5ZZrftQ6mrX4LAaDthLszH6iaGTa4KaZ0gHqcWFMJVlqq6Gha6AapXcHpzA2A%2B9y%2FWIqTUJ0%2FySZ324drbsueLHBt5BYmKm4AEFqw6G89CemT1w%2FuTtfJUjRf0n3HCo%2B%2BdPdC5iq1iBzqFgrAi%2FL26%2BW2rL74B0S0vUNwd91fBRFHzx7TNkOL%2FNcnu%2Fh83n6q6Ghb6qhf6AW3lAmD0F0j9pR0lQZ3a81a10iHJSLzUm9e%2FpRIXtfdACCJRo7YAeuPFHN6LfOvfklTWB7%2F%2BLe%2BzKk9V%2FV66%2B9KmNvy6qa37EiHI7otDd4QCa9F8aKImBUhkNY5MRVngeRKRjifZxqM3n6olvSrTPEMnQK1sAIyEG5liIXcATLtXVxooBCX40ttDEN%2FmjzQUr4MXg4Hm%2B6O5M1y7%2BhSTD4SzpPvQeOGt9Pq3vM8qjaq9s6e3UUa80qgahTzx6W2nt4UfjhK6g9DfgxxnP9%2BJzB7D%2B6ikuB8SXrEPKUSKfYZ731WOqtaYHXyNUQitm8%2FVPUMnQK18AIwZdXcATLvXglGwRa89kT%2F%2BeCvWeKUNIr7b%2Fpdn%2Fd3kUxHVC%2B9P1NKoauvk14gNLtTBZnFqW%2F3om1ngo8BHzaT9Q8Ps4eeEk20%2BB3vo%2FD0prRSwxlqvJdmdv6dQCbuMB%2FoqR9Xm3F3rB8CVyAAvlwC4OANMFwHUzQB3gbokPzh%2F%2FPFNuSlcxK%2BrEeSjELUYLyOqN1WHZmQ3Jza0EBtcEGgx7wp2AkmSGGaURUlymJjHPZB%2FvTH4d%2FbcXPJXS9YenlZaBcRIEBNL%2FJxn%2FlqJg82hnSQGbaTkeLeLydIgJQWcyw1%2F3Rlgan3UVHVUHIGB9lFKWq%2FoKkg%2BKlHdeGtMRlS%2FEMAf7955hpNV1RTFfwKhLYYpkcO0DmK%2BrmlBqNnzfHFgwb9GrQUbJ8GfH9QrCZjh5zReUbZ5C7R4i85IKZIe7iPEdF6tlT9AXV4ZYEHVUupTiqpxGahqZ55COsVyPGjMhsoZUhVuEYUC1cp61BaU31DOpsspEafyWxUrlW4L6tJN2VgB%2Fkghh6a0uX8w5o3nSQ%2F3gYmUcgacyw2v73NLz6HVpxRV41Iy8MtUCVj9ZwDGtNqzRf0TY8aMGTNmzJgxY8aMGTNmzJgxY8aMGTNmzJgxY8aMGTNmzJgxY8ZujsFqucCyqMe0eRbGjEmI2nhR%2FHG6FDdmTYPuyzRFFsxGn7Euw%2FqXMzQ8LucGaZThkjub4WXQkmmasrIxYyU5%2Bbrm7ksJ6coR7obNoDIUgX%2FNSo1DlOxuxtV32QT8D%2FgMRcKk%2BWOQRvmKgrSGoRNgjuA1djarJcu%2FXfgzuKpUq%2Fx57MRgjX6dmqhhorKyW1sW20ofqz5LDw%2F327dsPDLvLTS%2FWYrnS%2BJoZ1GwrvZM08R4nFand95Qtux%2B0ckDH00N9c6mvpCPkbgwbCAzmsaF1mHFiklUiBnIgGh3SqwTbbyorOjBqK2ZFHhJTaTVuaW4fJ2rVTd4y4ZTvbN%2BMp0C35UdP4prB1cxaw%2Bl%2FL0TQzNd2eM7Wa2VblPeAZe60pFBF%2B0fZbpYyll6%2BDgsJ4J4iTwNEms3SxV4kZ2D3sJd1vkks6V4viSOdhYF67RnmFQjd%2FuTO2%2FwH8n98sJACwjIeqFfVtDa923hbnyiHUjWte%2FLaB3l2FpnLV5UQW6rry2HDCmD4JavQB40nVsq1Dl4S%2BPFxovn1sGysmoFPsUaISwHAaxWdMs6Zfmw1A%2BXwnESbjglb2gUssrpU4QoMuhcUYfLXulhaWfp4fEa7bhGl7gzgLN2s1RVRBlWuGySUcjqhaesV6Vj3e0ZJZJV4OWqZY5xqTSf0p3Cui%2FtvlW%2BEA2lJIZf5p9RFSHC5LQ%2BvLX4EcnVdNd86SDXLMibAkc8FnTfQ%2FelwVvUeFRYbWZ87AO3PKnET9qhr01U2QJ8KHc6zNzjX1jaFQik0%2F5qN3ewtLN08bzlEyC7CkFY382mqnDZJIkaXnhaq1Kx7vakkdXB62qseJTuFObWYPAzFD0R4l6xD%2FEcf2xssSvLl2W7H1HiG9k4HGc4VguHkSv%2BOU3L7wHrL6OqwAeejwCWb%2BgxNHNunWIUmwyhHut0WNncjRfbc4r9yfzXdkXAbCtAXIySZbgcLOUst2PRruI8pyiGwmn1SFZZqnKXpVHDC08VN6Nh3e1JqZE%2BUSVk1SNqVdWGs3w7DEiv2FtiyMLB7rnOrMcjysrG4aEZHKvzAixX6XM3TlQZMQR%2B3dTpbRAmx7uyeycgXK2W45%2B%2BtwuSYu1CS0oSvm845SW3IQ%2BYhYAklapRl5uoz2o6qYcvplJYKSRTeaoW3rN%2FDOSNp%2BsQUrCFRFVnX0T7g%2Bi7psZKz1zR%2FeoStapq306uqNaWU1U7frc%2FtvdPibxomHNz%2FRdk4fXGo32TDjbOKFQNPBbN1V%2BeNMnv3BJiNfj11BbWIKNeTguq9vhOjCU4UWVqRrw3dG%2FnpO5NedvTqepgKWedW6eHL6bS0MzH99x8qrrvwT8G8sbTqUrB5uV13Eenuv3jTO%2FlnZWOF94vfz2jQ1TcoGhkymlmSLrU%2BGPHnoH55tniRzT2jCy87vjz4fWOsmCSRNWew3sneP2jykdfcC81%2BOKJQG0gK9ckalbUSKi8ijPVYQ8ihZAqxakcLOUsoftIv0rSta8PyLiFVF5ReaqibyZJw4kXnkpVGlZ3Vx%2Bn%2FcNM52VNuPh%2BA4%2Fx1zN0oqK9kxCPHLK7QanjNvTO2sFyzN13yaTKNpyNstW%2F7b8g0PKdXDBIwEwlTKoaWDXqkmOoocbnk0CgSEjDgwRai7p8Tlbcyys3V02rwx57%2FK2mqB4XY2ln6eKF4Cq8zuqkyLhVmqrcN2nDiReeGqvQsXqKiPpk9SAqzAw%2FFa9ndOTHWPWR7Tju9cydT6mwWM0I7rA67%2FRdMvzJjV3ZcF6wuCsr8sc%2BwfgTuEGU6NtW2ptF7Xvi5uELkwK0REIuyCaoHi%2FF0s7Sw%2BM1Np%2BDqUHjcnhZI9yVFvd54Sn0o2NLURR0yKrzsqbgfq0AzvC2%2F63q9YzHxSEg7Jk7tkN9HsqD7p0YyHRme%2BY2n4MkTqf8HFZzagv%2BuQF3dXCYWil6xYH9fPotlHcP7Gcrbh7eTVZqxi8fZCtVj72wlLMEyn7Nr8Tb6sUdsmmNl%2FM6X2l4mqMLd7XqaHGfg3I%2Bqemngy3NeKvrvKwput%2Fdt9p50MZSBD0hIOyW08gdBsOsOgX4DopKL2zMFMpJa4fUDsNWQLlu5d0VNxfvNDc14%2Bc4q1r12AtL0UrmKP6cVXiaevGNMXedKV7qoFyf1KOeBvZ6yKrzsqaoY4IGqKkyZszYjeh2qiuHNmbMmDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmLEym65O7%2FcNb59Dlp1cnvWvuA8FoEYxnda02A2oVVr3SlbMmlyuNM3p9MYZTaf3%2B4YXZ3EZMXp7JrOdWZ36VAp%2FoyzwEUhYfkStC3XBXMGdZ%2FT3fXj%2BPr0rWbHAAuhkTt7Mrobvb5ETbA24WrRYK0al01sani9qw%2F8rU34yL2pW7vK5OPNKG7tyXq3b7%2Bges9SJXQMZSn1Kxe%2BdoOkq2488o%2B0yGtSwJqNK3aPrpWoUBU%2B19k1A4tGvBCMw4BPgpU%2FfW4n6U4nK97ewh4ZY00JeBg11evllhR6QXKfXwbudXYXvnf1kE67f%2FGQTLrClly%2BEoNR4WEUKomYndtHrT7tftKaTHYtIiiR76CUQO5VrGOd0jzfegd9tvIPFkXzy%2BgidZHthoQbeirVeo9QfhcebFqLajkWnhjUcyoum0UJyXVe3%2Bqw9qF%2B5mtHDU0G8E7uGZij4MAggIB6F2W8eVdc1xxdxfwssH%2BsfX1zXbP8CdXqdy6p1eh28%2B5Dju7K49g7Xb%2BKaPRxZaeX3zn58D6eICg8SMCusPVaM1fK19pTyhQCoSpfYqguz3S%2ByBpvejQ%2B91HpN1tBc9xh6QxTlTMP%2FscNbVfUROhd8awUqXjgitpBcV9maXA0uqO9YVGpYgTULzlNrvUYZi3VcHZQx54MgrZ6XcSeO9m2%2FEsSjL%2FEHUb%2BdlFXYlaMqq0HJvUROWteuP1%2BoGlsUI4wNy400%2Fjq9Dl4canzCFRY1nUwQykf5rYEMEnx8AKmtwsO4wkJXezZbdVFGqb%2B4A7UuMYq0JHFGyA7tObTHAodJSGcpXPeY1Q7N4J41sOofPkPDfyPHw3X2WAHcWqHpJBGfIyo8yAYZHgPfkKtzUsl2uTFUagQ%2BSri6bRgRPiqnq%2BPGI4miKK7pCsnpW0amaMRz16n1NfUc1SpqUcq8liaahugm1%2F0mUOqI47vniptMrtNbGt5RlOGqMSr81BCrhyCvmjukGp%2B0FY9YfdNJlc6wwFsFUYQ%2F3nEQqFG9Wg1I6B7z%2B%2BT33ZmV1Qfx1p5WtopFc0KSBLxD1Fo5vulKVEu2ywurogaX23R1gZ2KGXChq8u3uuoLL6lP7%2ByxHbQsLmuhEFVkiXODT0hNZx0RND0tKe8r2L%2Fo%2FZNoMsF%2FuU6vg3f3L3J8V9ZRbj23DkdJVfkBO5OYJ6oSjweEaiys1Bl28O5m8cez%2Fs8G7Zlwv2WPrKj6JBP14LrHVgxHVBxZ8XNCWh%2FET4cxcOdqOgT8mJuocvyxHY4ibqlUVVNDZ5ycGnILx3Zlp4akQezbmLEYmcKYRugSQyvVliOLW0qWuPJUZf0ndjkt1DMHCUTubajTu9R1%2FXV6Hbz7kOMTtpg%2Fzt0wu5UglG%2FL%2F%2FcJotLq4w5o1XgR8Kt1iVn10AwmkxC37qcdi7tflDU01z1mtdDAMDeH%2F2vXnFXVB%2FAwh7ddEEQ61PjmguSHHM9qsWR30C8XHiue2lCooUdVVvPkU47nPPmUXDKoHXWmu2F0tGMa1V4IelncUrLEhW1D1CvU0je0Arz%2BvCOL4wYsfPqBOr3FaRaZTq%2BDd%2Fe6KnwUXnPg3G3lfJRYPu6WktCqj1793TGBXJcYI4HB0825lAkmmKSPJad7LDLAuFWIqj6ID92OLghjMAGPNYF62COqCm%2FrZ4X2TuCj108rqalRyuyTrRCS7yCCrhCVA6IG8xHFLM7My5fFLSVLXPm00u5bU19g%2FXmKqyub%2BmL3rblfOYrrNJ3e0vAio1Wp8iuH586OYXCSfbJJrbjo6B5b800sQqqPLt5OdBHxnODHd6oFSJcE2wRqlOa8rIUH%2FKxFiQy675z6EoWeTNLNEt%2BADDBEWCipa4%2Fatae2uJQLhU5vF1Wn93uGF2dxdXoKUuged2vVp1J4JxDWdRpa4Fua8x7Z3jMnn6V63Xl5srjXkyWuPFWFjmhOW7mm6K71dHq%2Ff3gx4yBjl2P9q%2FVdRgvdr9VCqCJdAWFbSha3mKz6RNW9W2PGjBkzZsyYMWPGjBkzZsyYMWPGjBkzZsyYMWPGjBkzZsyYMWPGjBkzVgaDZXN7TCsYM1ZICw1dWVC6QQmPPvtzn72m%2F6DGlfrg%2FDNqWUZc2dpzuOL3PW0xqhwm1PqMVtkZlcJBHsm8P2tcK13GNnkOD%2B%2FvvpO%2BHbsxisPqZ3TdT0lXFzf2Ye9sfDEIq%2BytySDoqfXOxj4kXWUMnTfI2tidv1evSQi8FGU%2F3qbRAUwjleD%2FPh18x%2F%2B98wrtj9KtsQi0Dl3a0gpwsU01Ta0CVY1kSfqyoDYx7f3UoPtlHse8f1m9R%2FDw%2Fu67aO1PoG6H1DPn1a1SOl4QFddrXydZdXVxI%2Bzh53D1IwoQ4kq%2Fh5%2BLqB0y1nilmfHrbD7X%2F09qqq4F2cz1D9hjWZ2y6aaDrJ0hldqhK%2FBzWi%2F87eze1wtEkX3P4TKeoAZBHINZDW2ZlK4AiHASrmMPI8Y8J3i7z1NLeJafYOWmKldbLGV8kY824rdC%2F0gp47aka2qVyNlwmbtEvlUoMnF6eIeoOenV0skqdHFhmS8s6hEKDBIdWlu%2Frwkwzz797NOop9acFxXzf4yBhXhOKWbvxIP7w0Bx1aiHzdH%2BRlXVnb%2BXdxwYKLcXuGE7y4scE%2FAPPtJ8VIYXY3wC1HcHMqDG9xK1ZWlUXSrmIV9clVcFBBkPR3sKjw2n6F2BrF7Q2wWdBd2F38laNczU7bh0fJGPNs5vWUjIzsjr339h6b0Ov6zb%2Fv5PQL897auEuMQLbXleYWvkvxO6uPFF%2FC6%2BqNLFdfSL7nrgrgccXSPZpbmgaFd2%2FCjr7jrULJUd4zYeyfVBk%2BvfiUrnwo3vRmGcFuLeXAsI4oJ3qfhX1%2FSmZXg%2BdqE85%2Bs%2FfP2HttQmaV8WvnGGeusMz%2FCUyV0LZbJSX8Q3CKkRfCYgYxoqj2sV1oA0ZtTxyCxKIKtVl%2FjcGV%2FEaJP4XDEWQaSE7u7oGvmVv%2Fm1pfe6dVy3%2FS2JTFzPnF7n6n4S1FC5aHLDySp0cWEwr4NmVOriOg%2FfTVX5xTsWcdQ%2BtWV0i3W5TdnPWcPWQRE%2BhhiOgOGr%2FikuFCz5oDvJpu9DAtpiHXfbakUHKfjUV7DivsUfzw2FxkbTq0D%2BczSNomUUojZe5LVROW9JfTTIeDz7k9Uu1UI%2FopZC1cLfq%2BsjiJokkRXlSHjsBi54OSyVzGEhrlIIVOhwZxRkNbr%2FiaX3%2BnhCt%2F1lio6P%2FAKyLkw3A0ClKu%2BeChVBc2R1dHQDjwUeU%2BviVlVh4IsHUlV8lo9JCXgYR7YH34MkVK78w%2Bv98a2frJvCG%2BudFSNfnPlJRvdNwoz2X1j1QGb1b%2FfZwlGwSUTN%2Bn9Jsr5JP3z3JY6%2F96Uk23Icf%2BqPFwmlnrkZe5yfifTMRdTbTsS43Bt33pXzsnEYHXHpP9UD7eniRJ3YvX2tfQdvlS9g06OqQ1SxaQmdrPE8Uf1Se1x5WcfpxweK7xRGwZryURVKa2j7yvuc7a9eP1VzOtlFh%2F18HV3c1vxWA%2FIAFSlafEjdanNX9uHnAguRfOlIJ3981O5vkYL78j1kfIPfvGoggyPi%2BVTn%2Fw7aJZ9P4cgJVwj64SGgTiMex3fMMVtpf7xIKL3wU1a9%2Bdzmc6z6hZ%2FaWz3UyYiKgakY4zefs%2BeVMf8HyLO%2Bhf9UXUEgR9Tmj5vssv0zwJWlqkNUGNe7%2BWxSvd2VQ1Y5Uf0cXFYj3Jug8E4H3tOPavzLhzG1L%2B5zjmwAolKVz8kLJV5zMZOujm5V1WrGD6So%2BCy9eH3%2FhWaXtH9X9nxKdUvYGHf%2Bnq1wlO390OdTvbNtLPA8nII3Fg881gaP3%2F8KiIcEyLuv%2FxCdhdVbB8NSPCaUgKJw%2FQf3P7gf7wbJJ9vvLLDQmQWJ745czTsO7O%2FMBhbKNapiSCTkM8cjuBFRkzQDXOy44hn4X4HvpwcZ1z7IL6d5d%2BNPug2nckQNOakf7wSXF1lVRF3q4JgJzonD%2BqSiQHPK5ehd2cG%2FKydVYUx92%2FsMaIOacsxVsRXd3%2BcnN7o6urpzVXxrGylI%2BoBAp%2FThiPFo306%2BcR2eI3%2Fom8%2B1wTiM73mty63gWLLHz8WxI%2Fa2E3f92Qq0MSGV7Z2JxhdSJzfi52bIdePXkxu7sjCK%2Bb6%2F3XAWpCFXiLrDllcrTm3ZcLZco6qgmi2HaW9EJM8Ao%2BPyZ%2FrZoMuFJZ0l77zDkPhtyu1WgF2UzLGcmXLhdyqyylrefb%2F5eZsrE0y7Ck6%2B5G%2FndalqBdp9znh0h%2FSVk6KDKWxTn%2B90dXH1qNp4sfvS6W2gTgd5S8xVqgWgT25EYoNoZn3ra7w%2BzjYa3g%2BddcBmVO8l%2FpD4w8B7h%2FYUpiA88ZCuuAeS%2BtsObWoDvKRGzR9jwm1VvhvDr6vsCKH5Y9%2FyO7B3FYrtOJ6CQGRHuUZVQbX8Jo%2BpgiDJ5xrq0cs9bvBx1TVdaVC8iAj5fad6Duo6uWvivLaR3S28xMqTuwnOmmwqJ1Wbj3rjYXirV4W11A5G1mRaurh6VO2%2BBE5Sk3Mrkogjq%2Fn4HiB3A87AemdpOrewTUIHhMBx%2BL%2BedI36TdAN%2FGwjkKhe1idHmd%2BjjCpe2nTbe42c2NU9p3JF%2FbnqUpO6bp0OUfkkYWRKbMQwMiWfrlTail6KhNTdATzTfmenP9ZP82YqVdde88Y%2F%2FJw6rL1OooqelK4rm2%2B2W%2BBQvlXSc5J851GTu1InXedW8xotTClIDZ1Lv%2BSQng1tWcvVbrVcsb80fVmp61bTRL0LzmjJzfhS8Km66jtnogXVLan7JxCFM2HXoeZNqAxErWijfQcftDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjxowZM2bMmDFjxoz9%2F2u4KsiaNO1gTOYkgWLZCarynNZV6uyy6zRcFwRkdJzX1iee%2F64%2BhRBIyIR81S6W3CtZKy%2BHR53neZrO8zLFT0NXdhn%2BH9PyuTN2Gx0sqydraWHlz8rYyAyt9KVXs7%2BJjBQLTzbfr0X0PUh2BQokTLBsuXhJvoED6LqNFxsvhph9BYoOXl3o2vjRBNN4jJlcMxzU6Azmya41r%2BcgsAakBv9R0VQdJkfnOUHUeV6O%2BLav%2Bv9p5JV9T9zzWzXescZ3caU0LHMMSkrX1kkubXlF1F7rEyWIzRaWJ1YI8UJ%2BvWSB16%2BJzg594yoW%2Fmr3rSqHCX6ZyHUDwY9U5a5rhvWhGVxmhkvQrMwqtq5ZXZvA853ZX3YnSRLZ1suo5rrhFOt%2F9umRqTbSWAaaCJdv%2F%2Bcnn2omdQbN7Mmnbv9nGAX66FQFXZ1v7QXyhNqM%2FsY5lA6rqfNcKr53VkjTlr98EMwJxT6M%2FjryNUUQRvgnSgQNv4nLHP3JnWDutsQDqSHr8kGmr5jYw%2BquIMkKxNnnZX7Ax187qszwETXn17HPiqka%2B4zguOmVi21fJv5P97%2FGGatWadrF3es8FX0iq%2BmdjbrwsGhXOdZYsTb20EsYH1DGow1HhS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2Fy8vL6%2Bvqfn5%2Ft7e339%2Ff29vbo6Ojz8%2FP6%2Bvr19fX19fWmpqbLy8v6%2Bvr4%2BPjT09Pr6%2Bv6%2Bvrr6%2Buqqqrz8%2FPt7e2ioqLPz8%2Fa2trW1taioqLr6%2Bvi4uL5%2BflVVVXNzc3%2F%2F%2F%2FW1tbj4%2BPh4eHq6ur8%2FPz%2F%2F%2F%2F29vb7%2B%2Fvz8%2FP09PTMzMz%2F%2F%2F%2F%2F%2F%2F%2F5%2Bfn19fX%2F%2F%2F%2Fy8vL9%2Ff0AAADZ2dn8%2FPz7%2B%2Fv8%2FPzp6em%2Fv7%2F7%2B%2Fvq6urp6en%2B%2Fv7%2F%2F%2F%2F4ck%2FmAAAA8nRSTlMAGgDUzwIP8SMQ759fCgUvqfDGFeIYA78fbxNTt98%2FhsV%2FBhdD4Q1rRI%2Bvwo3ATxJTD18IoKWasozTETbQ4D40IX5hC6dAMR7RXydvEsRuotKLkZCATYahkzOxQlFqmbZwJiUhFWy1wyJYcXI7gB2XIEFbgjxgiWFtfTSFMy8wSYgEqFBDTSE2KCpnSyZZUaZHRFAsDuWBYJJ7AVZQpC0Z6njBKWjdN4dlMV30iN8bV7%2BzJJeHMRiDYsR6U9yVYxdP2c1dj8CKFZZVFjtaaTxOI9cMKQk4NnBW4PKUOmiNI%2FkwWoQYUdQOSk6GvkUURFSM3n71h14AAB4tSURBVHhe7J2HfyPHmaa%2FYicCDTQCQRAkQWgABpMcDSkOw3CGM5o8Gk2QRjlZOVjBsizbcs5pndb22r7d23ybc7zbdDnnnHPO%2Bd6%2F4FjdIGu6vmp280CtbF%2B%2Fkkn%2Fnip%2BaPSDDqA%2BFOm7J3ncIoDi0NAQkY3d2IaJSws2NNZZnCouduhAsrgf7o4BYy59O4fvn3ROJQKoREkBGKqYytAJCCEQWh220I81TPFIozLaNiCMH4PJr47WIooL1C1isUUsFSwpkMqPAMARDUIFjLcYpj5tGbmqw%2BP6bhz49jZwbZ9S9k8Kd20QQLDdzFbdIz%2FJJ0OFyJFaI6mOcZ6HGOzAGxdi0tN8JL063CmJwi9FviX34m4FUrlxl0PgaBgIbrXJJfVp08yTrbq2tt99bINtCj9p%2F2TiZMMigCzYGa0WxwBgrEjxCBUici56obyLjsF%2B%2Fez8KGLwUdxVJuq9HZcpljX16lgjlaeg8hTpmUVNqubcUjzNKnBbGIBbJS6pT8nMo5ilAms3kxsAbElvsP0DqP2Ttt9KsEYIoBELpWxWDyHMocSDdUiCYMYDvJmAl5sUE%2BcDgiaiLMd6FrTJUmskFaTyEah8JPZsiru8WGL8ouLpx2rfqshkVQix%2Bz%2FOoyRIte64GalXsb5%2FJFX7J4UfxsVI3EUcMyrVrbqAtbVVB1x96q39f4Yo0goYpBJ6EmhWa31nx3WrUmskFaTyJah8iVSofNrqY2umHOeNsyIQ457ksUTnlP0dq4NfVyuLrpTKLlHy0sUp1UASq%2F2Txr2ASAiiwJvNYrVzBLjUbJ4BjlS0qbdE%2F%2FStUgAExAMyWG2jI2EFDd3qujNsWcPOesxquY6d1OOSmiMbId4YCTT%2BBEq0xDjRKACM8mO1HwF2mYm%2BDnRdrRRht5hUmRPHAeD4CdL3jwBEBQ3OheC84VE%2FXi2L1Q9fB14kOgFc%2F%2BzeVgmgJKuVTnzsPSh2iFoncY82uVrw14aH1%2FxCNVbszO4heYa0vDPk30uc%2F%2BOxv2LgBAAGdjSM8R548OvqoxHiUl0bYWyX7R8h1P5J22%2BHUIlAxXSl5FYDeZS67hHgTO%2F%2F2aoPbWy12r9JqFVifFsqsLYGbGtlJyq%2BV2TuBRrA3WTgs%2FAY70S30519XFebg19X3520%2BbakctBO2j%2BZ%2BNt23qsdwduyWCWnjjB1h%2FZvdWkqhPxKVhi3gMamh2Ilhn304xeIaTVJpVlsTp9FLRt3F9DPgvtmX1czbf4FSeXghcT9k4WXLYxtg8oYrLJRKZNTC7XWa7R%2Fq1RDCDfq7RltpDwixPTcjIdii1R87MYnptUktdKYn6Pz89ZSJj6l6k8NcA%2Bc9bqavvmF6jbdHqwW0vYP5%2Fq9dLGo7qVTrY5OXKnXr0yM7m3