Recent changes to User manual

User manual modified by Jieming Shi

Jieming Shi — Sun, 23 Oct 2016 03:16:04 -0000

--- v45
+++ v46
@@ -1,6 +1,6 @@
 #miRPro user manual

-Version: 1.1.3
+Version: 1.1.4

 ###Table of Contents

@@ -38,7 +38,7 @@
 Download package (version 2.0) from http://bioinformatics.psb.ugent.be/supplementary_data/erbon/nov2003/downloads/randfold-2.0.tar.gz, and after unzipping, you can follow the readme
 file to finish installation.

-**Warning**: randfold require Sean Eddy's SQUID library http://selab.janelia.org/software.html installed first. 
+**Warning**: randfold require Sean Eddy's SQUID library http://eddylab.org/software/squid/squid.tar.gz installed first. 

 #####4. Novoalign

@@ -88,15 +88,15 @@

 #####2. Install mirPRo package

-Download the most recent mirPRo package, e.g., mirPRo.XXX.tgz and unzip it.
-
-The executable programs are in the folder `mirPRo.XXX/bin/`. In addition, you can find source code, script, and user manual inside mirPRo package.
-
-#####3. Add mirPRo executable files to $PATH (optional)
+Download the most recent mirPRo package, e.g., "mirPRo.XXX.tgz" and unzip it.
+
+The executable programs are in the folder "mirPRo.XXX/bin". In addition, you can find source code, script, and user manual inside mirPRo package. If you want to compile source code yourself, add flag "-std=c++11" to g++ compiler. In particular, for program "mirpro", you need to add flag "-lpthread".
+
+#####3. Add mirPRo executable files to $PATH

 To enable the path for this software, append the following statement within the file .bashrc:

-    export PATH=$PATH:/home/user/Downloads/mirPRo/bin
+    export PATH=$PATH:/home/user/Downloads/mirPRo.XXX/bin

 ####How to use mirPRo

@@ -113,14 +113,14 @@
     [5P-adapter]=====[3P-Adapter]
     GATCGTCGGACTGTAGAACTCTGAAC ========= TCTAGCCTTCTCGTGTGCA 

-What will be used in mirPRO adapter trimming? the 3P-Adapter in plus strand
+What will be used in mirPRO adapter trimming is the 3P-Adapter in plus strand

 #####1.2. Creation of index file for reference genome sequence using novoindex

 novoindex is a program within Novoalign package (pre-requisite tool). You can use the following command to
 generate the indexed file for a reference genome:

-    novoindex -k 12 -s 1 XYZ.idx XYZ.fa
+    novoindex XYZ.idx XYZ.fa

 #####1.3. mirPRo needs both mature and precursor miRNA data

@@ -185,6 +185,7 @@
     --map-detail <int>  whether to show read mapping details in each sample; 1: yes; 0: no; default = 1;
     -v <int>  whether to variation of reads counted as mature miRNA; 1: yes; 0: no; default = 1;
     --arm <int>  whether to show dominant forms (5p or 3p; read counts with ratio > 2 and difference > 20) of mature miRNAs with two possible forms generated from same precursors in all samples;1: yes; 0: no; default = 1;
+   --strand <yes no="" reverse="">  whether the data is from a strand-specific assay. Specify 'yes', 'no', or 'reverse' (default: yes). 'reverse' means 'yes' with reversed strand interpretation;

     [optional parameters for read clean and known miRNA quantification]
     -q <int>  whether to perform read quality filter by FASTX-Toolkit; 1: yes; 0: no; if yes, 'fastq_quality_filter -q 20 -p 95' will be used; default = 0;
@@ -213,7 +214,7 @@

     --novel 1 --other [related_speceis] -g [genome_sequence] --index [novelalign_genome_index]

-If you set '-r 1', each time you perform novel miRNA prediction, you will get different results because the third-party program "randfold" can generate different ourput p-values each time you run it with the same input. For those novel miRNAs around the cut-off score, they might be infulenced because of the inconsistent "randfold" p-values.
+Each time you perform novel miRNA prediction for the same data, you might get slightly different results because (1) the third-party program "randfold" can generate different ourput p-values each time you run it with the same input; (2) some random permutations in the algorithm can affect the novel miRNA socres each time. For those novel miRNAs around the cut-off score, they might be infulenced because of the inconsistent "randfold" p-values.

 To enable read cataloging function, you need to specify the following parameters:

@@ -324,7 +325,7 @@

 (1) create index file for reference genome:

-    novoindex -k 12 -s 1 genome.idx genome.fa
+    novoindex genome.idx genome.fa

 (2) use mirpro to analyze known and novel miRNAs (rat as related species for novel miRNA prediction):

@@ -345,7 +346,7 @@

 (1) create index file for reference genome:

-    novoindex -k 12 -s 1 genome.idx genome.fa
+    novoindex genome.idx genome.fa

 (2) use mirpro to analyze known and novel miRNAs (mouse as related species for novel miRNA prediction):

User manual modified by Jieming Shi

Jieming Shi — Tue, 23 Aug 2016 18:08:37 -0000

--- v44
+++ v45
@@ -1,7 +1,6 @@
 #miRPro user manual

-Version: 1.1.2
-Date: 2016/07/13
+Version: 1.1.3

 ###Table of Contents

@@ -36,9 +35,8 @@

 #####3. randfold

-Go to http://bioinformatics.psb.ugent.be/supplementary_data/erbon/nov2003/ and download "Minimum free energy of 
-folding randomization test software - randfold version 2 (C version)", and after unzipping, you can follow the readme
-file to finish installation. 
+Download package (version 2.0) from http://bioinformatics.psb.ugent.be/supplementary_data/erbon/nov2003/downloads/randfold-2.0.tar.gz, and after unzipping, you can follow the readme
+file to finish installation.

 **Warning**: randfold require Sean Eddy's SQUID library http://selab.janelia.org/software.html installed first.

User manual modified by Jieming Shi

Jieming Shi — Thu, 14 Jul 2016 02:10:24 -0000

--- v43
+++ v44
@@ -1,7 +1,7 @@
 #miRPro user manual

-Version: 1.1.1
-Date: 2016/07/05
+Version: 1.1.2
+Date: 2016/07/13

 ###Table of Contents

@@ -57,14 +57,14 @@
 Go to http://www-huber.embl.de/users/anders/HTSeq/doc/install.html#installation-on-linux and following the instruction
 to install HTSeq (tested version 0.6.1p1).

