Merge pull request #2510 from eseiler/doc/changelog

[DOC] Update Changelog, Readme, and links

CHANGELOG.rst

@@ -13,6 +13,8 @@ Release 2.5.0 might work with older compilers, but there is no support.
 Library Features
 ^^^^^^^^^^^^^^^^
 
+- **Namespace**:
+   - The namespace was changed from ``seqan`` to ``seqan2`` to allow for interoperability with other SeqAn libraries.
 - Sequence I/O:
    - Accepting files that end in ``.fas``.
 - Indexing:
@@ -391,7 +393,7 @@ Library Updates and Selected Bugfixes
 
 - Journaled String Tree (new module):
     - reference compressed string set structure
-    - for more details see the `publication <http://bioinformatics.oxfordjournals.org/content/30/24/3499.short>`_
+    - for more details see the `publication <https://bioinformatics.oxfordjournals.org/content/30/24/3499.short>`_
 
 - STL containers:
     - added a completely new adaptation to SeqAn interfaces that supports all STL containers, also ``std::array`` and ``std::forward_list``

README.md

@@ -37,12 +37,12 @@ The licenses for the applications themselves can be found in the LICENSE files.
 
 ## Prerequisites
 
-Older compiler versions might work but are not supported.
+Older compiler versions might work but are neither supported nor tested.
 
 ### Linux, macOS, FreeBSD
-  * GCC ≥ 10
-  * Clang/LLVM ≥ 11
-  * Intel Compiler ≥ 2022.1.0 (Intel OneAPI)
+  * GCC ≥ 11
+  * Clang/LLVM ≥ 15
+  * Intel oneAPI C++ Compiler 2024.0.2 (IntelLLVM)
 
 ### Windows
   * Visual C++ ≥ 17.0 / Visual Studio ≥ 2022

apps/alf/README

@@ -1,5 +1,5 @@
                *** ALF - Alignment Free Sequence Comparison ***
-                       http://www.seqan.de/projects/alf
+                       https://www.seqan.de/apps/alf
                                 January, 2012
 
 ---------------------------------------------------------------------------
@@ -20,15 +20,15 @@ Table of Contents
 ALF can be used to calculate the pairwise similarity of sequences using
 alignment-free methods. All methods which are implemented are based on
 k-mer counts. More details can be found in the online documentation of the
-alignment-free methods (www.seqan.de). By default, ALF uses the 
+alignment-free methods (www.seqan.de). By default, ALF uses the
 N2 similarity measure.
 
 ---------------------------------------------------------------------------
 2. Installation
 ---------------------------------------------------------------------------
 
 ALF is distributed with SeqAn - The C++ Sequence Analysis Library (see
-http://www.seqan.de). To build ALF from Git do the following:
+https://www.seqan.de). To build ALF from Git do the following:
 
   1) git clone https://github.com/seqan/seqan.git
   2) mkdir -p build/Release
@@ -130,7 +130,7 @@ sequences from the input fasta file, for example:
 ---------------------------------------------------------------------------
 
 These examples use the fasta file "small.fasta" which can be found in
-seqan/apps/alf/example/. Copy this file to the directory where you 
+seqan/apps/alf/example/. Copy this file to the directory where you
 execute alf.
 
 (1) Run ALF with default settings on two sequences:

apps/alf/alf.cpp

@@ -103,7 +103,7 @@ int main(int argc, const char * argv[])
     addTextSection(parser, "Contact and References");
     addListItem(parser, "For questions or comments, contact:", "Jonathan Goeke <goeke@molgen.mpg.de>");
     addListItem(parser, "Please reference the following publication if you used ALF or the N2 method for your analysis:", "Jonathan Goeke, Marcel H. Schulz, Julia Lasserre, and Martin Vingron. Estimation of Pairwise Sequence Similarity of Mammalian Enhancers with Word Neighbourhood Counts. Bioinformatics (2012).");
-    addListItem(parser, "Project Homepage:", "http://www.seqan.de/projects/alf");
+    addListItem(parser, "Project Homepage:", "https://www.seqan.de/apps/alf");
 
     // Parse command line.
     seqan2::ArgumentParser::ParseResult res = seqan2::parse(parser, argc, argv);

apps/bs_tools/README

@@ -15,22 +15,22 @@ Table of Contents
 1. Overview
 ---------------------------------------------------------------------------
 
-BS tools are designed for the analysis of BS-Seq data, from bisulfite read 
+BS tools are designed for the analysis of BS-Seq data, from bisulfite read
 mapping to SNP and methylation level calling at single-nucleotide resolution.
 It consists out of two main tools: Bisar and Casbar.
 