V%2BFzIAs4S0crEckCmBDOedY1UCmI3%2BtN0LjUucan0yDOycjD8PZk4VJDCB3%2B%2FqmmtSqlc68g2dUYKlLJ%2FUrgzMl73Gu3xESfFqorzwO0OsXiI4kmrCe%2FSRoQ4T3slOK2ea0qa001Tgci0E2TiQkVk5tHooO9XnYJDWcP3TzovT4xOL5dJixDqXz29gHhGRZTRIRogzT2l5mk6b8F%2BG5KhtyB5%2Fj%2B2mie3mie3mlvNk1vNk1vNk1vNk1vNrZbouy65VR8%2BsST3UJbGpopjJYZdoNsFXGOptDrpfAn9LGWvU5xaLJFvmr9Ycu3kzstYuiHrUuaUFsfGFg%2FyQOFa%2BHaCIAeHMNTnPgA%2FwSrnrg3UPPD%2B1R8AHnwQ%2BIEUq7xONv4w%2Brk7ex2vBhRhng9ks%2BoyGAXU6XYrROTzXnTg4PrRW3EAIQQI8tueVn3I%2BGarnNuoz4%2BOztdZ%2F%2Bpl4KWXgMspVnmdbHwWIgxm91XHA7JxiJ1A64jHvJg0WS0CmBqzWf3NLSG2NmGTnopCOm8l8RZKpNsDSbG0l1UfUXyjVcZLqE8EoGCirj1cC%2F20Eq3yOgjrML6wwHgLFoWxUGHzicx1iB4CQJy7Iee7S4biAw4QUM9k1XhodzE%2B1yRqzo2zk3YXkPZaZODoEJl48avVU5pVQQjFJltVUgHfZJX9N%2FDDuJ3Cerdr%2FasvA5icBPByolVeB6yO5B2go%2FOXdzpJLuAVVseuGOv0%2F2M%2Bce6EnO0uIRO3elPbciars9UyhSlXZ%2FkJvoVSCS3OaeNRCTi%2F59j7UGFc0J7XVSWVad2hpv5VEO9fPQXgwx8GcMr4CRybTHWg6ijungJOuRo%2Fhp%2BgMD%2BBw4Y6Xb3OrOSG1BTPdKxCJZNVfJn6%2BbKhTnMcGG9yTv%2B5Zrb6CQT4LLtQEAkBIRKtFgR2IgpZrDa8aEzvX60AQBAAQIVi6bdzEa9jA7aso3FnGph2NA58ncJ8HTBsz5%2FQ69QkD1OM9TmNju7yYsqxmtFqI46fo36eg8HSzwM%2Fb7L3fR6RkYPwfTdzQVBtOklWuT1ulfevCiH0%2FtV7sZt7zd1ovM5F4KKqozgBpHMA6BB1AIDNb0yuGOvIVPAk8YT1BztW3fq5rXMb9fZjcexEEwEHpjPw%2BLjxDPwH2xHgvIIPMy5EBqtCiBSr6f2rswAaQjQAzCbsFVYn2NwMVB3FCWD1AeC9RO8FADb%2FmZ6az7fzcf15%2BWr7BzhWnYnV5irr1gPtWCX9swSbQHOrXN5qck61ByTgfPY9DzUC%2Fs6GICfsbVXCFKtp%2FatL%2FY9pHQKAJUOZyUnwOnNzYR3GhWAcKmDzHbU9GfpsvfcpPsh11ZhNZXVTG5qbt6hJ8l%2FOT%2FeITPyjX6l9kG8mqe0cwGp6%2F%2BrdAHCd6Lr%2BewKopNbh3Gx1kDoET%2FHBrqvGzCmrc6QlGFFA480k3jxdZpsJEoCgeE8lhfdQQ2JocjKj1fT%2B1RoAvJ%2Fo%2FQBQS7fK63CeZjW9TsOrM14dHW%2Br%2Ban6vF3qZbJKyurBpGnQQpicNDY0E4aAXnQC73%2BNh3XZsv5V1ow6RzQnv4%2FyMjJZ6nDO64jMdaZHJxgvUHnZND%2Bh%2FuguHdXmU0KEUF8PPpES0esZG5pJDAkxdDPOk%2FdC5Mmt5smt5smt5smt5lbz5Fbz5Fbz5Fbz5FZzq%2BYGw13usyHXNjcHKKrHZwuvpKWLinmDsECGlAwdND5R2vIg39VWq0atfV5Y14fs2ryIktVqjbUepmUW9zI2CUyes9AlnvJZtEfiaAEL%2B7OabBqJQ619rSnT4jwKiCHaRaD08MdFvVDnWhVXWpm9jFYrEf5AwoYQz1INNQZ7QG91GJfJkH%2BGBzSyghWyJoUAhJi0SIXRAaw292W1eSBWE4uI3YAIGAOYVsWl1sGsvhLhY3FahN6SqXLs0xZKxud5QurmeQee0xGIRnrRD%2FVGFE6iJKIQj0gdYsjI1RCzKhErnWrVj3Hy0Y3OwCDaqx2Ya92%2FVeBYhK8DbLplAbcC7MT2vh%2FEMZPVyhraZAjgMGRe9S2RQiWJg519D%2BoMnPi4e1n1oReZJXLHKtJqNUFrNaZ1EKuzIswstzp%2B6dK44Vm%2B3Ah%2BCmiZ9%2FsDxFNBnX6%2FrTYVHuwMvJBmdcFs1YdmtYp7yLVRdEFUSNBaiGsdwKqKxq0vAF%2BwuNVTn%2B68buH7uQqxdRYnXWL5XXxtYKtChfHEgcHPwKEeSixPJO3BZHVdt1oQc64NwEZM3zqpxPn6%2Bpth9fiLwIvHmdUOwswaVDTPb%2BB%2BYnkYP3dwx2rmu6XWQZyBhdgogHj5XYTChhCm%2BoWqZtXttn4EYW7Wpy%2Beqbi%2FXshk1dqy9mMVH9ja%2BgCY1YcsIcQW0DGp%2BGkcJpYbeGlfVktAaXCrzYM5A6%2FQ3lZpJWE7C9UYr0wBP4kwSh%2BTKrmSmsWqNdwctrhV0Q%2B3ipMnway6eF7usjYe4lZbpRpeIBbge%2FZlVZnI0nyXOjD4PTCHu8hk26tvh6gQ5ypKH5MacSWVW63G9VnDTriYLnNRhEyLdWSaWzLX8AU5%2Fkn98zpXwW6X1Mj%2F0NkCFhKOym0emVgYbKXag74HNtchGGyPTmyH2VbZ1adLVbykpGpW41xKJalV34qd30KwjkxjS2YX4WLXFfY%2BFmEakz3SYpt%2BH7lSXWFHJVud%2BvfXanNAqzxpj1vQpSpeLmQ7VUmpUivrTw9EmDJlyty25SD6oVHD404zqTQiMaOF3R%2FS%2BIboZ6Mw4PrDB3UGFpRchxTkSX3cwePQd0ZW2P8ZNHkvRJ7cap7cap7cam41T241T241T241T241t%2Bq2aOAs0rdVcquuXawYFrpdTF6%2Fl6eDJUqOu0SDxvdpH8mtus8eR9HUnQ3ftK4vANslPSdxisOlKcjZ8uc6jI9Ryzy%2FWKEuq%2BUn9KOHW5VA%2BVASn%2BrQAcR2wy%2FJvAWwoYjyuD4vFDnwTdi33ZhV1z55ybJYx0B9sw2UDOvrRqK0dAHcZ16C2xp2T1ywntO4d3aCcJXPH696M4EPm0s1aQWkISRQPpTEgcUWGQKAkLknBtIRlFbGm6yUokyeHDJyGLT6QKRVTcPJS8P6Wq%2F1ibnlNg4b1tcFwHR3jOunn8KmEGLkhG3fMeJofPR8yQcWXX1%2BuTAa%2BMAFTWpBAKLAtALSEBIoH0riAIrdwa1KEVA2OAfMQyZ5csjM14llHX2tahqOX2PLSr0%2F6kkwrK9r6ts%2BFcKaq1eZix7h%2BAnG%2B4uZr%2Bl8oUK%2B3p3hLiJURVhkjyANgQzUOJTEIWN3BrUqRSgbBs5KKcrlySHOE1tXIq1qGl8V1MPh0KJlWF%2FX0AVYQjuk9xuvb7CGTzB%2BP6w6UL1D4wsoLrLttrEbW7cRjpGR8iFXcaMl3x3UKmxlw8BZKUWZPF6IS%2BVauVSVNjDWHQMu8PWBI6u1%2BEFc%2FaTBNQE7Um3Gf3RrZMIbLzgaf6cHKTV%2Bgr%2BgrF4w2iAj5UNrGmeWpga2GmXNzHkpjbKXsc22v5HUutIAsDbEpao8gCg%2FxtcHJsn19XV%2F7kGE4VafkvVtMF5oEp0ul3QezHhSKvTXYfSpJ%2FY6BSylSKd86A7FjZaqzwxsNXqEOxI4K2WmI2InI3z7fTLGDx93KHxLY5ZKvQ3IbDYN6wMDgLa%2Brnf5i16C1Y%2BMb9cHGJdp%2BpwHMxsFAkjTGg3qUgkYlo7MlA85ihssWZMFZ1Cr1rA6TgycWzVTFcP2%2B4lSh50hoqfkWxopleddFoD6nGl9YAD6%2BrptrB2SuE6xNNClubLjdtFgfDtmHqworrRG72x0qQSEokzUOJTEw7daI71B75akTyXVwFkpTrlVrjVZ6hDRZZy8ZJZKzkUPjTNkWh%2FYsJL%2BxzzIeLfH8Z3YyZ0D8eS2ZSAUlUD5UBIH2qfPD%2F7ORvpUUg2clTJTocK33%2FzOpi91iFqwfvCaQ%2BYEM43H1FjKerzN01UPqJ4O4nj1XAMyjXOrA%2FHktmUgFJVE%2BZBELueNyeVmQk8mZW7dJ2nI5VIljwaZP0Z5uFZzU34kdYiubY2cdygpwbRylLoeb7MwKkSB7ZjVaSEzvToYT25bFkK1IXPKh0LkcD7dowNIVNkx8ugLO%2FY4TddqbsqPpA6R06TvvORxEnDeCzFo8l6IPLnVPLnVPLnV3Gqe3Gqe3Gqe3Gqe3Gpu1dzf%2B5Zx1ShxcPUHT2uqktR9uN%2F4ST9UWThIq65taI95S7gaAsyddTWPzc%2FCB85JnHT3ZdVuUULel2C1UsTCYK8at0XAUMsNrdqm9pi9uQd4%2B5kPq569Prk%2BgOISkaEPeXS%2BDns%2FfJzXJ2oplMnGAoC1fVlV28%2FkGVX529x750BW5YcvgEox7EYrAYAQrL835ICJW09Xq09b5vkNGPi5kYl5jbPHVVmrjQMfqpWI9SE%2FQvTIRB0lnQdEgZlXarw%2BLRVBaTZ4o3opu9XOVQALCVK9%2BaqxkjcTDGT12RqKQBG1Z4eIDgMAEevvlVyGc2%2FYKRScYc8033pmHIxbq1crgZWxPrm4qwyc%2F1CN9D7kCnwfldtxTOPRRxc4j3biuOLqyKOEmGy0apCptTJa7RYRxnTc3yvlFYxWpdRBrDZnPIQvjuYQUQ0QgkgIredTchnOo5PRGufWZH3Y%2BVmPceDUZ12Ac1ld5zt%2FBF1G60MOqkA1CLxZjdPVlo01zkOpM%2BU4b9kpa5oxGyf7%2FGQ2qz5UCyrLyoaSp1V6KKVtKfvirkNEDWCH1khlL74u8Trnl3oTTqXIOXBnbw0mTgSdQ6bXg4zeh7wePrZX0%2FjVsF%2BS8UhqoPEppFhlNkaEAKA3cJJtvi3oYCfWY4a73BUu1Q%2Bri8JBWj0UjbP%2BXsllOPfCRtc7PJ3L%2B8RKMXsd8%2BOKKzgngMmqJ4TWh1xBtSq%2FHtL4j1uyC4vxUiRV449ZKVa5DfNBecmDjHcpjh9FYyM81VSHg5S7XHZXPJBVMe9J2JgXQ0Rvi8ZZf2%2FIARO3Xd93bc5hd4rmOkIYuSASOienWisBf7J2F%2Bl9yMF8oTAfHNHrHHGGq8MOMY5Qqs6D4SqApHUDlY1Uq803IPNGM46xOb3S60F9JIHd5Wa7K%2B5vjcj8B%2Bdbxei9SbE1FPb3yrD%2B3r14ESgmzR%2BUE93xaQC1u8q8D1neA4%2FxOmO%2FUHAqBo67AmKcnMK4B0qIspFqlVY3AGysanRzTgJrppx2l8vvige7W7pmeTPAjGddG%2Br394L19751nJzCFeDpsrEPucjmZ%2BdK%2BIxFhjAbKVZpxYK1osO56MGDlLtcdlc8sFVn%2BHQABKdl735Cf%2B9bwtUQwOBB1g%2BGiYfZSLVKFxuXyBwn5S6X3RUPbpWcJgkx1JS9%2Bwn9vW8lZ82xB1%2BfiU4ZEOYNCqablDXqLlfXGuz1M3kvRJ7vZKt5cqu51Ty51Ty51Ty51Ty51Ty51dxqntyqe5W%2BrZP3A3dhd4g6NrpkSqc7BibV%2FgjtM4twDXRsjIyxYXMI9dUcn7Lk1VdfVd%2FexFSAA18nOXs%2F8GGrhoUF1KzDxOyVbAAvMKv34RNkSGdxbGyxY%2Bb%2F%2Bs84xFKCefnoFoCUngEebT3LoppfjM265ZZb1Lc3Ma94IgbcItsUxlPWSWZWk%2Fty8fyMBXgzzzN5lSkAaH%2BNDdTwx2jM1aC7iDCLrpE%2F0XLZ86kBNZd4mvuwiv5f%2FAwt2sb5yGrV9d3kA8b3GfUN9Yus0YdvTzrn6ySbrZYAWEJYAEqs6tGjkDG8iBrjj8Mj1oh1N71g8xZ6dTLg%2FHvvk1w75Ot13JexOUCoMNvFViQVFzJYnZubU9%2F44svmAyb6ptNCFWHM%2FVvvT9p%2BkdFqtE4y36DIqi%2BtHo6a%2FGp6X64AgNtuAwBBsawB3tnpf6e%2F6Ih%2BE8DCC9p1%2BAjaaABAFUdM%2FE%2F9Zcm1C8%2FHPw5UiMUF4GY8VoWY96zXZfuIQLWQwSoA9S198WX3BqRAH8AN7TBadAv8L36%2Fhp28lO1YbTDbKuaO1cgq%2FKFIJ1yXrwGrrLLzrHX661PsRbfUbQKsTBfWu%2FHRNoAfs9Dl%2FI87KxZ7HWwCm8o1270Zr6vB6T8ddRkqqZmtmhdf5qsJTmktOoVJQCw7hl3%2F09jJV7JZ%2FWAJKsUUq%2FrfgG4AwFNP8fV%2Bj27nttvkV%2F1Qsi4egcwXY%2FzyjxKssFqLVB7Edae%2B9gBQb17Hgzfz49v8d%2FAXiUKuUkLjV4FfbaBkasYDipUYhdj9h7T8QhHe2%2F820TrtzyqX2kjSyhYX7QHmXf%2Bz6KfRzGS1UT4FlXtSra6ryevJ%2Fbp0224ols96zxchU9c3bwrX7wSA10llro7umXcA9TNd1Odi3Jf8E%2BTHOLk1fMZpt53PoObqUtsA2kpryrFakVJPFivqHjijVSa1Ol2VWolpZVKJkqwGHqI8SZmsfrADFXzRZJWvnyyDaoH166afgXuHEMY7wzfvhVUA6N2Mz1i4f0KIiadgndH4kY9b6HU1fh%2FaPXr8ceq1tcWwi965ZQDL57xilmM1%2BszJb9b023sPO9Hu9uqA36n4QDum7gLkbipUgQvEtTKpBCTcqI6KMN4ns1ktPwqVapNb5Vqj62q1wPqB0626dv%2Fm52mHLeiOBypyRHvqbUwtLEyhPezEeRXAn22hGuMdeB%2BLtvpjHjqx%2BqdXZfXK6ul20rHK%2B2%2FDjxTFhIwKwLoiZEbJ2Nb%2BOFvnVH3TtUYbzy35ScveVvCJbFZbUMGXs7yzKURWC0OsHzjdqn18a1rMzwvWDP2xBsZ7D7GVyclZnnzyHe94cnLZ0Xhh8vfwR1%2FU1s4%2BiSj880rLTYrelzeXsxyr0lpAFIyyNd1hXuS6XEeYepmvc6q%2B6c%2BBVYLSKqVyTc9ls3ofVKxeyjrJrBeC9c2mWD0%2B3CQKAmJpPrNVJlisDlFveWJiuUfE%2BGv4B804ryCWCsXSmBfzjf3%2Fbiku1Y2k8pzZ8ABv4wwNFBGlwF4HTYFtDuFks1qDyvNp6yRzq6pvlm%2Fe6ip7uzTs7NFlTGKkTNmzIgKNBCIWbXg6oGA6bclrngJbG9gYZ2VUiNEVh96sCCmdwYQnMCpUmJtC4YB7IRz67kneC5Ent5ont5ont5ont5pbzZNbzZNbzZNbzZNbXZhaiIPcagtRii5ljQsYJy%2B4rnn3dlGkNzH4KFomHIbz0liR9T8fKF%2BcmlqUnMcdA7qUKXt0xNqAbZgeWu3%2FwFfRz4%2BQKa2rLUOTAYoV0%2FK0tg1qceFu7SzMi58i4Ul2i6a9VUzYIWiimdnqm7%2Fu8amv3XPna5LzHEFjck6C9P7kvZrRhICBhVZFNPYw%2BnmYWNzSGH7lGjR6yrhW47OwJbfxLOm53%2FspZhX4w8AFcXTDcJh1pn7jDRAL3viNqY7RK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<div id="immigration-and-netgrowth" class="section level1">
<h1>2. Immigration and netgrowth</h1>
<pre class="r"><code>source('R/functions.R')</code></pre>
<pre><code>## Loading required package: phyloseq
## Loading required package: reshape2
## Loading required package: ggplot2
## Loading required package: gridExtra
## Loading required package: grid
## Loading required package: dplyr
## 
## Attaching package: 'dplyr'
## 
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## 
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union</code></pre>
<pre class="r"><code>source(&quot;R/core_community.R&quot;)
source(&quot;R/net_growth_rate.R&quot;)
sessionInfo()</code></pre>
<pre><code>## R version 3.1.1 (2014-07-10)
## Platform: x86_64-w64-mingw32/x64 (64-bit)
## 
## locale:
## [1] LC_COLLATE=Danish_Denmark.1252  LC_CTYPE=Danish_Denmark.1252   
## [3] LC_MONETARY=Danish_Denmark.1252 LC_NUMERIC=C                   
## [5] LC_TIME=Danish_Denmark.1252    
## 
## attached base packages:
## [1] grid      stats     graphics  grDevices utils     datasets  methods  
## [8] base     
## 
## other attached packages:
## [1] dplyr_0.2       gridExtra_0.9.1 ggplot2_1.0.0   reshape2_1.4   
## [5] phyloseq_1.9.13
## 
## loaded via a namespace (and not attached):
##  [1] ade4_1.6-2                annotate_1.42.1          
##  [3] AnnotationDbi_1.26.0      ape_3.1-4                
##  [5] assertthat_0.1            Biobase_2.24.0           
##  [7] BiocGenerics_0.10.0       biom_0.3.12              
##  [9] Biostrings_2.32.1         cluster_1.15.3           
## [11] codetools_0.2-9           colorspace_1.2-4         
## [13] data.table_1.9.2          DBI_0.3.0                
## [15] DESeq2_1.4.5              digest_0.6.4             
## [17] evaluate_0.5.5            foreach_1.4.2            
## [19] formatR_1.0               genefilter_1.46.1        
## [21] geneplotter_1.42.0        GenomeInfoDb_1.0.2       
## [23] GenomicRanges_1.16.4      gtable_0.1.2             
## [25] htmltools_0.2.6           igraph_0.7.1             
## [27] IRanges_1.22.10           iterators_1.0.7          
## [29] knitr_1.6                 lattice_0.20-29          
## [31] locfit_1.5-9.1            MASS_7.3-34              
## [33] Matrix_1.1-4              multtest_2.20.0          
## [35] munsell_0.4.2             nlme_3.1-117             
## [37] parallel_3.1.1            permute_0.8-3            
## [39] plyr_1.8.1                proto_0.3-10             
## [41] RColorBrewer_1.0-5        Rcpp_0.11.2              
## [43] RcppArmadillo_0.4.450.1.0 RJSONIO_1.3-0            
## [45] rmarkdown_0.3.3           RSQLite_0.11.4           
## [47] scales_0.2.4              splines_3.1.1            
## [49] stats4_3.1.1              stringr_0.6.2            
## [51] survival_2.37-7           tools_3.1.1              
## [53] vegan_2.0-10              XML_3.98-1.1             
## [55] xtable_1.7-4              XVector_0.4.0            
## [57] zlibbioc_1.10.0</code></pre>
<div id="load-data" class="section level2">
<h2>load data</h2>
<pre class="r"><code>biomfname = &quot;data/otu97/netgrowth_seqs_97_otutable.biom&quot;
netgrowthdata &lt;- LoadData(biompath=biomfname, 
                          mapfpath=&quot;data/mapfile.txt&quot;)</code></pre>
<pre><code>## Warning: No greengenes prefixes were found. 
## Consider using parse_taxonomy_default() instead if true for all OTUs. 
## Dummy ranks may be included among taxonomic ranks now.
## Warning: No greengenes prefixes were found. 
## Consider using parse_taxonomy_default() instead if true for all OTUs. 
## Dummy ranks may be included among taxonomic ranks now.</code></pre>
<pre class="r"><code>ids    &lt;- as.character(c(94, 97, 99))
fname_template &lt;- &quot;data/otuXX/netgrowth_seqs_XX_otutable.biom&quot;
fnames &lt;- sapply(ids, function(id) gsub(&quot;XX&quot;, id, fname_template) ) 