-#####6. gcc and g++ (version 4.8+)
+#####6. gcc and g++ (version 4.9+)

     sudo add-apt-repository ppa:ubuntu-toolchain-r/test
-    sudo apt-get update; sudo apt-get install gcc-4.8 g++-4.8
+    sudo apt-get update; sudo apt-get install gcc-4.9 g++-4.9
     sudo update-alternatives --remove-all gcc
     sudo update-alternatives --remove-all g++
-    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.8 20
-    sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.8 20
+    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.9 20
+    sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.9 20
     sudo update-alternatives --config gcc
     sudo update-alternatives --config g++

User manual modified by Jieming Shi

Jieming Shi — Tue, 05 Jul 2016 21:56:24 -0000

--- v42
+++ v43
@@ -1,7 +1,7 @@
 #miRPro user manual

-Version: 1.1
-Date: 2016/06/16
+Version: 1.1.1
+Date: 2016/07/05

 ###Table of Contents

User manual modified by Jieming Shi

Jieming Shi — Thu, 16 Jun 2016 18:03:56 -0000

--- v41
+++ v42
@@ -1,7 +1,7 @@
 #miRPro user manual
-Version: 1.0.1
-Date: 2015/12/07
-

+
+Version: 1.1
+Date: 2016/06/16

 ###Table of Contents

@@ -15,25 +15,24 @@

 ####How to cite the software
 Shi J, Dong M, Li L, Liu L, Luz-Madrigal A, Tsonis PA, Rio-Tsonis KD and Liang C (2015) mirPRo - a novel standalone program for differential expression and variation analysis of miRNAs. Sci Rep, 5:14617.  http://www.nature.com/articles/srep14617
-


 ####How to install prerequisite tools

 #####1. FASTX-Toolkit

-Go to http://hannonlab.cshl.edu/fastx_toolkit/download.html and follow the instruction in "Program Installation" to install the toolkit (version 0.0.14).
+Go to http://hannonlab.cshl.edu/fastx_toolkit/download.html and follow the instruction in "Program Installation" to install the toolkit (tested version 0.0.14).

 **Warning**: the prerequisite of FASTX-Toolkit includes pkg-config, gcc, and wget. Also, the compatible version of 
-libgtextutils (version 0.7) is needed before you install FASTX-Toolkit. 
+libgtextutils (tested version 0.7) is needed before you install FASTX-Toolkit. 

 #####2. RNAfold

-Go to http://www.tbi.univie.ac.at/RNA/index.html#download and download the ViennaRNA Package (version 2.1.9).
-
+Go to http://www.tbi.univie.ac.at/RNA/index.html#download and download the ViennaRNA Package (tested version 2.1.9).
 Alternatively, you can install Ubuntu package from PPA:
-\# sudo apt-add-repository ppa:j-4/vienna-rna
-\# sudo apt-get update
-\# sudo apt-get install vienna-rna
+
+    sudo apt-add-repository ppa:j-4/vienna-rna
+    sudo apt-get update
+    sudo apt-get install vienna-rna

 #####3. randfold

@@ -45,61 +44,76 @@

 #####4. Novoalign

-Go to http://www.novocraft.com/support/download/ and download Novoalign (release V3.02.12).
+Go to http://www.novocraft.com/support/download/ and download Novoalign (tested version V3.02.12).

 For instance, download novocraftV3.02.12.Linux3.0.tar.gz and unzip, then move the whole folder into /usr/local/genome/novocraft folder.  

-To enable the path for this software, append the following statement within the file .bashrc
-export PATH=$PATH:/usr/local/genome/novocraft/2015-02-13
+To enable the path for this software, append the following statement within the file .bashrc:
+
+    export PATH=$PATH:/usr/local/genome/novocraft/2015-02-13

 #####5. HTSeq

 Go to http://www-huber.embl.de/users/anders/HTSeq/doc/install.html#installation-on-linux and following the instruction
-to install HTSeq (version 0.6.1p1).
-
-#####6. Test if installation is successful
-
-To test the success of installation,  type the following commands in the terminal:
-
-fastq_quality_filter -h
-fastx_collapser -h
-novoindex
-novoalign
-randfold
-RNAfold -h
-htseq-count
-

+to install HTSeq (tested version 0.6.1p1).
+
+#####6. gcc and g++ (version 4.8+)
+
+    sudo add-apt-repository ppa:ubuntu-toolchain-r/test
+    sudo apt-get update; sudo apt-get install gcc-4.8 g++-4.8
+    sudo update-alternatives --remove-all gcc
+    sudo update-alternatives --remove-all g++
+    sudo update-alternatives --install /usr/bin/gcc gcc /usr/bin/gcc-4.8 20
+    sudo update-alternatives --install /usr/bin/g++ g++ /usr/bin/g++-4.8 20
+    sudo update-alternatives --config gcc
+    sudo update-alternatives --config g++
+
+#####7. Test if installation is successful
+
+To test the success of installation, type the following commands in the terminal:
+
+    fastq_quality_filter -h
+    fastx_collapser -h
+    novoindex
+    novoalign
+    randfold
+    RNAfold -h
+    htseq-count
+    gcc -v
+    g++ -v

 ####How to install mirPRo
-#####1. Make sure the whole mirPRo package is in correct path
-
-To enable the path for this software, append the following statement within the file .bashrc  
-export PATH=$PATH:/home/mubil/Downloads/mirPRo/bin
+
+#####1. System requirement
+
+This program has been tested on Ubuntu 12.04 and Ubuntu 14.04. 