-Bisar reads three-letter mappings of bisulfite reads and computes 
-local pairwise four-letter realignments using an advanced statistical 
+Bisar reads three-letter mappings of bisulfite reads and computes
+local pairwise four-letter realignments using an advanced statistical
 alignment model.
 
-These alignments can be then used in the subsequent tool Casbar for a simultaneous 
-SNP and methylation level calling. A Bayesian model is used to compute the 
-posterior probability for each possible genotype under the observed data 
-and a given methylation level. The methylation level maximizing the 
-posterior probability is determined and the genotype with the highest 
+These alignments can be then used in the subsequent tool Casbar for a simultaneous
+SNP and methylation level calling. A Bayesian model is used to compute the
+posterior probability for each possible genotype under the observed data
+and a given methylation level. The methylation level maximizing the
+posterior probability is determined and the genotype with the highest
 probability is chosen.
 
-The files README.bisar and README.bisar contain detailed documentation of 
+The files README.bisar and README.bisar contain detailed documentation of
 the respective tools.
 
 ---------------------------------------------------------------------------
@@ -60,6 +60,6 @@ or
 ---------------------------------------------------------------------------
 
 More detailed information you can find in the following document:
-http://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
+https://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
 msc_thesis_krakau.pdf?1394119375
 

apps/bs_tools/README.bisar

@@ -18,19 +18,19 @@ Table of Contents
 1. Overview
 ---------------------------------------------------------------------------
 
-Bisar reads three-letter mappings of bisulfite reads and computes 
-local pairwise four-letter realignments using an advanced statistical 
-alignment model. The alignment scoring scheme incorporates the global 
-methylation rate, the bisulfite conversion rate and base qualities combined 
+Bisar reads three-letter mappings of bisulfite reads and computes
+local pairwise four-letter realignments using an advanced statistical
+alignment model. The alignment scoring scheme incorporates the global
+methylation rate, the bisulfite conversion rate and base qualities combined
 with base dependent sequencing error frequencies.
-Mapping qualities are computed and after the final verification step only 
+Mapping qualities are computed and after the final verification step only
 unique four-letter alignments are given out in a SAM file.
 
 ---------------------------------------------------------------------------
 3. Usage
 ---------------------------------------------------------------------------
 
-To get a short usage description of Bisar, you can execute bisar -h or 
+To get a short usage description of Bisar, you can execute bisar -h or
 bisar --help.
 
 Usage: bisar [OPTION]... <MAPPED READ FILE> <GENOME FILE> <READS FILE>
@@ -45,7 +45,7 @@ Usage: bisar [OPTION]... <MAPPED READ FILE> <GENOME FILE> <READS FILE>
   [ -o  FILE ],  [--output-file FILE ]
 
   Mapping output file. Valid filetype is: .sam.
-  
+
   [ -e3 NUM ],  [ --max3-error NUM ]
 
   Max. error rate in 3-letter alphabet. In range [0..100]. Default: 3.
@@ -62,15 +62,15 @@ Usage: bisar [OPTION]... <MAPPED READ FILE> <GENOME FILE> <READS FILE>
 
   Use empirical substitution error frequencies of Illumina sequencing
   data for alignment scoring scheme (corresponding to Dohm et al. 2008).
-   
+
   [ -nsi ],  [ --ns-ins-errors ]
 
-  Use empirical insertion error frequencies of Illumina sequencing data for 
+  Use empirical insertion error frequencies of Illumina sequencing data for
   alignment scoring scheme (corresponding to Minoche et al. 2011).
 
   [ -nsd ],  [ --ns-del-errors ]
 
-  Use empirical deletion error frequencies of Illumina sequencing data for 
+  Use empirical deletion error frequencies of Illumina sequencing data for
   alignment scoring scheme (corresponding to Minoche et al. 2011).
 