datasets &lt;- lapply(ids, function(id) 
  LoadData(biompath= fnames[id], mapfpath= &quot;data/mapfile.txt&quot;) )</code></pre>
<pre><code>## Warning: No greengenes prefixes were found. 
## Consider using parse_taxonomy_default() instead if true for all OTUs. 
## Dummy ranks may be included among taxonomic ranks now.
## Warning: No greengenes prefixes were found. 
## Consider using parse_taxonomy_default() instead if true for all OTUs. 
## Dummy ranks may be included among taxonomic ranks now.
## Warning: No greengenes prefixes were found. 
## Consider using parse_taxonomy_default() instead if true for all OTUs. 
## Dummy ranks may be included among taxonomic ranks now.</code></pre>
<pre class="r"><code>ids &lt;- sapply(ids, function(id) paste0(&quot;otu&quot;, id ))
names(datasets) &lt;- ids

sapply(datasets, function(dataset)     sample_sums(dataset) )</code></pre>
<pre><code>##         otu94 otu97 otu99
## AMPA636 75041 75041 58297
## AMPA642 71365 74533 75041
## AMPA645 74533 74369 74533
## AMPA648 70859 71365 74369
## AMPA635 71700 70859 71365
## AMPA644 62439 65911 62439
## AMPA639 75525 71700 67449
## AMPA649 74369 62439 65911
## AMPA609 65911 67449 75525
## AMPA610 67449 43673 43673
## AMPA640 43673 75525 71700
## AMPA647 58297 58297 70859</code></pre>
<pre class="r"><code>sapply(datasets, function(dataset) sum(sample_sums(dataset)))</code></pre>
<pre><code>##  otu94  otu97  otu99 
## 811161 811161 811161</code></pre>
<pre class="r"><code>sapply(datasets, function(dataset) sum(   nsamples(dataset)))</code></pre>
<pre><code>## otu94 otu97 otu99 
##    12    12    12</code></pre>
<pre class="r"><code>sapply(datasets, function(dataset) sum(      ntaxa(dataset)))</code></pre>
<pre><code>## otu94 otu97 otu99 
##  2214  3609  5584</code></pre>
<pre class="r"><code>min(sapply(datasets, function(dataset) sample_sums(dataset) ))</code></pre>
<pre><code>## [1] 43673</code></pre>
<pre class="r"><code>resample_depth &lt;- 40000