 #####2. Install mirPRo package

-Download the most recent mirPRo package, e.g., mirPRo.vYYYYMMDD.tgz and unzip it.
-
-The executable programs are in the folder mirPRo/bin/. In addition, you can find src folder and readme file inside mirPRo folder. 
-
-This program has only been tested on Ubuntu 12.04 and Ubuntu 14.04. However, if you want to compile the source code, you need the g++ compiler of version 4.6 or later. 
-

+Download the most recent mirPRo package, e.g., mirPRo.XXX.tgz and unzip it.
+
+The executable programs are in the folder `mirPRo.XXX/bin/`. In addition, you can find source code, script, and user manual inside mirPRo package.
+
+#####3. Add mirPRo executable files to $PATH (optional)
+
+To enable the path for this software, append the following statement within the file .bashrc:
+
+    export PATH=$PATH:/home/user/Downloads/mirPRo/bin

 ####How to use mirPRo
+
 #####1. Important step or information before using mirPRo

 #####1.1. Sequencing adapter information for small RNA-Seq

 For instance, we can obtain the following information for RNA-Seq project that utilizes one pair of adapters (5P-Adapter and 3P-Adapter). Their sequences are presented in both plus strand and minus strand

--(1) Plus strand
-[5P-adapter]=====[3P-Adapter]
-GTTCAGAGTTCTACAGTCCGACGATC ========= AGATCGGAAGAGCACACGTCT                                    
-(2) Minus strand
-[5P-adapter]=====[3P-Adapter]
-GATCGTCGGACTGTAGAACTCTGAAC ========= TCTAGCCTTCTCGTGTGCA 
-
+    (1) Plus strand
+    [5P-adapter]=====[3P-Adapter]
+    GTTCAGAGTTCTACAGTCCGACGATC ========= AGATCGGAAGAGCACACGTCT                                    
+    (2) Minus strand
+    [5P-adapter]=====[3P-Adapter]
+    GATCGTCGGACTGTAGAACTCTGAAC ========= TCTAGCCTTCTCGTGTGCA 

 What will be used in mirPRO adapter trimming? the 3P-Adapter in plus strand

@@ -108,154 +122,133 @@
 novoindex is a program within Novoalign package (pre-requisite tool). You can use the following command to
 generate the indexed file for a reference genome:

-\# novoindex -k 12 -s 1 XYZ.idx XYZ.fa
+    novoindex -k 12 -s 1 XYZ.idx XYZ.fa

 #####1.3. mirPRo needs both mature and precursor miRNA data

 You need to provide the complete mature and hairpin miRNA data in FASTA format downloaded from 
 [miRBase](http://www.mirbase.org/).

- README    Release notes - read these first!
- miRNA.dat all published miRNA data in EMBL format
- hairpin.fa    Fasta format sequences of all miRNA hairpins
- mature.fa Fasta format sequences of all mature miRNA sequences
- miRNA.diff    Changes between the last release and this
- miRNA.dead    List of entries that have been removed from the database
- miFam.dat Family classification of miRNA hairpin sequences
+    README Release notes - read these first!
+    miRNA.dat  all published miRNA data in EMBL format
+    hairpin.fa Fasta format sequences of all miRNA hairpins
+    mature.fa  Fasta format sequences of all mature miRNA sequences
+    miRNA.diff Changes between the last release and this
+    miRNA.dead List of entries that have been removed from the database
+    miFam.dat  Family classification of miRNA hairpin sequences

 We need to use mature.fa, hairpin.fa and miFam.dat three files.

 #####1.4. Arf format
 This file format was created by [miRDeep2](https://www.mdc-berlin.de/36105849/en/research/research_teams/systems_biology_of_gene_regulatory_elements/projects/miRDeep/documentation), and is also used in our program to record the read mapping information.

--******************************"arf" file format******************************************
-Each line in such a file contains 13 columns. Example line:
-
-PAN_123456_x969696    21    1    21    ATACAATCTACTGTCTTTCCT    chr22    21    46508682    46508702    ATACAATCTACTGTCTTTCCT    +    1    mmmmmmmmmmmmmmmmmmmmm
-
-1: read identifier
-2: length of read sequence
-3: start position in read sequence that is mapped
-4: end position in read sequence that is mapped
-5: read sequence
-6: identifier of the genome-part to which a read is mapped to. This is either a scaffold id or a chromosome name
-7: length of the genome sequence a read is mapped to
-8: start position in the genome where a read is mapped to
-9: end position in the genome where a read is mapped to
-10: genome sequence to which a read is mapped
-11: genome strand information. Plus means the read is aligned to the sense-strand of the genome. Minus means it is aligned to the antisense-strand of the genome.
-12: Number of mismatches in the read mapping
-13: Edit string that indicates matches by lower case 'm', mismatches by upper case 'M', ambiguous nucleotides by 'N', insertions by 'I', deletions by 'D', soft clips by 'S'.
-*****************************************************************************************
-
+    ******************************"arf" file format******************************************
+    Each line in such a file contains 13 columns. Example line:
+
+    PAN_123456_x969696    21    1    21    ATACAATCTACTGTCTTTCCT    chr22    21    46508682    46508702    ATACAATCTACTGTCTTTCCT    +    1    mmmmmmmmmmmmmmmmmmmmm
+
+    1: read identifier
+    2: length of read sequence
+    3: start position in read sequence that is mapped
+    4: end position in read sequence that is mapped
+    5: read sequence
+    6: identifier of the genome-part to which a read is mapped to. This is either a scaffold id or a chromosome name
+    7: length of the genome sequence a read is mapped to
+    8: start position in the genome where a read is mapped to
+    9: end position in the genome where a read is mapped to
+    10: genome sequence to which a read is mapped
+    11: genome strand information. Plus means the read is aligned to the sense-strand of the genome. Minus means it is aligned to the antisense-strand of the genome.
+    12: Number of mismatches in the read mapping
+    13: Edit string that indicates matches by lower case 'm', mismatches by upper case 'M', ambiguous nucleotides by 'N', insertions by 'I', deletions by 'D', soft clips by 'S'.
+    *****************************************************************************************