   [ -der NUM ],  [ --del-error-rate NUM ]
@@ -118,7 +118,7 @@ Usage: bisar [OPTION]... <MAPPED READ FILE> <GENOME FILE> <READS FILE>
   [ -h ],  [ --help ]
 
   Displays this help message.
-  
+
   [ --version ]
 
   Display version information.
@@ -130,14 +130,14 @@ Usage: bisar [OPTION]... <MAPPED READ FILE> <GENOME FILE> <READS FILE>
 
 The verified four-letter pairwise alignments are given out in SAM format.
 
-See http://samtools.sourceforge.net/ for more details.
+See https://samtools.sourceforge.net/ for more details.
 
 ---------------------------------------------------------------------------
 5. Example
 ---------------------------------------------------------------------------
 
-In order to compute realignments for all reads with up to 4% errors in their 
-three-letter alignment, while allowing up to 5% errors in four-letter 
+In order to compute realignments for all reads with up to 4% errors in their
+three-letter alignment, while allowing up to 5% errors in four-letter
 alignments call:
 
   bisar -e3 4 -e4 5 -o mapped_reads_verified.sam mapped_reads.sam \
@@ -161,8 +161,8 @@ or
 7. References
 ---------------------------------------------------------------------------
 
-More detailed information about the underlying method you can find in the 
+More detailed information about the underlying method you can find in the
 following document:
-http://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
+https://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
 msc_thesis_krakau.pdf?1394119375
 

apps/bs_tools/README.casbar

@@ -19,22 +19,22 @@ Table of Contents
 1. Overview
 ---------------------------------------------------------------------------
 
-Casbar uses pairwise four-letter alignments given in SAM format for 
-simultaneous SNP and methylation level calling. A Bayesian model is used to 
-compute the posterior probability for each possible genotype under the 
-observed data and a given methylation level. The methylation level maximizing 
-the posterior probability is determined and the genotype with the highest 
-probability is chosen. Therefore the bisulfite conversion rate and base 
-qualities, if chosen combined with base dependent sequencing error frequencies, 
-are incorporated. 
-All called SNPs and methylation levels that pass the verification criteria 
-are given out in a VCF and BED file respectively. 
+Casbar uses pairwise four-letter alignments given in SAM format for
+simultaneous SNP and methylation level calling. A Bayesian model is used to
+compute the posterior probability for each possible genotype under the
+observed data and a given methylation level. The methylation level maximizing
+the posterior probability is determined and the genotype with the highest
+probability is chosen. Therefore the bisulfite conversion rate and base
+qualities, if chosen combined with base dependent sequencing error frequencies,
+are incorporated.
+All called SNPs and methylation levels that pass the verification criteria
+are given out in a VCF and BED file respectively.
 
 ---------------------------------------------------------------------------
 3. Usage
 ---------------------------------------------------------------------------
 
-To get a short usage description of Casbar, you can execute casbar -h or 
+To get a short usage description of Casbar, you can execute casbar -h or
 casbar --help.
 
 Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-LEVEL FILE>
@@ -57,31 +57,31 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
 
   [ -mp NUM],  [ --max-pile NUM ]
 
-  Maximal number of matches allowed to pile up at the same genome position. 
+  Maximal number of matches allowed to pile up at the same genome position.
   In range [0..inf]. Default: 0.
-    
+
   [ -mmp ],  [ --merged-max-pile ]
 
   Do pile up correction on merged lanes.
-  
+
   [ -mc NUM ],  [ --min-coverage NUM ]
 
-  Minimal required number of reads covering a candidate position. 
+  Minimal required number of reads covering a candidate position.
   In range [1..inf]. Default: 6.
 
   [ -eb NUM ],  [ --exclude-border NUM ]
 
-  Exclude read positions within eb base pairs of read borders for 
+  Exclude read positions within eb base pairs of read borders for
   SNP calling. Default: 0.
 
   [ -su ],  [ --suboptimal ]
 
   Keep suboptimal reads.
-   
+
   [ -pws NUM ],  [ --parse-window-size NUM ]
 
-  Genomic window size for parsing reads (concerns memory consumption, 
-  choose smaller windows for higher coverage). In range [1..100000]. 
+  Genomic window size for parsing reads (concerns memory consumption,
+  choose smaller windows for higher coverage). In range [1..100000].
   Default: 100000.
 