rarefyDataset &lt;- function(mydata, depth= FALSE, seed= FALSE){
  mydata &lt;- subset_samples(mydata, type == &quot;WW&quot;)
  mydata &lt;- rarefy_even_depth(mydata,     rngseed = seed,
                                      sample.size = depth, 
                                         trimOTUs = TRUE)
  mydata
}

WWDatasets &lt;- lapply(ids, function(id) 
                    rarefyDataset(datasets[[id]],
                                  depth = resample_depth, 
                                   seed = 1234))</code></pre>
<pre><code>## `set.seed(1234)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1234); .Random.seed` for the full vector
## ...
## 1058OTUs were removed because they are no longer 
## present in any sample after random subsampling
## 
## ...
## `set.seed(1234)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1234); .Random.seed` for the full vector
## ...
## 1728OTUs were removed because they are no longer 
## present in any sample after random subsampling
## 
## ...
## `set.seed(1234)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1234); .Random.seed` for the full vector
## ...
## 2560OTUs were removed because they are no longer 
## present in any sample after random subsampling
## 
## ...</code></pre>
<pre class="r"><code>names(WWDatasets) &lt;- ids

lapply(WWDatasets, function(dataset) printDatasetStats(dataset) )</code></pre>
<pre><code>## [1] &quot;number of plants: 3&quot;
##      
##       2012 2013
##   HJO    0    2
##   AAE    0    2
##   AAW    1    1
## [1] 240000
## [1] &quot;total reads: 240000&quot;
## [1] &quot;number of plants: 3&quot;
##      
##       2012 2013
##   HJO    0    2
##   AAE    0    2
##   AAW    1    1
## [1] 240000
## [1] &quot;total reads: 240000&quot;
## [1] &quot;number of plants: 3&quot;
##      
##       2012 2013
##   HJO    0    2
##   AAE    0    2
##   AAW    1    1
## [1] 240000
## [1] &quot;total reads: 240000&quot;</code></pre>
<pre><code>## $otu94
## [1] &quot;total reads: 240000&quot;
## 
## $otu97
## [1] &quot;total reads: 240000&quot;
## 
## $otu99
## [1] &quot;total reads: 240000&quot;</code></pre>
<pre class="r"><code>data.k &lt;- SampleEvenDepth(datasets[[&quot;otu97&quot;]], 
                          depth = 20000, 
                          seed = 1234)</code></pre>
<pre><code>## [1] &quot;sample seed = 1234&quot;
## [1] &quot;subsampled at 20000 reads&quot;</code></pre>
<pre><code>## `set.seed(1234)` was used to initialize repeatable random subsampling.
## Please record this for your records so others can reproduce.
## Try `set.seed(1234); .Random.seed` for the full vector
## ...
## 450OTUs were removed because they are no longer 
## present in any sample after random subsampling
## 
## ...</code></pre>
<pre class="r"><code>print(sample_sums(data.k))</code></pre>
<pre><code>## AMPA636 AMPA645 AMPA649 AMPA642 AMPA648 AMPA609 AMPA635 AMPA644 AMPA610 
##   20000   20000   20000   20000   20000   20000   20000   20000   20000 
## AMPA640 AMPA639 AMPA647 
##   20000   20000   20000</code></pre>
</div>
<div id="core-community-in-influent-wastewater" class="section level2">
<h2>Core community in influent wastewater</h2>
<pre class="r"><code>coredataframe &lt;- calcSummaryData(WWDatasets, ids, core_cutoff=1)