 #####2. Known miRNA and novel miRNA analysis
-Run mirPRo/bin/mirpro.
-
--mirpro helps quantify known miRNAs and predict novel miRNAs optionally from miRNA sequencing data.
-Usage: mirpro -i <input_file_1> -i <input_file_2> ... -i <input_file_n> -d <output_directory> -m <mature_miRNA_sequence_file> -p <pre-miRNA_sequence_file> -s <species> -a <adapter_sequence> [optional parameters]
-
-***********************************help***************************************
-[mandatory parameters]
--i <input_file>: read sequencing file , FASTQ format;
--d <output_directory>: directory for output files; eg. ./miRNA_output/;
--m <mature_miRNA_sequence_file>: mature miRNA file downloaded from miRBase, FASTA format;
--p <pre-miRNA_sequence_file>: precursor miRNA file downloaded from miRBase, FASTA format;
--s <species|0>: three-letter code for the species you want to analyze in miRBase;
-   eg. mmu for mouse; hsa for human; if your species is not in miRBase, use "-s 0",
-   and add optional parameters to predict novel miRNAs;
--a <adapter_sequence|0>: adapter sequence; if data has no adapter, set 0;
-
-[optional parameters]
-
--t <int>: the number of threads will be used in the program; default = 1;
-
-Known miRNA quantification:
--q <1/0>: choice of read quality filter; 1: yes; 0: no; default = 1;
--c <int>: minimum count number of collapsed read that will be kept; default = 1;
---adapter-mistake <int>: allowed nucleotide mistakes in adapter detection, including indel or mismatch; default = 1;
---adapter-len <int>: minimum adapter length in sequence; default = 10;
---clean-len <int>: minimum read length after removing adapter; default = 15;
---gtf <gtf_file>: the annotation file in GTF format for species under study;
-        if it is given, the mapping of reads against whole genome will be performed (maximum penalty score = 60),
-        and the number of mapped reads of different features in the annotation file wil be calculated;
---map-len <int>: minimum mapped length of reads which are mapped to precursor miRNAs; default = 15;
--o <int>: the gap opening penalty in novoalign mapping; default = 40;
--e <int>: the gap extend penalty in novoalign mapping; default = 6;
---map-score <int>: maximum mapping penalty score; default is 60;
---5-upstream <int>: max number of nucleotides shift in the upstream of the 5' end of the mature miRNA; default = 3;
---3-upstream <int>: max number of nucleotides shift in the upstream of the 3' end of the mature miRNA; default = 3;
---5-downstream <int>: max number of nucleotides shift in the downstream of the 5' end of the mature miRNA; default = 3;
---3-downstream <int>: max number of nucleotides shift in the downstream of the 3' end of the mature miRNA; default = 3;
---seed <1/0>: choice of performing seed region (2-8 nt) check;
-        1: conduct seed region checking and keep reads that have no mapping mistake in the seed region;
-        0: no check; default = 1;
---map-detail <1/0>: choice of showing mapping details for each sample; 1: yes; 0: no; default = 1;
--v <1/0>: choice of showing variation of reads counted as mature miRNA; 1: yes; 0: no; default = 1;
--f <miRNA_family_data>: file of precursor family information downloaded from miRBase;
-        if given, expression result will be shown based on precursor family;
---arm <1/0>: choice of showing dominant forms (5p or 3p; read counts with ratio > 2 and difference > 20)
-        of mature miRNAs with two possible forms generated from the same precursors in all samples;
-        1: yes; 0: no; default = 1;
-
-Novel miRNA prediction and quantification:
---novel <1/0>: analysis choice; 1: predict novel miRNA; 0: not predict; default = 0;
---other <related_species>: name of other related species, used for novel miRNA prediction;
-        more than one species can be set; eg. --other mmu --other rno;
--g <genome_sequence>: genome file for this species, used for novel miRNA prediction, FASTA format;
---index <novelalign_genome_index> : novelalign genome index file for this species,
-        if given, this program will use the index file directly instead of re-build it;
--n <int>: cut-off score (-10 to 10); lower score means higher sensitivity;
-        higher score means higher true positive rate; default = 0;
--r <1/0>: choice of performing randfold to calculate p-value; 1: yes; 0: no; default = 1;
-******************************************************************************
-
+
+Run "bin/mirpro".
+
+    mirpro helps quantify known miRNAs and optionally predict novel miRNAs from miRNA sequencing data.
+    Usage: mirpro [options]
+
+    [mandatory parameters]
+    -i <string>  miRNA sequencing file, FASTQ format; can be multiple files; e.g., -i file_1.fastq -i file_2.fastq ... -i file_n.fastq;
+    -m <string>  mature miRNA file downloaded from miRBase, FASTA format;
+    -p <sring>  precursor miRNA file downloaded from miRBase, FASTA format;
+    -s <string>  miRBase 3-letter code for the species you want to analyze ; e.g., 'mmu' for mouse; 'hsa' for human; if your species is not in miRBase, set 'null', and set '--novel 1' to predict novel miRNA;
+    -a <string>  adapter sequence in miRNA sequencing data; if data has no adapter, set 'null;'
+    --novel <int>  whether to predict novel miRNAs; 1: yes; 0: no; if yes, option '-g' and '--other' must be set (see below);
+
+    [optional parameters]
+    -d <string>  directory for output files; default = '.';
+    -t <int>  the number of threads will be used in the program; default = 1; it should <= the number of input fastq file;
+    -g <string>  genome file for this species, used for novel miRNA prediction, FASTA format;
+    --gtf <string>  the annotation file in GTF format for species under study; if it is given, '-g' must be set, and read mapping against whole genome will be performed (maximum novelalign penalty score = 60), and the number of mapped reads of different features in the annotation file will be calculated;
+    -f <string>  file of precursor family information downloaded from miRBase (miFam.dat); if given, additional known miRNA expression quantification result will be shown based on precursor family;
+    --seed <int>  whether to perform miRNA seed region (2-8 nt) check, and keep reads that have no mapping mistake in the seed region; 1: yes: 0: no; default = 1;
+    --map-detail <int>  whether to show read mapping details in each sample; 1: yes; 0: no; default = 1;
+    -v <int>  whether to variation of reads counted as mature miRNA; 1: yes; 0: no; default = 1;
+    --arm <int>  whether to show dominant forms (5p or 3p; read counts with ratio > 2 and difference > 20) of mature miRNAs with two possible forms generated from same precursors in all samples;1: yes; 0: no; default = 1;
+
+    [optional parameters for read clean and known miRNA quantification]
+    -q <int>  whether to perform read quality filter by FASTX-Toolkit; 1: yes; 0: no; if yes, 'fastq_quality_filter -q 20 -p 95' will be used; default = 0;
+    -c <int>  minimum count of clean collapsed read that will be kept; default = 1;
+    --adapter-mistake <int>  allowed nucleotide mistakes in adapter detection, including indel or mismatch; default = 1;
+    --adapter-len <int>  minimum adapter length in sequence; default = 10;
+    --clean-len <int>  minimum read length after removing adapter; default = 15;
+    --map-len <int>  minimum mapped length of reads which are mapped to precursor miRNAs; default = 15;
+    -o <int>  the gap opening penalty in novoalign mapping; default = 40;
+    -e <int>  the gap extend penalty in novoalign mapping; default = 6;
+    --map-score <int>  maximum mapping penalty score; default is 60;
+    --5-upstream <int>  max number of nucleotides shift in the upstream of the 5' end of the mature miRNA; default = 3;
+    --3-upstream <int>  max number of nucleotides shift in the upstream of the 3' end of the mature miRNA; default = 3;
+    --5-downstream <int>  max number of nucleotides shift in the downstream of the 5' end of the mature miRNA; default = 3;
+    --3-downstream <int>  max number of nucleotides shift in the downstream of the 3' end of the mature miRNA; default = 3;
+
+    [optional parameters for novel miRNA prediction]
+    --other <string>  name of miRBase 3-letter code of other related species, multiple species can be set; e.g., '--other mmu --other rno'; if you don't have a related species, set 'null';
+    --index <string>  novelalign genome index file for studied species, if given, program will run faster, skipping the step of building index; the index file must be built using the same version of novoalign with that used by mirpro;
+    -n <int>  cut-off score (-10 to 10) for novel miRNA prediction; lower score means higher sensitivity; higher score means higher true positive rate; default = 0;
+    -r <int>  whether to perform randfold to calculate p-value innovel miRNA prediction; 1: yes; 0: no; default = 0; if yes, runtime will increase significantly, but result will be more reliable;