   [ -I TEXT],  [ --intervals TEXT ]
@@ -94,7 +94,7 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
 
   [ -mm NUM ],  [ --min-mutations NUM ]
 
-  Minimal number of deviating bases for calling. In range [1..inf]. 
+  Minimal number of deviating bases for calling. In range [1..inf].
   Default: 3.
 
   [ -mq NUM],  [ --min-quality NUM ]
@@ -103,17 +103,17 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
 
   [ -mmq NUM],  [ --min-map-quality NUM ]
 
-  Minimum base call quality for a match to be considered. In range [0..inf]. 
+  Minimum base call quality for a match to be considered. In range [0..inf].
   Default: 1.
 
   [ -hes NUM ],  [ --prob-hetero-snp NUM ]
 
-  Heterozygous SNP probability to compute genotype prior probabilities. 
+  Heterozygous SNP probability to compute genotype prior probabilities.
   In range [0..1]. Default: 0.005.
 
   [ -hos NUM],  [ --prob-homo-snp NUM ]
 
-  Homozygous SNP probability to compute genotype prior probabilities. 
+  Homozygous SNP probability to compute genotype prior probabilities.
   In range [0..1]. Default: 0.0005.
 
   [ -msc NUM],  [ --min-score NUM ]
@@ -126,7 +126,7 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
 
   [ -nec ],  [ --ns-errors-calling ]
 
-  Use empirical error frequencies of Illumina sequencing data to compute 
+  Use empirical error frequencies of Illumina sequencing data to compute
   likelihoods in bayesian model (corresponding to Dohm et al. 2008).
 
   [ -v ],  [ --verbose ]
@@ -136,15 +136,15 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
   [ -vv ],  [ --very-verbose ]
 
   Enable very verbose output.
-  
+
   [ -q ],  [ --quiet ]
 
   Set verbosity to a minimum.
 
   [ -h ],  [ --help ]
 
   Displays this help message.
-  
+
   [ --version ]
 
   Display version information.
@@ -154,30 +154,30 @@ Usage:  casbar [OPTIONS] <GENOME FILE> <ALIGNMENT FILE> -o <SNP FILE> -b <METH-L
 4. Output Formats
 ---------------------------------------------------------------------------
 
-All called SNPs that pass the verification criteria are given out in a VCF 
-file. 
+All called SNPs that pass the verification criteria are given out in a VCF
+file.
 
-All called methylation levels that pass the verification criteria 
-are given out in a BED file 
-(BED6 format: chrom, start, end, name, score, strand and methylation level). 
+All called methylation levels that pass the verification criteria
+are given out in a BED file
+(BED6 format: chrom, start, end, name, score, strand and methylation level).
 
 ---------------------------------------------------------------------------
 5. Example
 ---------------------------------------------------------------------------
 
-In order to perform SNP and methylation level calling by taking nonuniform 
-sequencing error probabilities into account call: 
+In order to perform SNP and methylation level calling by taking nonuniform
+sequencing error probabilities into account call:
 
   casbar -nec -o snps.vcf -b meth_levels.bed genome.fa \
    mapped_bisulfite_reads.sam
 
-To perform SNP and methylation level calling by taking nonuniform sequencing 
+To perform SNP and methylation level calling by taking nonuniform sequencing
 error probabilities into account for genomic positions with a coverage >= 6
 call:
-          
+
   casbar -nec -mc 6 -msc 5 -o snps.vcf -b meth_levels.bed genome.fa \
    mapped_bisulfite_reads.sam
-  
+
 The minimum score in this case a SNP or methylation level to be called is 5.
 
 ---------------------------------------------------------------------------
@@ -193,8 +193,8 @@ or
 7. References
 ---------------------------------------------------------------------------
 
-More detailed information about the underlying method you can find in the 
+More detailed information about the underlying method you can find in the
 following document:
-http://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
+https://www.mi.fu-berlin.de/en/inf/groups/abi/theses/master_dipl/krakau/
 msc_thesis_krakau.pdf?1394119375