OTUtotals &lt;- group_by(coredataframe, identities) %.%
  summarize( &quot;totalOTUs&quot;  = sum(taxsum),
     &quot;coreOTUs&quot;   = taxsum[ corestatus == &quot;core&quot;] , 
     &quot;percentcoreOTUs&quot;= round(taxsum[corestatus == &quot;core&quot;] / 
                               sum(taxsum) * 100, 1),
     &quot;percentreads&quot;   = round(readprop[corestatus == &quot;core&quot;] *
                                100, 1))
print(OTUtotals)</code></pre>
<pre><code>## Source: local data frame [3 x 5]
## 
##   identities totalOTUs coreOTUs percentcoreOTUs percentreads
## 1      otu99      3024      309            10.2         83.0
## 2      otu97      1881      242            12.9         88.1
## 3      otu94      1156      157            13.6         92.7</code></pre>
<pre class="r"><code>p &lt;- plotCore(coredataframe, cumulative = FALSE)</code></pre>
<pre><code>## Loading required package: RColorBrewer</code></pre>
<pre class="r"><code>otuplot   &lt;- p[[1]]
readsplot &lt;- p[[2]]

pdf(file = &quot;figs/ww_core40k.pdf&quot;)
grid.arrange(otuplot, readsplot, nrow = 2)
dev.off()</code></pre>
<pre><code>## pdf 
##   2</code></pre>
<pre class="r"><code>grid.arrange(otuplot, readsplot, nrow = 2)</code></pre>
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" title="plot of chunk unnamed-chunk-2" alt="plot of chunk unnamed-chunk-2" width="672" /></p>
</div>
<div id="abundnace-of-top-10-otus" class="section level2">
<h2>Abundnace of top 10 OTUs</h2>
<pre class="r"><code>ds   &lt;- WWDatasets[[&quot;otu94&quot;]]
ds.p &lt;- transform_sample_counts(ds, function(x) x / sum(x))
n    &lt;- 10
topNww_otus  &lt;- names(sort(taxa_sums(ds.p), decreasing=TRUE)[1:n])
topN.ww      &lt;- subset_taxa(ds, taxa_names(ds) %in% topNww_otus )

print(formatAverage(sample_sums(topN.ww) / sample_sums(ds) * 100,
                    decimals=0))</code></pre>
<pre><code>## [1] &quot;63 (+- 11, n=6)&quot;</code></pre>
</div>
<div id="compare-the-top-otus-in-sludge-and-influent" class="section level2">
<h2>Compare the top OTUs in sludge and influent</h2>
<pre class="r"><code>plot3 &lt;- compareTop20AsWw(data.k)
ggsave(path=&quot;figs&quot;, filename=&quot;top20OTUsWW_vs_AS.pdf&quot;, 
       plot=plot3, width=8)</code></pre>
<pre><code>## Saving 8 x 5 in image</code></pre>
<pre class="r"><code>plot3</code></pre>
<p><img src="data:image/png;base64,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" title="plot of chunk unnamed-chunk-4" alt="plot of chunk unnamed-chunk-4" width="672" /></p>
</div>
<div id="overall-comparison-of-the-diversity-in-the-wastewater-and-activated-sludge-samples." class="section level2">
<h2>Overall comparison of the diversity in the wastewater and activated sludge samples.</h2>
<pre class="r"><code>ord.cca &lt;- ordinate(physeq = data.k, 
                    method = &quot;CCA&quot;, 
                    distance = &quot;bray&quot;)
print(
  plot1  &lt;- plot_ordination(physeq = data.k, 
                            ordination=ord.cca, 
                            shape = &quot;plant&quot;,
                            type = &quot;samples&quot;, 
                            color = &quot;sample_type&quot;) +
  geom_text(aes(label = pair), color= &quot;black&quot;, size = 5, vjust = 2) +  
  geom_point(size = 5)
)</code></pre>
<p><img 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" title="plot of chunk ordination" alt="plot of chunk ordination" width="672" /></p>
<pre class="r"><code>ggsave(path=&quot;figs&quot;, filename=&quot;CCA_AS_vs_WW.pdf&quot;, plot=plot1)</code></pre>
<pre><code>## Saving 7 x 5 in image</code></pre>
<p>The CCA splits the samples by sample type in the first CA and roughly by plant in the second.</p>
<p>Add run model</p>
</div>
<div id="calculate-net-growth-rates" class="section level2">
<h2>Calculate Net growth rates</h2>
<pre class="r"><code>source(&quot;R/net_growth_rate.R&quot;)