 **Important Notes**

--For prediction of novel miRNAs, you should add the following parameters:
-   -novel 1 --other <related_speceis> -g <genome_sequence> --index <novelalign_genome_index>
-   
-For prediction of novel miRNAs without known miRNA quantification, set "-s 0", and add the following parameters:
-   -novel 1 --other <related_speceis> -g <genome_sequence> --index <novelalign_genome_index>
-
-Each time you perform novel miRNA prediction, you will get different results because the third-party program "randfold" can generate different ourput p-values each time you run it with the same input.
-And for those novel miRNAs around the cut-off score, they might be infulenced because of the inconsistent "randfold" p-values.
-So you if you want to get consistent results for novel miRNA prediction, please turn off "randfold" by "-r 0".
-
-To enable read cataloging function, you should add the following parameters:
-   -gtf <gtf_file>
-You can download the gene annotation file in gtf format from ensembl website: http://useast.ensembl.org/info/data/ftp/index.html?redirect=no.
-
-To show miRNA gene family expression data, you the following parameters:
-   -f <miRNA_family_data>
+For prediction of novel miRNAs, you need to specify the following parameters:
+
+    --novel 1 --other [related_speceis] -g [genome_sequence] --index [novelalign_genome_index]
+
+If you set '-r 1', each time you perform novel miRNA prediction, you will get different results because the third-party program "randfold" can generate different ourput p-values each time you run it with the same input. For those novel miRNAs around the cut-off score, they might be infulenced because of the inconsistent "randfold" p-values.
+
+To enable read cataloging function, you need to specify the following parameters:
+
+    -gtf [gtf_file]
+    
+You can download the gene annotation file in GTF format from ensembl website: http://useast.ensembl.org/info/data/ftp/index.html?redirect=no.
+
+To show miRNA gene family expression data, you need to specify the following parameters:
+
+    -f [miRNA_family_data]
+    
 You should use the file "miRNA.dat" downloaded from miRBse as the miRNA family data.

-To enable multiple threads, you should add the following parameters:
-   -t <number of="" threads="">
-

+To enable multiple threads, you need to specify the following parameters:

+

+    -t [number_of_threads]

+  

+It should <= the number of input fastq file.
#####3. "Arm switching" detection

-Run mirPRo/bin/mirpro_armSwitch, using the file "result/arm.csv" as input.

+

+Run "bin/mirpro_arm_switch", using the file "[output_directory]/result/arm.csv" as input.

 The output result file records the miRNAs that have "arm switching" phenomenon across different treatments.
-


-*****help information****

-This program can detect "arm swtiching" phenomenon with the file "result/arm.csv" in the output directory as input.

-Usage: mirpro_armSwitch -i input.csv -o output.csv -t treatment1 -t treatment1 -t treatment 2 -t treatment2

--i: input file including the dominant miRNAs (3p or 5p) in all samples.

--i: input file including the dominant miRNAs (3p or 5p) in all samples.

--o: output result file.

--t: treatment for each sample in the input file.

-***********

-


+    This program can detect 'arm switching' phenomenon with the file 'result/arm.csv' in the output directory of mirpro as input.

+    Usage: mirpro_arm_switch [options]

+    [mandatory parameters]

+    -i <string>  input file including the dominant miRNAs (3p or 5p) in all samples.

+    -o <string>  output result file.

+    -t <string>  treatment for each sample in the input file; can be multiple; e.g., -t treatment_1 -t treatment_2 ... -t treatment_n; the treatments and samples in the input file must be in the same order; at least two treatments must be given.
Important Notes
-


 Before you run this program, please open the file "result/arm.csv", and check the order of the sample file names in the third row. You have to provide the treatment name for each sample in the same order. 

 For example, assume we have the following samples and corresponding treatments:
@@ -267,50 +260,49 @@
And in the third row of the file "result/arm.csv", we have the following order for our samples: "Data1, Data2, Data3, Data4".

 For the input of mirpro_armSwitch, you have enter the treatment parameter in the order: "-t T1 -t T2 -t T3 -t T4" as the parameters for treatment.

-

#####4. Read cataloging function for clean miRNA sequencing reads (separated module)

-Run mirPRo/bin/mirpro_feature_pro.

+

+To use this module, you need to install SAM tools first (https://sourceforge.net/projects/samtools/?source=navbar). Then run "bin/mirpro_feature_pro".

 The output result files include the read cataloging information in csv format and unmapped read sequences in FASTA format.
-


-****help information*****

-This program can perform read cataloging (using htseq-count) for aligned RNA sequencing reads in SAM/BAM file according to the given genome annotation file in GTF/GFF3 format.

-htseq-count and samtools are required for this program.

