From 2c1815c74d5da5dbfe6c7da0aaed85e2ccd59647 Mon Sep 17 00:00:00 2001 From: Zhenguo Zhang Date: Thu, 14 May 2015 14:44:57 -0400 Subject: [PATCH] correct POD: 'indices' => metrics --- README | 26 +++++++++++++++++--------- README.md | 35 ++++++++++++++++++++++------------- lib/Bio/CUA.pm | 6 +++--- lib/Bio/CUA/CUB/Builder.pm | 6 +++--- lib/Bio/CUA/CUB/Calculator.pm | 4 ++-- 5 files changed, 47 insertions(+), 30 deletions(-) diff --git a/README b/README index 9a7ca1e..ac6d899 100644 --- a/README +++ b/README @@ -11,25 +11,25 @@ One amino acid can be encoded by more than one synonymous codon, and synonymous codons are unevenly used. For example, some codons are used more often than other synonymous ones in highly expressed genes (I). To measure the unevenness of codon usage, multiple -indices of codon usage bias have been developed, such as Fop +metrics of codon usage bias have been developed, such as Fop (Frequency of optimal codons), CAI (Codon Adaptation Index), tAI (tRNA Adaptation Index), and ENC (Effective Number of Codons). Biased codon usage is widespread, visible in all species. It is important both to -identify codons having high translational efficiency (often named +identify codons having high translational efficiency (often termed optimal codons) and to study the distribution of codon usage among genes (e.g., genes with more optimal codons versus genes with fewer optimal codons). -So far, no software exists to compute all the above CUB indices, and -it is worse that parameters in existing software are often fixed, -so one can compute certain types of CUB indices for a limited list of -species and can not modify parameters. For example, when one wants to +So far, no software implements all the above CUB metrics in one place. +More importantly, parameters in existing software are often fixed, +so one can compute certain types of CUB metrics for a limited list of +species and cannot tune parameters. For example, when one wants to identify optimal codons in certain tissues, it may be better to use -most highly expressed genes to calculate CAI index, which is +most highly expressed genes of that tissue to calculate CAI, which is impossible with existing software. This package mainly solves these two problems: providing tools -computing all common CUB indices and allowing users to tune parameters +computing all common CUB metrics and allowing users to tune parameters freely. We also incorporate or extend some method variants, such as GC-content corrected ENC, background-data normalized CAI, etc. See the relevant methods' description in CUB classes for more details. @@ -39,12 +39,15 @@ See the relevant methods' description in CUB classes for more details. To install this module, run the following commands: +a. If install after downloading the package, + perl Makefile.PL make make test make install -or install directly from CPAN as +b. install directly from CPAN as + cpan Bio::CUA 4. SUPPORT AND DOCUMENTATION @@ -88,3 +91,8 @@ GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see L. +6. CITATION + +Zhenguo Zhang and Daven C. Presgraves, CUA: a Flexible Codon Usage +Analyzer (In preparation) + diff --git a/README.md b/README.md index 1cee8c7..ad94501 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,9 @@ -##1. Bio-CUA +##1. Bio-CUA + Version: 1.01 -##2. Purpose +##2. Purpose + The aim of this distribution is to provide comprehensive and flexible tools to analyze codon usage bias (CUB) and relevant problems. @@ -9,25 +11,25 @@ One amino acid can be encoded by more than one synonymous codon, and synonymous codons are unevenly used. For example, some codons are used more often than other synonymous ones in highly expressed genes (I). To measure the unevenness of codon usage, multiple -indices of codon usage bias have been developed, such as Fop +metrics of codon usage bias have been developed, such as Fop (Frequency of optimal codons), CAI (Codon Adaptation Index), tAI (tRNA Adaptation Index), and ENC (Effective Number of Codons). Biased codon usage is widespread, visible in all species. It is important both to -identify codons having high translational efficiency (often named +identify codons having high translational efficiency (often termed optimal codons) and to study the distribution of codon usage among genes (e.g., genes with more optimal codons versus genes with fewer optimal codons). -So far, no software exists to compute all the above CUB indices, and -it is worse that parameters in existing software are often fixed, -so one can compute certain types of CUB indices for a limited list of -species and can not modify parameters. For example, when one wants to +So far, no software implements all the above CUB metrics in one place. +More importantly, parameters in existing software are often fixed, +so one can compute certain types of CUB metrics for a limited list of +species and cannot tune parameters. For example, when one wants to identify optimal codons in certain tissues, it may be better to use -most highly expressed genes to calculate CAI index, which is +most highly expressed genes of that tissue to calculate CAI, which is impossible with existing software. This package mainly solves these two problems: providing tools -computing all common CUB indices and allowing users to tune parameters +computing all common CUB metrics and allowing users to tune parameters freely. We also incorporate or extend some method variants, such as GC-content corrected ENC, background-data normalized CAI, etc. See the relevant methods' description in CUB classes for more details. @@ -37,13 +39,15 @@ See the relevant methods' description in CUB classes for more details. To install this module, run the following commands: +a. If install after downloading the package, + perl Makefile.PL make make test make install -or install directly from CPAN as - +b. install directly from CPAN as + cpan Bio::CUA ##4. SUPPORT AND DOCUMENTATION @@ -85,5 +89,10 @@ MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License -along with this program. If not, see http://www.gnu.org/licenses/. +along with this program. If not, see L. + +##6. CITATION + +Zhenguo Zhang and Daven C. Presgraves, CUA: a Flexible Codon Usage +Analyzer (In preparation) diff --git a/lib/Bio/CUA.pm b/lib/Bio/CUA.pm index d5aff46..9291bce 100644 --- a/lib/Bio/CUA.pm +++ b/lib/Bio/CUA.pm @@ -39,15 +39,15 @@ One amino acid can be encoded by more than one synonymous codon, and synonymous codons are unevenly used. For example, some codons are used more often than other synonymous ones in highly expressed genes (I). To measure the unevenness of codon usage, multiple -indices of codon usage bias have been developed, such as Fop +metrics of codon usage bias have been developed, such as Fop (Frequency of optimal codons), CAI (Codon Adaptation Index), tAI (tRNA Adaptation Index), and ENC (Effective Number of Codons). The causes of CUB phenomena are complicated, including, mutational bias, selection on translational efficiency or accurancy. CUB is one fundamental concept in genetics. -So far, no software exists to compute all the above CUB indices, and -worse is that parameters of CUB calculations are often fixed in +So far, no software exists to compute all the above CUB metrics, and +more importantly parameters of CUB calculations are often fixed in software, so one can only analyze genes in a limited list of species and one can not incorporate its own parameters such as sequences of highly expressed genes in a tissue. diff --git a/lib/Bio/CUA/CUB/Builder.pm b/lib/Bio/CUA/CUB/Builder.pm index e6160c6..1f983d1 100644 --- a/lib/Bio/CUA/CUB/Builder.pm +++ b/lib/Bio/CUA/CUB/Builder.pm @@ -5,7 +5,7 @@ package Bio::CUA::CUB::Builder; =head1 NAME Bio::CUA::CUB::Builder -- A module to calculate codon usage bias (CUB) -indices at codon level and other parameters +metrics at codon level and other parameters =head1 SYNOPSIS @@ -31,9 +31,9 @@ indices at codon level and other parameters Codon usage bias (CUB) can be represented at two levels, codon and sequence. The latter is often computed as the geometric means of the -sequence's codons. This module caculates CUB indices at codon level. +sequence's codons. This module caculates CUB metrics at codon level. -Supported CUB indices include CAI (codon adaptation index), tAI (tRNA +Supported CUB metrics include CAI (codon adaptation index), tAI (tRNA adaptation index), RSCU (relative synonymous codon usage), and their variants. See the methods below for details. diff --git a/lib/Bio/CUA/CUB/Calculator.pm b/lib/Bio/CUA/CUB/Calculator.pm index c526f84..b416b31 100644 --- a/lib/Bio/CUA/CUB/Calculator.pm +++ b/lib/Bio/CUA/CUB/Calculator.pm @@ -31,10 +31,10 @@ Bio::CUA::CUB::Calculator -- A module to calculate codon usage bias Codon usage bias (CUB) can be represented at two levels, codon and sequence. The latter is often computed as the geometric means of the -sequence's codons. This module caculates CUB indices at sequence +sequence's codons. This module caculates CUB metrics at sequence level. -Supported CUB indices include CAI (codon adaptation index), tAI (tRNA +Supported CUB metrics include CAI (codon adaptation index), tAI (tRNA adaptation index), Fop (Frequency of optimal codons), ENC (Effective Number of Codons) and their variants. See the methods below for details.