df.netgrowth &lt;- calcNetGrowthData(data.k, k_lower_bound=-0.2, seed = 1234)</code></pre>
<pre><code>##      
##       AS WW
##   HJO  2  2
##   AAE  2  2
##   AAW  2  2
## List of 2
##  $ :'data.frame':    18954 obs. of  6 variables:
##   ..$ OTU   : chr [1:18954] &quot;0&quot; &quot;1&quot; &quot;2&quot; &quot;3&quot; ...
##   ..$ sample: Factor w/ 6 levels &quot;AMPA649&quot;,&quot;AMPA635&quot;,..: 1 1 1 1 1 1 1 1 1 1 ...
##   ..$ prop  : num [1:18954] 1e-04 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 0e+00 ...
##   ..$ type  : chr [1:18954] &quot;WW&quot; &quot;WW&quot; &quot;WW&quot; &quot;WW&quot; ...
##   ..$ plant : Factor w/ 3 levels &quot;HJO&quot;,&quot;AAE&quot;,&quot;AAW&quot;: 3 3 3 3 3 3 3 3 3 3 ...
##   ..$ pair  : Factor w/ 6 levels &quot;HJO-1&quot;,&quot;HJO-2&quot;,..: 5 5 5 5 5 5 5 5 5 5 ...
##  $ :'data.frame':    18954 obs. of  6 variables:
##   ..$ OTU   : chr [1:18954] &quot;0&quot; &quot;1&quot; &quot;2&quot; &quot;3&quot; ...
##   ..$ sample: Factor w/ 6 levels &quot;AMPA636&quot;,&quot;AMPA645&quot;,..: 1 1 1 1 1 1 1 1 1 1 ...
##   ..$ prop  : num [1:18954] 0.0019 0 0.00015 0 0 0 0 0 0 0 ...
##   ..$ type  : chr [1:18954] &quot;AS&quot; &quot;AS&quot; &quot;AS&quot; &quot;AS&quot; ...
##   ..$ plant : Factor w/ 3 levels &quot;HJO&quot;,&quot;AAE&quot;,&quot;AAW&quot;: 1 1 1 1 1 1 1 1 1 1 ...
##   ..$ pair  : Factor w/ 6 levels &quot;HJO-1&quot;,&quot;HJO-2&quot;,..: 1 1 1 1 1 1 1 1 1 1 ...
## NULL</code></pre>
<pre><code>## Warning: Unequal factor levels: coercing to character</code></pre>
<pre class="r"><code>plist        &lt;- plotNetGrowthDistribution(df.netgrowth)</code></pre>
<pre><code>## [1] &quot;Percent of reads at k &lt; zero:&quot;
## [1] 10.28</code></pre>
<pre class="r"><code>print(plist[[1]])</code></pre>
<p><img 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VoBbdmXsi8moLf+1jkT0PBP2FZ6ZX2F7Nu3q+87HdDyT1gYMY9A1zn6f+HtS9kX8wh0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xQR0EtABDmDMvpSAbqFcK6At+1L2xY4U0Lc3Nzff/vx46f3tpZs3py89U64V0JZ9Kftixwnorz/c3Pv+4eLbh0sfgvr0koCu5gDG7EsJ6Fq//XSfx3c3Nz/eXXx3X9Jfvrv5w18/uySg6zmAMftSArrW+5vf//nu/9/eP1G/fTh6/0j0tpk/Pr8koBdwAGP2pQR0rbcfPsP57v5R5vtPz93fPL8koBdwAGP2pQT0Ug8Bffv4ZP3dXTufXvpcuVZAW/al7IsdLaC//XT3IPPhf+/cPbN/eunEbyrXCmjLvpR9sYMF9MOXkm7/78MX43/57j6gs0sffuXNTPJHf3A6oOWfAHwtTgd0gw+kCOjdN3veP1l//KrRQzKfXvrwawUUuNThAnr/JH2ezJsfn1468fvKx9uewrfsS9kXO9hT+LsvH90WdMEj0LlyrYC27EvZFztcQO+/YrTgc6Bz5VoBbdmXsi92uIDefx/T/Ovu3/789NKJ31KuFdCWfSn7YscM6Pw7Pz+79LlyrYC27EvZFztKQD89TX/3+c8e+UmkjAMYsy8loGs9/pDRw1eM/Cz8K3EAY/alBHSt20i+me4fiZ54/SWvxlRxAGP2pQR0tds8nn8FUK8HGnEAY/alBPRL/vG7f/m32cU/ffNf/vf8X99X8uNzdK9I/xocwJh9KQEdCuj/8f8ufO9fVq4V0JZ9KftiOw7oP34noMe/g9qXsi+2l4D+5ZtTnj6FX61cK6At+1L2xfYS0NuHmyf814vbea9cK6At+1L2xfYS0Onvr9dPAV3OAYzZlxLQL3n2RaRMuVZAW/al7IsJ6CSgAxzAmH0pAd1CuVZAW/al7IsJ6CSgAxzAmH0pAX3Bf/zr/KtIvg/08HdQ+1L2xXYW0GffDiqgh7+D2peyL7avgD7/XiYBPfwd1L6UfbF9BfRPWTOfKNcKaMu+lH2xXQX0n398lX4K6HIOYMy+lIB+yT9+l/3w0RPlWgFt2ZeyLyagk4AOcABj9qUE9Etun8IL6DNHv4Pal7IvtquATn+pXsDuqXKtgLbsS9kX21dAX+k5fLlWQFv2peyL7Sugdz+I9AqPQcu1AtqyL2VfbFcB/exVlX0j/eHvoPal7IsJ6CSgAxzAmH0pAf0SAf3c0e+g9qXsi+0qoK+lXCugLftS9sUEdBLQAQ5gzL6UgG6hXCugLftS9sUEdBLQAQ5gzL6UgH6JLyJ97uh3UPtS9sUEdBLQAQ5gzL6UgH6JgH7u6HdQ+1L2xXYV0Ll//rH7oc5yrYC27EvZF9ttQMuXZirXCmjLvpR9sR0H9PYx6H8b/k0nlWsFtGVfyr7YjgPaPQQt1wpoy76UfbF9B9QXkQ5/B7UvZV9MQCcBHeAAxuxLCehy//idp/DHv4Pal7Ivtt+A3n1T6P85+ptOK9cKaMu+lH2xXQX0+TfS/8u/XZLNT8q1AtqyL2VfbNcBrf6CuXKtgLbsS9kX23FAo68gTQI6wAGM2ZcS0C2UawW0ZV/KvpiATgI6wAGM2ZcS0C2UawW0ZV/Kvtj+AvrhE6HdZ0AFdIADGLMvJaAvmH0dyReR7hz9Dmpfyr7YzgL65Ovw1beBCuhyDmDMvpSAftE//3jbzYfXsPv77T95PdDj30HtS9kX21dA/z6L5l1MvR7o4e+g9qXsi+0roH+af+Lz9um8n4U//B3UvpR9sV0F9PZB5/ynN72g8r8f/w5qX8q+2K4CevuYc/6k/e9eD/T4d1D7UvbFBHQS0AEOYMy+lIB+iafwnzv6HdS+lH2xXQXUF5E+d/Q7qH0p+2L7CqhvY/rM0e+g9qXsi+0roL6R/jNHv4Pal7Ivtq+APv1RzuyH4cu1AtqyL2VfbGcB9WIizx39Dmpfyr7Y3gLq5eyeOfod1L6UfbH9BfQVlGsFtGVfyr6YgE4COsABjNmXEtCX/OXhq/D/+F34HL5cK6At+1L2xXYW0LtPgN4H9D/+9Zvq2+gFdIADGLMvJaBfdP99oPc/zXn3baBZQcu1AtqyL2VfbF8B/cvs7/H4yzd+Eunfj38HtS9lX2xXAb19ADr7zOfts3g/C3/4O6h9KftiuwroP37n1ZieO/od1L6UfbG9BdTrgT5z9DuofSn7YgI6CegABzBmX0pAv+Sff3zypP1PnsIf/w5qX8q+2K4CeveV90+fBP37N08+I3qBcq2AtuxL2RfbV0Dvvo/+w/cx3f1j9cNI5VoBbdmXsi+2r4A+fP/8R9G3gQrocg5gzL6UgL7g7kc4P/j4LfUXK9cKaMu+lH2xvQX04+uBdvkU0AEOYMy+lIBu4W+dMwEN/4RtpVfWV8i+fbv6vtMBLf+EhRHzeqDrHP2/8Pal7It5BDoJ6AAHMGZfSkC3UK4V0JZ9KftiAjoJ6AAHMGZfSkC3UK4V0JZ9KftiAjoJ6AAHMGZfSkC3UK4V0JZ9KftiAjoJ6AAHMGZfSkC3UK4V0JZ9KftiAjoJ6AAHMGZfSkC3UK4V0JZ9KftiAjoJ6AAHMGZfSkBP+/ASTDPR32h8r1wroC37UvbFdhvQ7vXoBXSAAxizLyWgp50KaFfQcq2AtuxL2RfbSUA/888/3hY0+ks5BXQ5BzBmX0pAF7v7yz2ivxSpXCugLftS9sX2G9C7v+M4+kpSuVZAW/al7IvtOKC3D0Gj5/DlWgFt2ZeyL7bjgP7jd9WXkcq1AtqyL2VfbMcB/ecfBfT4d1D7UvbFBHQS0AEOYMy+lIAu53Ogd45+B7UvZV9sxwH1Vfg7R7+D2peyL7bfgPo+0HtHv4Pal7IvtteA+kmkD45+B7UvZV9sJwE9+bPw//Jvl7fzXrlWQFv2peyL7TigXo3pztHvoPal7IvtNqBeD/TB0e+g9qXsi+0koK+rXCugLftS9sUEdBLQAQ5gzL6UgG6hXCugLftS9sUEdBLQAQ5gzL6UgJ72j9+lXzV6plwroC37UvbFBHQS0AEOYMy+lICeJqDnHP0Oal/KvpiATgI6wAGM2ZcS0NME9Jyj30HtS9kXE9BJQAc4gDH7UgJ6moCec/Q7qH0p+2ICOgnoAAcwZl9KQE87+XJ22QsylWsFtGVfyr6YgE4COsABjNmXEtDTBPSco99B7UvZF9tPQH0O9KSj30HtS9kXE9BJQAc4gDH7UgJ6moCec/Q7qH0p+2ICOgnoAAcwZl9KQE8T0HOOfge1L2VfTEAnAR3gAMbsSwnoaQJ6ztHvoPal7IsJ6CSgAxzAmH0pAd1CuVZAW/al7IvtLKD/8a/3P4H0L/+2vpYnlGsFtGVfyr7YrgL6p9lPcZbP6Mu1AtqyL2VfbEcBffbz8OGj0HKtgLbsS9kX209A75+9f6jmfUu7gpZrBbRlX8q+2G4CetfM2YsvPbt4mXKtgLbsS9kX201A//LNN//lf88u//OP33zzX1cG87lyrYC27EvZF9tLQG8fcT57yn77lL56CFquFdCWfSn7YnsJ6N8/f7x5+5j0v63J5efKtQLasi9lX2wvAf3T518zun0IGn0vU7lWQFv2peyL7SSg//zj08+AnnvbOuVaAW3Zl7IvtpOAnvxZ+D/5O5GOfwe1L2VfTEAnAR3gAMbsSwnoaQJ6ztHvoPal7IvtJKA+B3rO0e+g9qXsi+0koL4Kf87R76D2peyL7SWgf/F9oKcd/Q5qX8q+2F4C+o/fPf+Ep59Eunf0O6h9Kftiewmon4U/4+h3UPtS9sV2E9ATr8YUfQlJQAc4gDH7UgJ61v3rgX5IqNcD/ejod1D7UvbF9hPQx78P6VH2aqACOsABjNmXEtAvmf+dSNXnP++UawW0ZV/KvtiuAupv5fzc0e+g9qXsi+0soK+jXCugLftS9sWOFNB3N7fePF56/4VLz5RrBbRlX8q+2HEC+usPN/d+/+f7i28fLn3784lLArqaAxizLyWga/320306f/nu5g9/ne4fjX5/7pKArucAxuxLCeha7z889Lyt5I/3D0e/P3dJQC/gAMbsSwnoWm8/PLq8fST65i6nH5+7f3ZJQC/gAMbsSwno+oC+mf3DY05vn7zftvPpJQG9gAMYsy8loJe6f7r+8DD0zt0z+6eXTvyecq2AtuxL2Rc7XEDvG3mbzO8fLv7y3X1AZ5c+/LqbmeiPvnc6oOWfAHwtTgd0gw8kCujtA9Dbp+uPXzV6SObTSx9+oYAClzpYQG9befdZznkyb358eunE7yofb3sK37IvZV/sWE/hb1N5/xBzwSPQuXKtgLbsS9kXO1RA734Y6f4R5oLPgc6VawW0ZV/KvtiRAnr7BP1DH+dfd//256eXTvzGcq2AtuxL2Rc7UEA/9fPJ94He/sPTSwJ6AQcwZl9KQC/p56eHl34S6ZU4gDH7UgK61oevv3+65GfhX4MDGLMvJaBrvXv6Q0Zejel1OIAx+1ICutLjq4F+fN1krwf6KhzAmH0pAV3p9tHl04B6RfpX4QDG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9lX0xAJwEd4ADG7EsJ6BbKtQLasi9l31qnS3lG+QcvjJiArnOYO+gZ9qXsW0tAzyvXCmjLvpR9awnoeeVaAW3Zl7JvLQE9r1wroC37UvatJaDnlWsFtGVfyr61BPS8cq2AtuxL2beWgJ5XrhXQln0p+9YS0PPKtQLasi9l31oCel65VkBb9qXsW0tAzyvXCmjLvpR9awnoeeVaAW3Zl7JvLQE9r1wroC37UvatJaDnlWsFtGVfyr61BPS8cq2AtuxL2beWgJ5XrhXQln0p+9YS0PPKtQLasi9l31oCel65VkBb9qXsW0tAzyvXCmjLvpR9awnoeeVaAW3Zl7JvLQE9r1wroC37UvatJaDnlWsFtGVfyr61BPS8cq2AtuxL2beWgJ5XrhXQln0p+9YS0PPKtYAMtEUAABXhSURBVALasi9l31oCel65VkBb9qXsW0tAzyvXCmjLvpR9awnoeeVaAW3Zl7JvLQE9r1wroC37UvatJaDnlWsFtGVfyr61BPS8cq2AtuxL2beWgJ5XrhXQln0p+9YS0PPKtQLasi9l31oCel65VkBb9qXsW0tAzyvXCmjLvpR9awnoeeVaAW3Zl7JvLQE9r1wroC37UvatJaDnlWsFtGVfyr61BPS8cq2AtuxL2beWgJ5XrhXQln0p+9YS0PPKtQLasi9l31oCel65VkBb9qXse9lQKgV0EtABDmDMvpSAbqFcK6At+1L2vUxAR5VrBbRlX8q+lwnoqHKtgLbsS9n3MgEdVa4V0JZ9KfteJqCjyrUC2rIvZd/LBHRUuVZAW/al7HuZgI4q1wpoy76UfS8T0FHlWgFt2Zey72UCOqpcK6At+1L2vUxAR5VrBbRlX8q+lwnoqL91zgQ0/BO2lV5ZXyH79q3YFwT08g/ik4UR8wh0nR3+F36IfSn7XhYE9PIP4pOFERPQdXZ4Bx1iX8q+lwnoqHKtgLbsS9n3MgEdVa4V0JZ9KfteJqCjyrUC2rIvZd/LBHRUuVZAW/al7HuZgI4q1wpoy76UfS8T0FHlWgFt2Zey72UCOqpcK6At+1L2vUxAR5VrBbRlX8q+lwnoqHKtgLbsS9n3MgEdVa4V0JZ9KfteJqCjyrUC2rIvZd/LBHRUuVZAW/al7HuZgI4q1wpoy76UfS8T0FHlWgFt2Zey72UCOqpcK6At+1L2vUxAR5VrBbRlX8q+lwnoqHKtgLbsS9n3MgEdVa4V0JZ9KfteJqCjyrUC2rIvZd/LBHRUuVZAW/al7HuZgI4q1wpoy76UfS8T0FHlWgFt2Zey72UCOqpcK6At+1L2vUxAR5VrBbRlX8q+lwnoqHKtgLbsS9n3MgEdVa4V0JZ9KfteJqCjyrUC2rIvZd/LBHRUuVZAW/al7HuZgI4q1wpoy76UfS8T0FHlWgFt2Zey72UCOqpcK6At+1L2zQSlFNA75VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkA/8/7m+0//eOvN6UvPlGsFtGVfyr4ZAX3u1x8+BvTtzb1vfz5x6blyrYC27EvZNyOgz9z28zGg7+7/6Zfvbv7w188uCeh6DmDMvpSAXuA2kI8BfXwoevumH59fEtALOIAx+1ICut7t0/T//j8/BPT9p+fub55f+ly5VkBb9qXsmxHQuduHl9//9tOHgL59fLL+7q6dTy8J6AUcwJh9KQFdH9D/8dfpMaC3///m4a3vb37/56eXBPQSDmDMvpSAXmQW0A9fTPrlu/uAzi59+KU3M8Uf/eh0QMs/ASi8XkA3GJMG9NO3M90l8+mlD79UQOE/NwF97lRAb358eunEbysfb3sK37IvZd/M6wW0nbTItR+BzpVrBbRlX8q+GQF9buBzoHPlWgFt2Zeyb0ZAnzv1Vfhvf3566cRvK9cKaMu+lH0zAvrcqe8Dvf2Hp5c+V64V0JZ9KftmBPS5jwH1k0ivxAGM2ZcS0It8DKifhX8lDmDMvpSANgH1akyvxAGM2ZcS0CigXg/0dTiAMftSAnqRWUC9Iv2rcABj9qUEdAvlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl7JvRkAj5VoBbdmXsm9GQCPlWgFt2Zeyb0ZAI+VaAW3Zl9rjvpFGCegWyrUC2rIvtcd9ArqEgK7jAKbsiwnopRZGTEDXcQBT9sUE9FILIyag6ziAKftiAnqphRET0HUcwJR9MQG91MKICeg6DmDKvpiAXmphxAR0HQcwZV/s2gEd+cUCGinXCmjLvtQe9wnoEgK6jgOYsi8moJdaGDEBXccBTNkXE9BLLYyYgK7jAKbsiwnopRZGTEDXcQBT9sUE9FILIyag6ziAKftiAnqphRET0HUcwJR9MQG91MKICeg6DmDKvpiAXmphxAR0HQcwZV9MQC+1MGICuo4DmLIvJqCXWhgxAV3HAUzZFxPQSy2MmICu4wCm7IsJ6KUWRkxA13EAU/bFBPRSCyMmoOs4gCn7YgJ6qYURE9B1HMCUfbGvI6DXdvno2aRlBHQdBzBlX0xAL7UwYgK6jgOYsi8moJdaGDEBXccBTNkXE9BLLYyYgK7jAKbsiwnopRZGTEDXcQBT9sUE9FILIyag6ziAKftiAnqphRET0HUcwJR9MQG91MKICeg6DmDKvpiAXmphxAR0HQcwZV8sCMzIuxDQLZRrBbRlX0pAryK44j5NWkZA1zn6AbQvJaBXEVxxnyYtI6DrHP0A2pf6qgMaNEpAt1CuFdCWfSkBvYryGlwYMQFd5+gH0L6UgF5FeQ0ujJiArnP0A2hfSkCvorwGF0ZMQNc5+gG0LyWgV1FegwsjJqDrHP0A2pcS0Ksor8GFERPQdY5+AO1LCehVlNfgwohtGdC/dc4ENPwTtpVeWV8h+2KnAzPya884/S6+koCW1+DCiHkEus7RH8HYl/II9CrKa3BhxAR0naMfQPtSAnoV5TW4MGICus7RD6B9KQG9ivIaXBgxAV3n6AfQvpSAXkV5DS6MmICuc/QDaF9KQK+ivAYXRkxA1zn6AbQvJaBXUV6DCyMmoOsc/QDalxLQqyivwYURE9B1jn4A7UsJ6FWU1+DCiAnoOkc/gPalBPQqymtwYcQEdJ2jH0D7UgJ6FeU1uDBiArrO0Q+gfSkBvYryGlwYMQFd5+gH0L6UgF5FeQ0ujJiArnP0A2hfSkCvorwGF0ZMQNc5+gG0LyWgV1FegwsjJqDrHP0A2pcS0Ksor8GFERPQdY5+AO1LCehVlNfgwogJ6DpHP4D2pQT0KsprcGHEBHSdox9A+1ICehXlNbgwYgK6ztEPoH0pAb2K8hpcGDEBXefoB9C+lIBeRXkNLoyYgK5z9ANoX0pAr6K8BhdGTEDXOfoBtC8loFdRXoMLIyag6xz9ANqXEtCrKK/BhRET0HWOfgDtSx0noF+18hpcGDEBXefoB9C+lIBeRXkNLoyYgK5z9ANo34tGzrCAXkV5DS6MmICuIzCpPe4bOcMCehXlNbgwYgK6jsCk9rhv5Ayf2fd6GXi9SH3Nimvu0cKICeg6ApPa476RMyygV1Fcc48WRkxA1xGY1B73jZxhAb2K4pp7tDBiArqOwKT2uG/kDAvoVRTX3KOFERPQdQQmtcd9I2dYQK+iuOYeLYyYgK4jMKk97hs5wwJ6FcU192hhxAR0HYFJ7XHfyBkW0KsorrlHCyMmoOsITGqP+0bOsIBeRXHNPVoYMQFdR2BSe9w3coYF9CqKa+7RwogJ6DoCk9rjvpEzLKBXUVxzjxZGTEDXEZjUHveNnGEBvYrimnu0MGICuo7ApPa4b+QMC+hVFNfco4URE9B1BCa1x30jZ1hAr6K45h4tjJiAriMwqT3uGznDAnoVxTX3aGHEBHQdgUntcd/IGRbQqyiuuUcLIyag6whMao/7Rs6wgF5Fcc09WhgxAV1HYFJ73DdyhgX0Kopr7tHCiAnoOgKT2uO+kTMsoFdRXHOPFkZMQNcRmNQe942cYQG9iuKae7QwYgK6jsCk9rhv5AwL6FUU19yjhRET0HUEJrXHfSNnWECvorjmHi2MmICuIzCpPe4bOcMCehXFNfdoYcQEdB2BSe1x38gZFtCrKK65RwsjJqDrCExqj/tGzrCAXkVxzT1aGDEBXUdgUnvcN3KGBfQqimvu0cKICeg6ApPa476RMyygV1Fcc48WRkxA1xGY1OvtO3PUrh3QIAPBLz66y2/U2U22jICuc5jAnHGYfWeOmoAe0eU36uwmW0ZA1zlMYM44zL4zR01Aj+jyG3V2ky0joOscJjBnfB37gnNy5l0I6BFdfqPObrJlBHSdryMwr+fr2BeckzPvQkCP6PIbdXaTLSOg63wdgXk9X8e+4JyceRcCekSX36izm2wZAV3n6wjM6xnad/m9WUBfnjfyLv6TuvxGnd1kywjoOgI6c/m9WUBfnjfyLv6TuvxGnd1kywjoOgI6c/m9WUAJXH6jzm6yZQR0HQGdufzeLKAELr9RZzfZMgK6zmECeuauKKAr3/PpXyugV3H5jTq7yZYR0HUE9MX3MfIeBJTA5Tfq7CZbRkDXEdAX38fIezhOQNnQ5TfqJwsjJqDrCOiL72PkPQgogctv1E8WRkxA1xHQF9/HyHsQUAKX36ifLIyYgK4joC++j5H3IKAELr9RP1kYMQFdR0BffB8j70FACVx+o36yMGICus7XEdDgfnTmXewwoENHTUCP6PIb9ZOFERPQdQT0xfcx8h4ElMDlN+onCyMmoOsI6IvvY+Q9fCUBfb0/j2sYucu9ZGHEBHSd/5wBfbV789cdUHZi5C73koURE9B1BDS9NwsogZG73EsWRkxA1xHQlffmoXfxeu9ZQI9o5I7/koURE9B1BHTlvXnoXbzeexbQIxq5479kYcReOaDvb269OfMvy7VfdUCDu4aAXuU9s2sjd/yXLCzc6wb07c29b38++W/LtacDGlzPZ97FDgMafBRDXu+j+Dr28dUZOZQvWZi4Vw3ou5ub76fpl+9u/vDXU/+6XCugL+4LPoohr/dRfB37+OqMHMqXLGzcawb01x/u+nlf0B9P/fty7bUDOvSOL79njAX06/Bq14WActrIwX7Jwsi9ZkDfPz53f3v606DlWgH96rzadSGgnDZysF+yMHKvGdC3j0/d353+LGi5diig174Bg/csoPCSJiYPFkbuFQP620+PDzzf3/z+zyd+QblWQL86r3ZdwGlNTB4srNzrBvT7h3/65buPAb2ZKf+wryOgZz64a38Y8J9SWZSFXjGgj19DukZA2xp/fezbN/uO6koBPf1l+M7Rb0D79s2+o7r2I9BXcvQb0L59s++orv050Fdy9BvQvn2z76iu9FX4Mz/MmTn6DWjfvtl3VFf6PtDTP8vZOfoNaN++2XdUW/4kUujoN6B9+2bfUW35s/Cho9+A9u2bfUe15asxhY5+A9q3b/Yd1ZavBxo6+g1o377Zd1RbviJ96Og3oH37Zt9Rbfl3IoWOfgPat2/2HdVBAgpwfQIKsJKAAqwkoAArCSjASgIKsJKAAqwkoAArCSjASnsN6MmfEX335I3X+jHSV3Hug3//+Cr/v/304a/me/UXankVL+474u03f+N+b78Xp+38phuz04CeepWSX394eOOHvz7kai9k8hrOffCf/p6px7X7O4B3Xt53wNvvyRt3e/u9PG3fN92gfQb01Ovk3f4n/S6dj2+83kvpvYJzH/zdqfv490ztcdgHC/Yd7/Z7+sa93n4Lpu36phu1y4CefKXm9x8eej688Yov5tw798HfXv4YmPc7foq0YN/xbr9nb9zp7bdg2q5vumG7DOjJvyvk8W9gevi77K7414n0znzwt8+M/vv//PQI7fvPft9eLNh3vNvv2Rt3evstmLbrm27YLgM6+9vqPn2e5ePNdf8PJ3/JXpz+4G//i/79p78q+u1r/03Rr2jBvuPdfs/euNPbb8G0Xd90w/YY0Pnfl/z53fD+GcSXf8lX7swH/8v/+Ov0MTC//vDt//php1/qXLDveLffszfu9PZbMG3XN924nQb041dSPr+J7m+2L/+Sr9wXPviP/+r+04U7/VLngn3Hu/2evXGnt9+Cabu+6cbtMaCfvtflxE10+y9vn0F88Zd87b7wwX+8d77/8P0vb3f4pc4F+453+z17405vvwXTdn3Tjdt7QJ9/oe/23939N/1Lv+Sr94UP/mNAHz+/dPuGvc1bsu94t9+zN+709lswbdc33bi9B/TZf+Nu/9X9W3b9n8Elj0A/2uGXOj0CnS3a1+3nEehzOwro46eNfjz/WZa7b8S+/4/eHj8Rs2DfiYC+281zwJF9x7v9zi3az+13x+dAn9tpQN88vOn908/B3/6KDzfZ2V/yFXt533EC+ubhTWf3He/2O7doP7ffnQXT9njTXWBHAf1k9p1m83vfp36e/SX7cP6D33NAP1mw73i335lFO9u3YNqub7phuwzo6Z91uO3np//i7frHIc5/8J8/xX27w59oeXnfAW+/J2/c7e3nJ5Ge2WVAz/1A7uwZw65/IPf8Bz/7KvzDf91//WGHn2dasO94t9/TN+719vOz8M/sMqAnX+/l3dOfe9j1S8Kc/eDn30j/Zpp/+mlXXt53wNvvyRt3e/t5Naan9hnQJ684eHsnfPjW+Y/ePP8lu/P5vgefAvN+vnV3Xt53wNvvyaLd3n4vT9v3TTdopwGdv+b1w6348WfjPr591y+L/dm+6fGfv//0jzc3u32S9PK+A95+Txbt9vZ7edq+b7oxew0owOYEFGAlAQVYSUABVhJQgJUEFGAlAQVYSUABVhJQgJUEFGAlAQVYSUABVhJQgJUEFGAlAQVYSUABVhJQgJUEFGAlAQVY6f8Hr8MRact3hQkAAAAASUVORK5CYII=" title="plot of chunk Run Net growth rate script" alt="plot of chunk Run Net growth rate script" width="672" /></p>
<pre class="r"><code>print(plist[[2]]) </code></pre>
<p><img src="data:image/png;base64,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" title="plot of chunk Run Net growth rate script" alt="plot of chunk Run Net growth rate script" width="672" /></p>
<pre class="r"><code>grid.arrange(plist[[1]], plist[[2]], nrow=2)</code></pre>
<p><img 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" title="plot of chunk Run Net growth rate script" alt="plot of chunk Run Net growth rate script" width="672" /></p>
<pre class="r"><code>ggsave(path=&quot;figs&quot;, filename=&quot;cumabun_by_netgrowth.pdf&quot;, 
       plot=plist[[2]], width=8, height=6, units=&quot;cm&quot;)