-

-Usage: mirpro_feature_pro [optional choices] -i <alignment_file> -t <annotation_file> -o <output_directory>

-

-[optional choices]

--c <yes no="">: whether the aligned reads in SAM/BAM file is collapsed; default: no; for paired-end data, collapsed aligned reads are not supported in this program;

--x <yes no="">: whether to use the output sam file of htseq-count to categorize read features (slow, but more accurate);if set to "no", this program will use the output count of htseq-count to categorize read features; default: no; for collapsed aligned reads, this will be automatically set to "yes"; for paired-end data, this can be only set to "no";

--s <yes no="" reverse="">: whether the data is from a strand-specific assay (default: yes);

--r <order>: For paired-end data, the alignment have to be sorted either by read name or by alignment position. If your data is not sorted, use the samtools sort function of samtools to sort it. Use this option, with name or pos for <order> to indicate how the input data has been sorted. The default is name.

--m <mode>: mode to handle reads overlapping more than one feature; possible values for <mode> are union, intersection-strict and intersection-nonempty (default: union);

--a <minaqual>: skip all reads with alignment quality lower than the given minimum value; default: 0;

---type <feature type="">: feature type (3rd column in GFF file) to be used, all features of other type are ignored (default, suitable for RNA-Seq analysis using an Ensembl GTF file: exon)

---samout <samout>: write out all SAM alignment records into an output SAM file called <samout>, annotating each line with its assignment to a feature or a special counter (as an optional field with tag 'XF');

---idattr <id attribute="">: GFF attribute to be used as feature ID. This option is only valid for GTF file. The default, suitable for RNA-Seq analysis using an Ensembl GTF file, is gene_id. If the feature ID is not set to gene_id, the htseq-count output will be given, but the read cataloging statistics will not be given. For GFF3 file, the program will convert it to equivalent GTF file, and run htseq-count setting the feature ID to gene ID.

-*************

-


+    This program can perform read cataloging (using htseq-count) for aligned RNA sequencing reads in SAM/BAM file according to the given genome annotation file in GTF/GFF3 format. htseq-count and samtools are required for this program.

+    Usage: mirpro_feature_pro [options]

+

+    [mandatory parameters]

+    -i <string>  alignment_file; SAM/BAM format;

+    -t <string>  annotation_file; GTF/GFF3 format;

+    -o <string>  output_directory;

+

+    [optional parameters]

+    -c <yes no="">  whether the aligned reads in SAM/BAM file is collapsed; default = 'no'; for paired-end data, collapsed aligned reads are not supported in this program;

+    -x <yes no="">  whether to use the output sam file of htseq-count to categorize read features (slow, but more accurate); default = 'no'; if 'no', this program will use the output count of htseq-count to categorize read features; for collapsed aligned reads, this will be automatically set to 'yes'; for paired-end data, this can be only set to 'no';

+    -s <yes no="" reverse="">  whether the data is from a strand-specific assay; default = 'yes';

+    -r <string>  For paired-end data, the alignment have to be sorted either by read name or by alignment position. If your data is not sorted, use the samtools sort function of samtools to sort it. Use this option, with 'name' or 'pos' to indicate how the input data has been sorted. Default = 'name'.

+    -m <string>  mode to handle reads overlapping more than one feature; possible values are 'union', 'intersection-strict' and 'intersection-nonempty' (default = 'union');

+    -a <int>  skip all reads with alignment quality lower than the given minimum value; default = 0;

+    --type  <string>  feature type (3rd column in GFF file) to be used, all features of other type are ignored (default, suitable for RNA-Seq analysis using an Ensembl GTF file: 'exon');

+    --samout <string>  name of SAM output file including all SAM alignment records, annotating each line with its assignment to a feature or a special counter (as an optional field with tag 'XF'); default = 'htseq_count_out.sam';

+    --idattr <string>  GFF attribute to be used as feature ID. This option is only valid for GTF file. The default, suitable for RNA-Seq analysis using an Ensembl GTF file, is gene_id. If the feature ID is not set to gene_id, the htseq-count output will be given, but the read cataloging statistics will not be given. For GFF3 file, the program will convert it to equivalent GTF file, and run htseq-count setting the feature ID to gene ID.
Important Notes
-


 For SAM/BAM file without collapsed reads, if you want to use the output count of htseq-count to perform read cataloging:

-   mirpro_feature_pro -i <alignment_file> -t <annotation_file> -o <output_directory>

- 

+

+    mirpro_feature_pro -i [alignment_file] -t [annotation_file] -o [output_directory]

+

 For SAM/BAM file without collapsed reads, if you want to use the output sam file of htseq-count to perform read cataloging (more accurate, but slow):

-   mirpro_feature_pro -x yes -i <alignment_file> -t <annotation_file> -o <output_directory>

- 

+

+    mirpro_feature_pro -x yes -i [alignment_file] -t [annotation_file] -o [output_directory]

+

 For SAM/BAM file with collapsed reads, the output sam file of htseq-count must be used to perform read cataloging:

-   mirpro_feature_pro -c yes -i <alignment_file> -t <annotation_file> -o <output_directory>

- 

-In the output count of htseq-count, the count of "alignment_not_unique" represents the number of all alignments for non-uniquely aligned reads (not the number of non-uniquely aligned reads). So if using this file to perform read cataloging (-x no, by default), you will not get the accurate number of non-uniquely aligned reads.

-While using the output sam file of htseq-count to perform read cataloging (-x yes), in our final result, "alignment_not_unique" can represent the number of non-uniquely aligned reads.

