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INFERNAL User's Guide INFERNAL User’s Guide Sequence analysis using profiles of RNA sequence and secondary structure consensus http://eddylab.org/infernal Version 1.1.2; July 2016 Eric Nawrocki and Sean Eddy for the INFERNAL development team github.com/EddyRivasLab/infernal/ Contents 1 Introduction 5 How to avoid reading this manual . 5 What covariance models are . 5 Applications of covariance models . 6 Infernal and HMMER, CMs and profile HMMs . 6 What’s new in Infernal 1.1 . 7 How to learn more about CMs and profile HMMs . 7 2 Installation 9 Quick installation instructions . 9 System requirements . 9 Multithreaded parallelization for multicores is the default . 10 MPI parallelization for clusters is optional . 10 Using build directories . 11 Makefile targets . 11 Why is the output of ’make’ so clean? . 11 What gets installed by ’make install’, and where? . 11 Staged installations in a buildroot, for a packaging system . 12 Workarounds for some unusual configure/compilation problems . 12 3 Tutorial 14 The programs in Infernal . 14 Files used in the tutorial . 14 Searching a sequence database with a single covariance model . 15 Step 1: build a covariance model with cmbuild . 15 Step 2: calibrate the model with cmcalibrate . 16 Step 3: search a sequence database with cmsearch . 17 Truncated RNA detection . 23 Searching a CM database with a query sequence . 23 Step 1: create an CM database flatfile . 23 Step 2: compress and index the flatfile with cmpress . 24 Step 3: search the CM database with cmscan . 24 Truncated hit and local end alignment example . 26 Searching the Rfam CM database with a query sequence . 27 Creating multiple alignments with cmalign . 29 cmalign assumes sequences may be truncated . 30 Searching a sequence database for RNAs with unknown or no secondary structure . 31 Forcing global CM alignment with the -g option . 33 Specifying and annotating match positions with cmbuild –hand . 33 4 Infernal 1.1’s profile/sequence comparison pipeline 36 Filter thresholds are dependent on database size . 37 Manually setting filter thresholds . 38 In more detail: profile HMM filter stages . 39 Null model. 39 SSV filter. 40 Local Viterbi filter. 40 Biased composition filter. 41 Local Forward filter. 41 Glocal Forward filter. 42 1 Envelope definition. 43 In more detail: CM stages of the pipeline . 44 HMM band definition for CM stages. 44 HMM banded CM CYK filter. 44 HMM banded CM Inside filter/parser. 45 Optimal accuracy alignment. 45 Biased composition CM score correction: the null3 model. 45 Truncated hit detection using variants of the pipeline . 48 Differences between the standard pipeline and the truncated variants . 48 Modifying how truncated hits are detected using command-line options . 49 HMM-only pipeline variant for models without structure . 49 5 Profile SCFG construction: the cmbuild program 51 Technical description of a covariance model . 51 Definition of a stochastic context free grammar . 51 SCFG productions allowed in CMs . 51 From consensus structural alignment to guide tree . 52 From guide tree to covariance model . 53 Parameterization . 54 Comparison to profile HMMs . 54 The cmbuild program, step by step . 56 Alignment input file . 56 Parsing secondary structure annotation . 56 Sequence weighting . 57 Architecture construction . 57 Parameterization . 58 Naming the model . 58 Saving the model . 58 6 Tabular output formats 59 Target hits tables . 59 Target hits table format 1 . 59 Target hits table format 2 . 60 7 Some other topics 62 How do I cite Infernal? . 62 How do I report a bug? . 62 Input files . 63 Reading from a stdin pipe using - (dash) as a filename argument . 63 8 Manual pages 65 cmalign - align sequences to a covariance model . 65 Synopsis . 65 Description . 65 Options . 66 Options for Controlling the Alignment Algorithm . 66 Options for Controlling Speed and Memory Requirements . 67 Optional Output Files . 68 Other Options . 68 cmbuild - construct covariance model(s) from structurally annotated . 70 Synopsis . 70 Description . 70 2 Options . 70 Options Controlling Model Construction . ..
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