df.netgrowth$km_class &lt;- cut(df.netgrowth$km, 
                              breaks=c(-0.22, -0.1, 0, 0.03, 10), 
                              labels=c( &quot;inactive&quot;, &quot;low&quot;, &quot;active&quot;, &quot;max&quot;) )
df.netgrowth[(df.netgrowth$prop_ww == 0), &quot;km_class&quot; ] &lt;- &quot;max&quot;

df.netgrowth$tax_name &lt;- makeTaxLabels(df.netgrowth$OTU, data.k)

df.netgrowth$taxlab   &lt;- ifelse((df.netgrowth$prop_ww &gt; 0.01) &amp;
                                 (df.netgrowth$km &gt; -0.2) &amp;
                                 (df.netgrowth$km &lt;  0.01), 
                                  as.character(df.netgrowth$tax_name), &quot;&quot;)</code></pre>
</div>
<div id="plot-simple-ratio" class="section level2">
<h2>Plot simple ratio</h2>
<pre class="r"><code>ggplot(data=df.netgrowth, aes(x = ratio, fill = class)) +
    geom_histogram() +
    labs(x = &quot;ratio&quot;, y = 'OTU count') +
    theme(legend.position=&quot;none&quot;)</code></pre>
<pre><code>## stat_bin: binwidth defaulted to range/30. Use 'binwidth = x' to adjust this.</code></pre>
<pre><code>## Warning: Removed 32 rows containing missing values (position_stack).</code></pre>
<p><img 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" title="plot of chunk unnamed-chunk-5" alt="plot of chunk unnamed-chunk-5" width="672" /></p>
<pre class="r"><code>df.netgrowth  &lt;- arrange(df.netgrowth, ratio)
  
ggplot(data=df.netgrowth, aes(x = ratio, y = cumsum(prop_as / 6) * 100)) +
    geom_step() +
    xlab(&quot;ratio&quot;) +
    ylab('Cumulative read abundance (%)')</code></pre>
<p><img 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" title="plot of chunk unnamed-chunk-5" alt="plot of chunk unnamed-chunk-5" width="672" /></p>
</div>
</div>
<div id="summarise-data-per-plant-by-class" class="section level1">
<h1>Summarise data per plant by class</h1>
<p>Classes are “inactive”, “low”, “active”, “max”</p>
<pre class="r"><code>a &lt;- group_by(df.netgrowth, pair, km_class) %.%
     summarise( AS_percent = sum(prop_as * 100),
                n_otus     = n() )

# mean sludge% by class
dcast(a, pair ~ km_class, value.var= &quot;AS_percent&quot;, 
      fun.aggregate= function(x) round(mean(x), 1))</code></pre>
<pre><code>##    pair inactive  low active  max
## 1 HJO-1      2.8  5.1   54.4 37.6
## 2 HJO-2      4.1  9.6   30.4 55.8
## 3 AAE-1      2.9 14.6   51.7 30.7
## 4 AAE-2      2.8  5.8   48.6 42.8
## 5 AAW-1      1.9  4.4   47.5 46.2
## 6 AAW-2      2.0  5.5   76.2 16.3</code></pre>
<pre class="r"><code># mean # OTUs by class
dcast(a, pair ~ km_class, value.var= &quot;n_otus&quot;, fun.aggregate= sum, margins= TRUE )</code></pre>
<pre><code>##    pair inactive low active  max (all)
## 1 HJO-1      317  79    123  703  1222
## 2 HJO-2      296  68     72  742  1178
## 3 AAE-1      322  73    205  652  1252
## 4 AAE-2      339  91    128  840  1398
## 5 AAW-1      387  50    148  983  1568
## 6 AAW-2      718 114    330  633  1795
## 7 (all)     2379 475   1006 4553  8413</code></pre>
<pre class="r"><code># percent reads near k max
cumsum(df.netgrowth$prop_as / 6)[sum(df.netgrowth$k &gt; 0.02857 )]</code></pre>
<pre><code>## [1] 0.6836</code></pre>
<pre class="r"><code>high_growth_rate &lt;- df.netgrowth[df.netgrowth$k &gt; 0.02857, ]
max(high_growth_rate$prop_ww)</code></pre>
<pre><code>## [1] 0</code></pre>
<pre class="r"><code># percent of reads with k &gt; -0.15
cumsum(df.netgrowth$prop_as / 6)[sum(df.netgrowth$km &lt; -0)]</code></pre>
<pre><code>## [1] 0.1028</code></pre>
<p>The assumption is that the net growth rate at steady state will be equal to the max net growth rate (1/35 = 0.0286).</p>
<p>There are a lot of OTUs that are at or near the upper limit.</p>
<pre class="r"><code>printNetGrowthStats(df.netgrowth)</code></pre>
<pre><code>## [1] &quot;Wastewater totals&quot;
## [1] &quot;What proportion of the WW OTUs were found in the sludge?&quot;
## [1] &quot;Number of OTUs in Influent/sludge:&quot;
## 
##   WW Both   AS 
## 2119 1741 4553 
## [1] &quot;Number of OTUs in Influent:&quot;
##    WW  Both Total 
##  2119  1741  3860 
## [1] &quot;Number of OTUs in Influent (%):&quot;
##   WW Both 
##   55   45 
## [1] &quot;WW reads per class:&quot;
##     pair class percent
## 1  HJO-1    WW     6.1
## 2  HJO-2    WW     6.5
## 3  AAE-1    WW     7.0
## 4  AAE-2    WW     6.3
## 5  AAW-1    WW    13.5
## 6  AAW-2    WW    17.4
## 7  HJO-1  Both    93.9
## 8  HJO-2  Both    93.5
## 9  AAE-1  Both    93.0
## 10 AAE-2  Both    93.7
## 11 AAW-1  Both    86.5
## 12 AAW-2  Both    82.6
## [1] &quot;%reads from WW OTUs detected in sludge:&quot;
## [1] &quot;90.5 (+- 4.8, n=6)&quot;
## [1] &quot;%reads from WW OTUs not detected in sludge:&quot;
## [1] &quot;9.5 (+- 4.8, n=6)&quot;
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    6.10    6.35    6.75    9.47   11.90   17.40 
## [1] &quot;########################&quot;
## [1] &quot;Activated sludge totals&quot;
## [1] &quot;Number of OTUs in sludge:&quot;
##    AS  Both Total 
##  4553  1741  6294 
## [1] &quot;OTUs in sludge (%):&quot;
##   AS Both 
##   72   28 
## [1] &quot;AS reads per class:&quot;
##     pair class percent
## 7  HJO-1  Both    62.4
## 8  HJO-2  Both    44.2
## 9  AAE-1  Both    69.3
## 10 AAE-2  Both    57.2
## 11 AAW-1  Both    53.8
## 12 AAW-2  Both    83.7
## 13 HJO-1    AS    37.6
## 14 HJO-2    AS    55.8
## 15 AAE-1    AS    30.7
## 16 AAE-2    AS    42.8
## 17 AAW-1    AS    46.2
## 18 AAW-2    AS    16.3
## [1] &quot;%reads from AS OTUs detected in influent:&quot;
## [1] &quot;61.8 (+- 13.6, n=6)&quot;</code></pre>
<p>so the are on average 64% of the reads in the sludge detected in the influent, but this number is highly variable probably because the sampling of the sludge taxa in the nfluent is near the level of detection.</p>
<pre class="r"><code>myBreaks &lt;- c(1,10)