-


-


+

+    mirpro_feature_pro -c yes -i [alignment_file] -t [annotation_file] -o [output_directory]

+

+In the output count of htseq-count, the count of "__alignment_not_unique" represents the number of all alignments for non-uniquely aligned reads (not the number of non-uniquely aligned reads). So if using this file to perform read cataloging (-x no, by default), you will not get the accurate number of non-uniquely aligned reads. While using the output sam file of htseq-count to perform read cataloging (-x yes), in our final result, "__alignment_not_unique" can represent the number of non-uniquely aligned reads.
####How to test mirPRo

+

 #####1. Links of datasets (used in our paper) to test our program:
Reference sequences:

@@ -330,15 +322,17 @@

 hairpin.fa: ftp://mirbase.org/pub/mirbase/CURRENT/hairpin.fa.gz

 miFam.dat: ftp://mirbase.org/pub/mirbase/CURRENT/miFam.dat.gz
-#####2. Example scripts for mouse data:

+#####2. Example commands for mouse data:
(1) create index file for reference genome:

-novoindex -k 12 -s 1 genome.idx genome.fa

+

+    novoindex -k 12 -s 1 genome.idx genome.fa
(2) use mirpro to analyze known and novel miRNAs (rat as related species for novel miRNA prediction):

-mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf -t 4

-

-(3) use mirpro_armSwitch to detect "arm switching" phenomenon:

+

+    mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d . -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx -t 4

+

+(3) use mirpro_arm_switch to detect "arm switching" phenomenon:

 These are the sample names and corresponding treatments:
Sample Treatment

@@ -347,18 +341,19 @@

 SRR333599  Tg

 SRR333600  Tg
-Go to the "result/" folder;

-mirpro_armSwitch -i arm.csv -o armSwitch.csv -t WT -t WT -t Tg -t Tg

-

-#####3. Example scripts for human data:

+    mirpro_arm_switch -i result/arm.csv -o result/armSwitch.csv -t WT -t WT -t Tg -t Tg

+

+#####3. Example commands for human data:
(1) create index file for reference genome:

-novoindex -k 12 -s 1 genome.idx genome.fa

+

+    novoindex -k 12 -s 1 genome.idx genome.fa
(2) use mirpro to analyze known and novel miRNAs (mouse as related species for novel miRNA prediction):

-mirpro -i SRR1542714.fastq -i SRR1542715.fastq -i SRR1542716.fastq -i SRR1542717.fastq -i SRR1542718.fastq -i SRR1542719.fastq -d ./  -m mature.fa -p hairpin.fa -s hsa -a 0 -f miFam.dat --novel 1 --other mmu -g genome.fa --index genome.index --gtf annotation.gtf -t 6

-

-(3) use mirpro_armSwitch to detect "arm switching" phenomenon:

+

+    mirpro -i SRR1542714.fastq -i SRR1542715.fastq -i SRR1542716.fastq -i SRR1542717.fastq -i SRR1542718.fastq -i SRR1542719.fastq -d . -m mature.fa -p hairpin.fa -s hsa -a null -f miFam.dat --novel 1 --other mmu -g genome.fa --index genome.idx -t 6

+

+(3) use mirpro_arm_switch to detect "arm switching" phenomenon:

 These are the sample names and corresponding treatments:
Sample Treatment

@@ -369,30 +364,23 @@

 SRR1542718 control

 SRR1542719 ET1
-Go to the "result/" folder;

-mirpro_armSwitch -i arm.csv -o armSwitch.csv -t control -t ET1 -t control -t ET1 -t control -t ET1

-

-Quick notes

-

-


-(1) To skip adapter trimming process, add command: "-a 0"; For example:

-mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a 0 -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf

-

-(2) To skip seed region check, add command: "--seed 0"; For example:

-mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG --seed 0 -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf

-

-(3) To enable multi thread, add command: "-t <Number of="" threads="">"; For example:

-mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf -t 4

-

-(4) To test whether other patterns (not poly(A) or poly(U) tail) of 5'/3' non-templated nucleotide additions include the adapter sequence, use test_tail.pl in mirPRo/bin/. The input file can be "result/3_other_form.csv" or "result/5_other_form.csv".

-Usage: perl test_tail.pl <input_file> <adapter sequence="">

+    mirpro_arm_switch -i result/arm.csv -o result/armSwitch.csv -t control -t ET1 -t control -t ET1 -t control -t ET1

+

+Important Notes

+

+(1) To skip adapter trimming process, set "-a null"; 

+

+(2) To skip seed region check, set "--seed 0";

+

+(3) To test whether other patterns (not poly(A) or poly(U) tail) of 5'/3' non-templated nucleotide additions include the adapter sequence, use "script/test_tail.pl". The input file can be "result/3_other_form.csv" or "result/5_other_form.csv".

+

+    Usage: perl test_tail.pl <input_file> <adapter sequence="">

+

 For example:

 perl test_tail.pl result/3_other_form.csv ATCTCGTATGCCGTCTTCTGCTTG

 The result will show:

 found number: 0

 It means that there is no adapter sequences in other patterns of 3'non-templated nucleotide additions.

-


-

####Where to find the result files
@@ -403,6 +391,7 @@

 #####1. Most useful results
In "result/":

+

 3_other_form.csv: sequences and counts of other patterns of non-templated nucleotide in 3' end in all samples.

 5_other_form.csv: sequences and counts of other patterns of non-templated nucleotide in 5' end in all samples.

 arm.csv: includes the information of dominant forms (5p or 3p; read counts with ratio > 2 and difference > 10) of mature miRNAs with two possible forms generated from the same precursors in all samples.

@@ -428,6 +417,7 @@

 #####2. Other detailed results for each sample
In "result/XXX/" (XXX is the name of one sample):

+

 XXX_addition_nucleotide_pattern.csv: sequences and counts of other patterns of non-templated nucleotide in 5' and 3' end in the sample.

 XXX_arm.csv: includes the information of dominant forms (5p or 3p; read counts with ratio > 2 and difference > 10) of mature miRNAs with two possible forms generated from the same precursors in the sample.

 XXX_clipped_read_num: the number of reads after adapter trimming.

@@ -455,6 +445,7 @@

 XXX_variation_report.csv: the counts and percentages (in counted reads) of the miRNAs that have sequence differences compared with corresponding mature miRNAS in the sample.
In "result/XXX/mapping_report/":

+

 3-softclip_mapped.arf: the arf file of read-to-hairpin mappings with only 3' soft clip. 

 5-softclip_mapped.arf: the arf file of read-to-hairpin mappings with only 5' soft clips. 

 both_end_softclip_mapped.arf: the arf file of read-to-hairpin mappings with both 5' and 3' soft clips. 

@@ -464,11 +455,11 @@

 mismatch_mapped.arf: the arf file of read-to-hairpin mappings with only mismatches.

 multi_mapped.arf: the arf file of read-to-hairpin mappings of reads with multiple mappings.

 perfect_mapped.arf: the arf file of perfect read-to-hairpin mappings.

-unique_mapped.arf: the arf file of read-to-hairpin mappings of reads with unique mappings.

-

####How to use result files to perform statistical analysis

+

 R package DESeq or DESeq2 can be used for downstream statistical analysis.