ggplot(data=df.netgrowth, aes(x=prop_as*100, y= km, 
                               color = prop_ww*100, label = taxlab)) +
  geom_point() +
  geom_text( size = 3, color = &quot;black&quot;, vjust= 1, hjust = 1) +
  scale_x_log10(breaks= c(0.01,0.1,1,10), limits= c(0.01,15)) +
  scale_colour_gradient(trans= &quot;log&quot;, low=&quot;white&quot;, high=&quot;red&quot;,
                        breaks= myBreaks, labels = myBreaks) +
  facet_wrap(pair~plant) +
  labs(y= expression(paste(&quot;Bounded net growth rate (&quot;, d^-1, &quot;)&quot;, sep=&quot;&quot;)), 
       x= 'biomass abundance (%)', 
       colour = &quot;ww abundance (%)&quot;) </code></pre>
<pre><code>## Warning: Removed 196 rows containing missing values (geom_point).
## Warning: Removed 166 rows containing missing values (geom_point).
## Warning: Removed 128 rows containing missing values (geom_point).
## Warning: Removed 219 rows containing missing values (geom_point).
## Warning: Removed 251 rows containing missing values (geom_point).
## Warning: Removed 242 rows containing missing values (geom_point).
## Warning: Removed 196 rows containing missing values (geom_text).
## Warning: Removed 166 rows containing missing values (geom_text).
## Warning: Removed 128 rows containing missing values (geom_text).
## Warning: Removed 219 rows containing missing values (geom_text).
## Warning: Removed 251 rows containing missing values (geom_text).
## Warning: Removed 242 rows containing missing values (geom_text).</code></pre>
<p><img 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" title="plot of chunk color by influent abundance" alt="plot of chunk color by influent abundance" width="672" /></p>
<pre class="r"><code>ggsave(filename=&quot;figs/sludge_vs_k_all.png&quot;)</code></pre>
<pre><code>## Saving 7 x 5 in image</code></pre>
<pre><code>## Warning: Removed 196 rows containing missing values (geom_point).
## Warning: Removed 166 rows containing missing values (geom_point).
## Warning: Removed 128 rows containing missing values (geom_point).
## Warning: Removed 219 rows containing missing values (geom_point).
## Warning: Removed 251 rows containing missing values (geom_point).
## Warning: Removed 242 rows containing missing values (geom_point).
## Warning: Removed 196 rows containing missing values (geom_text).
## Warning: Removed 166 rows containing missing values (geom_text).
## Warning: Removed 128 rows containing missing values (geom_text).
## Warning: Removed 219 rows containing missing values (geom_text).
## Warning: Removed 251 rows containing missing values (geom_text).
## Warning: Removed 242 rows containing missing values (geom_text).</code></pre>
<pre class="r"><code>myBreaks &lt;- c(1,10)

df.netgrowth$taxlab &lt;- NA
df.netgrowth$taxlab &lt;- with(df.netgrowth, 
                             ifelse((prop_ww &gt;= 0.01) &amp; (prop_as &gt;= 0.0012) , 
                                    tax_name, taxlab) )

p &lt;- plot_netgrowth(mydata=df.netgrowth, value=&quot;AAE-2&quot;)</code></pre>
<pre><code>## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 1386 rows containing missing values (geom_text).
## Warning: Removed 920 rows containing missing values (geom_point).</code></pre>
<pre class="r"><code>p</code></pre>
<pre><code>## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 1386 rows containing missing values (geom_text).</code></pre>
<p><img 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" title="plot of chunk color by influent abundance" alt="plot of chunk color by influent abundance" width="672" /></p>
<pre class="r"><code>info &lt;- c(as.character(samData(data.k)$pair), &quot;all&quot;)</code></pre>
<pre><code>## Warning: 'samData' is deprecated.
## Use 'sample_data' instead.
## See help(&quot;Deprecated&quot;) and help(&quot;phyloseq-deprecated&quot;).</code></pre>
<pre class="r"><code>per_plant_plots &lt;- lapply(info, FUN=plot_netgrowth)</code></pre>
<pre><code>## Warning: Removed 767 rows containing missing values (geom_point).
## Warning: Removed 1213 rows containing missing values (geom_text).
## Warning: Removed 767 rows containing missing values (geom_point).
## Warning: Removed 753 rows containing missing values (geom_point).
## Warning: Removed 1167 rows containing missing values (geom_text).
## Warning: Removed 753 rows containing missing values (geom_point).
## Warning: Removed 1024 rows containing missing values (geom_point).
## Warning: Removed 1558 rows containing missing values (geom_text).
## Warning: Removed 1024 rows containing missing values (geom_point).
## Warning: Removed 949 rows containing missing values (geom_point).
## Warning: Removed 1786 rows containing missing values (geom_text).
## Warning: Removed 949 rows containing missing values (geom_point).
## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 1386 rows containing missing values (geom_text).
## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 1024 rows containing missing values (geom_point).
## Warning: Removed 1558 rows containing missing values (geom_text).
## Warning: Removed 1024 rows containing missing values (geom_point).
## Warning: Removed 767 rows containing missing values (geom_point).
## Warning: Removed 1213 rows containing missing values (geom_text).
## Warning: Removed 767 rows containing missing values (geom_point).
## Warning: Removed 753 rows containing missing values (geom_point).
## Warning: Removed 1167 rows containing missing values (geom_text).
## Warning: Removed 753 rows containing missing values (geom_point).
## Warning: Removed 949 rows containing missing values (geom_point).
## Warning: Removed 1786 rows containing missing values (geom_text).
## Warning: Removed 949 rows containing missing values (geom_point).
## Warning: Removed 777 rows containing missing values (geom_point).
## Warning: Removed 1239 rows containing missing values (geom_text).
## Warning: Removed 777 rows containing missing values (geom_point).
## Warning: Removed 777 rows containing missing values (geom_point).
## Warning: Removed 1239 rows containing missing values (geom_text).
## Warning: Removed 777 rows containing missing values (geom_point).
## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 1386 rows containing missing values (geom_text).
## Warning: Removed 920 rows containing missing values (geom_point).
## Warning: Removed 5190 rows containing missing values (geom_point).
## Warning: Removed 8349 rows containing missing values (geom_text).
## Warning: Removed 5190 rows containing missing values (geom_point).</code></pre>
<pre class="r"><code>names(per_plant_plots) &lt;- info</code></pre>
<pre class="r"><code>class_by_pair &lt;- group_by(df.netgrowth, pair, class)
d &lt;-summarise(class_by_pair, &quot;total&quot; = n()) %.%
    arrange(class, pair)
d1 &lt;- d[d$class == &quot;Both&quot;, &quot;total&quot;] / d[d$class == &quot;AS&quot;, &quot;total&quot;] * 100
names(d1) &lt;- unique(d$pair)
# result per pair
d1</code></pre>
<pre><code>## HJO-1 HJO-2 AAE-1 AAE-2 AAW-1 AAW-2 
## 34.85 25.07 47.85 31.43 24.21 78.36</code></pre>
<pre class="r"><code>by_class &lt;- group_by(df.netgrowth, class)
d2 &lt;-summarise(by_class, &quot;total&quot; = n()) %.%
    arrange(class)
d2</code></pre>
<pre><code>## Source: local data frame [3 x 2]
## 
##   class total
## 1    WW  2119
## 2  Both  1741
## 3    AS  4553</code></pre>
<pre class="r"><code># overall fraction
d2[d2$class == &quot;Both&quot;, &quot;total&quot;] / d2[d2$class == &quot;AS&quot;, &quot;total&quot;] *100</code></pre>
<pre><code>## [1] 38.24</code></pre>
<div id="nob-in-influent-and-effluent" class="section level2">
<h2>NOB in influent and effluent</h2>
<pre class="r"><code>data.p &lt;- transform_sample_counts(physeq = data.k, function(x) x / sum(x) * 100)
NOB &lt;- subset_taxa(data.p,
                   (Genus ==  &quot;Nitrotoga_etal&quot;) | (Genus == &quot;Nitrospira&quot;) )
NOB.prop &lt;- transform_sample_counts(physeq = NOB, function(x) x / sum(x) * 100 )

p &lt;- plot_bar(NOB, &quot;Genus&quot;, fill=&quot;OTU&quot; , facet_grid = type ~ pair) 
p$data$OTU    &lt;- factor(p$data$OTU)
p$data$Genus  &lt;- gsub(p$data$Genus, pattern=&quot;_etal&quot;, replacement=&quot;&quot;)
p_tetra_total &lt;- p + 
  geom_bar(aes(fill = OTU, color = OTU), stat = &quot;identity&quot;, position = &quot;stack&quot;) +
  ylab(&quot;Read abundance (% total)&quot;) +
  xlab(label=&quot;&quot;) + 
  theme_bw() +
  theme(legend.position=&quot;none&quot;,
        axis.title.x = element_text(size = 8),
        axis.title.y = element_text(size = 8, vjust = 0.2),
        axis.text.x  = element_blank(),
        axis.text.y  = element_text(size = 6),
        axis.ticks.x = element_line(size = 0.3),
        axis.ticks.y = element_line(size = 0.3),
        strip.text   = element_text(size = 6),
        panel.grid.minor = element_blank(),
        strip.background = element_rect(linetype= &quot;blank&quot;, fill = &quot;white&quot;)
        )

p2 &lt;- plot_bar(NOB.prop, &quot;Genus&quot;, fill=&quot;OTU&quot; , facet_grid = type ~ pair)
p2$data$OTU   &lt;- factor(p2$data$OTU)
p2$data$Genus &lt;- gsub(p2$data$Genus, pattern=&quot;_etal&quot;, replacement=&quot;&quot;)
p_tetra_rel &lt;- p2 +
  geom_bar(aes(fill = OTU, color = OTU), stat = &quot;identity&quot;, position = &quot;stack&quot;) +
  ylab(&quot;Read abundance (% total)&quot;) +
  xlab(label=&quot;&quot;) + 
  theme_bw() +
  theme(legend.position=&quot;none&quot;,
        axis.title.x = element_text(size = 8),
        axis.title.y = element_text(size = 8, vjust = 0.2),
        axis.text.x  = element_text(size = 6,  hjust = 1, vjust = 1, 
                                    angle = 45),
        axis.text.y  = element_text(size = 6),
        axis.ticks.x = element_line(size = 0.3),
        axis.ticks.y = element_line(size = 0.3),
        strip.text   = element_text(size = 6),
        panel.grid.minor = element_blank(),
        strip.background = element_rect(linetype= &quot;blank&quot;, fill = &quot;white&quot;)
        )

pdf(file = &quot;figs/Figure_S10.pdf&quot;)
grid.arrange(p_tetra_total, p_tetra_rel, nrow = 2)</code></pre>
<pre><code>## Warning: Removed 7 rows containing missing values (position_stack).
## Warning: no non-missing arguments to min; returning Inf
## Warning: no non-missing arguments to max; returning -Inf
## Warning: position_stack requires constant width: output may be incorrect
## Warning: Removed 7 rows containing missing values (position_stack).
## Warning: no non-missing arguments to min; returning Inf
## Warning: no non-missing arguments to max; returning -Inf
## Warning: position_stack requires constant width: output may be incorrect</code></pre>
<pre class="r"><code>dev.off()</code></pre>
<pre><code>## pdf 
##   2</code></pre>
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