+

 (1) For known miRNA gene differential expression analysis, please use "result/result_precursor.csv"  as the input count table;

 (2) For known and novel miRNA gene differential expression analysis, please merge "result/result_precursor.csv" and "result/result_novel_precursor.csv" to one count table and use it as the input;

 (3) For known miRNA gene family differential expression analysis, please use "result/result_family.csv"  as the input count table;

User manual modified by Jieming Shi

Jieming Shi — Wed, 24 Feb 2016 15:44:50 -0000

--- v40
+++ v41
@@ -163,10 +163,10 @@
 -d <output_directory>: directory for output files; eg. ./miRNA_output/;
 -m <mature_miRNA_sequence_file>: mature miRNA file downloaded from miRBase, FASTA format;
 -p <pre-miRNA_sequence_file>: precursor miRNA file downloaded from miRBase, FASTA format;
--s <species 0="">: three-letter code for the species you want to analyze in miRBase;
+-s <species|0>: three-letter code for the species you want to analyze in miRBase;
    eg. mmu for mouse; hsa for human; if your species is not in miRBase, use "-s 0",
    and add optional parameters to predict novel miRNAs;
--a <adapter_sequence 0="">: adapter sequence; if data has no adapter, set 0;
+-a <adapter_sequence|0>: adapter sequence; if data has no adapter, set 0;

 [optional parameters]

User manual modified by Jieming Shi

Jieming Shi — Tue, 08 Dec 2015 15:44:22 -0000

--- v39
+++ v40
@@ -1,6 +1,6 @@
 #miRPro user manual
-Version: 1.0
-Date: 2015/11/09
+Version: 1.0.1
+Date: 2015/12/07
 


 ###Table of Contents

User manual modified by Jieming Shi

Jieming Shi — Mon, 09 Nov 2015 16:44:50 -0000

--- v38
+++ v39
@@ -1,6 +1,6 @@
 #miRPro user manual
-Version: v.20150930
-Date: 2015/09/30
+Version: 1.0
+Date: 2015/11/09
 


 ###Table of Contents
@@ -163,7 +163,9 @@
 -d <output_directory>: directory for output files; eg. ./miRNA_output/;
 -m <mature_miRNA_sequence_file>: mature miRNA file downloaded from miRBase, FASTA format;
 -p <pre-miRNA_sequence_file>: precursor miRNA file downloaded from miRBase, FASTA format;
--s <species>: species you want to analyze; eg. mmu for mouse; hsa for human;
+-s <species 0="">: three-letter code for the species you want to analyze in miRBase;
+   eg. mmu for mouse; hsa for human; if your species is not in miRBase, use "-s 0",
+   and add optional parameters to predict novel miRNAs;
 -a <adapter_sequence 0="">: adapter sequence; if data has no adapter, set 0;

 [optional parameters]
@@ -216,6 +218,10 @@
  For prediction of novel miRNAs, you should add the following parameters:
    -novel 1 --other <related_speceis> -g <genome_sequence> --index <novelalign_genome_index>
+   
+For prediction of novel miRNAs without known miRNA quantification, set "-s 0", and add the following parameters:
+   -novel 1 --other <related_speceis> -g <genome_sequence> --index <novelalign_genome_index>
+
 Each time you perform novel miRNA prediction, you will get different results because the third-party program "randfold" can generate different ourput p-values each time you run it with the same input.
 And for those novel miRNAs around the cut-off score, they might be infulenced because of the inconsistent "randfold" p-values.
 So you if you want to get consistent results for novel miRNA prediction, please turn off "randfold" by "-r 0".

User manual modified by Jieming Shi

Jieming Shi — Sat, 24 Oct 2015 17:44:14 -0000

--- v37
+++ v38
@@ -21,14 +21,14 @@

 #####1. FASTX-Toolkit

-Go to http://hannonlab.cshl.edu/fastx_toolkit/download.html and follow the instruction in "Program Installation" to install the latest toolkit.
+Go to http://hannonlab.cshl.edu/fastx_toolkit/download.html and follow the instruction in "Program Installation" to install the toolkit (version 0.0.14).

 **Warning**: the prerequisite of FASTX-Toolkit includes pkg-config, gcc, and wget. Also, the compatible version of 
-libgtextutils is needed before you install FASTX-Toolkit. 
+libgtextutils (version 0.7) is needed before you install FASTX-Toolkit. 

 #####2. RNAfold

-Go to http://www.tbi.univie.ac.at/RNA/index.html#download and download the latest ViennaRNA Package.
+Go to http://www.tbi.univie.ac.at/RNA/index.html#download and download the ViennaRNA Package (version 2.1.9).

 Alternatively, you can install Ubuntu package from PPA:
 \# sudo apt-add-repository ppa:j-4/vienna-rna
@@ -45,7 +45,7 @@

 #####4. Novoalign

-Go to http://www.novocraft.com/support/download/ and download the latest Novoalign.
+Go to http://www.novocraft.com/support/download/ and download Novoalign (release V3.02.12).

 For instance, download novocraftV3.02.12.Linux3.0.tar.gz and unzip, then move the whole folder into /usr/local/genome/novocraft folder.  

@@ -55,7 +55,7 @@
 #####5. HTSeq

 Go to http://www-huber.embl.de/users/anders/HTSeq/doc/install.html#installation-on-linux and following the instruction
-to install HTSeq.
+to install HTSeq (version 0.6.1p1).

 #####6. Test if installation is successful

User manual modified by Jieming Shi

Jieming Shi — Sat, 24 Oct 2015 17:14:53 -0000

--- v36
+++ v37
@@ -330,7 +330,7 @@
 novoindex -k 12 -s 1 genome.idx genome.fa

 (2) use mirpro to analyze known and novel miRNAs (rat as related species for novel miRNA prediction):
-m2irpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf -t 4
+mirpro -i SRR333597.fastq -i SRR333598.fastq -i SRR333599.fastq -i SRR333600.fastq -d ./  -m mature.fa -p hairpin.fa -s mmu -a ATCTCGTATGCCGTCTTCTGCTTG -f miFam.dat --novel 1 --other rno -g genome.fa --index genome.idx --gtf annotation.gtf -t 4

 (3) use mirpro_armSwitch to detect "arm switching" phenomenon:
 These are the sample names and corresponding treatments: