| hisat2-build |
hisat2-build [options]* <reference_in> <ht2_base> |
hisat2-build builds a HISAT2 index from a set of DNA sequences. |
| hisat2 |
hisat2 [options]* -x <hisat2-idx> {-1 <m1> -2 <m2> | -U <r> | --sra-acc <SRA accession number>} [-S <sam>] |
Mapping RNA-seq reads with hisat2 |
| 2bwt-builder |
2bwt-builder <FastaPath/YourFasta> |
Build index files for the reference genome before running SOAP |
| STAR |
STAR --runMode genomeGenerate --option1-name option1-value(s) ... |
Generating genome indexes for STAR |
| bamCompare |
bamCompare -b1 treatment.bam -b2 control.bam -o log2ratio.bw |
This tool can be used to generate a bigWig or bedGraph file based on two BAM files that are compared to each other while being simultaneously normalized for sequencing depth. |
| STAR |
STAR --genomeDir /path/to/genomeDir --readFilesIn /path/to/read1 [/path/to/read2] --runThreadN NumberOfThreads --option1-name option1-value(s) ... |
Mapping RNA-seq reads with STAR |
| Bowtie2 |
bowtie2 [options]* -x <bt2-idx> {-1 <m1> -2 <m2> | -U <r> | --interleaved <i> | -b <bam>} [-S <sam>] |
Aligning sequencing reads to long reference sequences. It is particularly good at aligning reads of about 50 up to 100s or 1,000s of characters to relatively long (e.g. mammalian) genomes. Bowtie 2 supports gapped, local, and paired-end alignment modes. |
| gfServer |
gfServer status host port |
Make a server to quickly find where DNA occurs in genome. To set up a server:gfServer start host port file(s)Where the files are .nib or .2bit format files specified relative to the current directory.To remove a server:gfServer stop host portTo query a server with DNA sequence:gfServer query host port probe.faTo query a server with protein sequence:gfServer protQuery host port probe.faTo query a server with translated dna sequence:gfServer transQuery host port probe.faTo query server with PCR primersgfServer pcr host port fPrimer rPrimer maxDistanceTo process one probe fa file against a .nib format genome (not starting server):gfServer direct probe.fa file(s).nibTo test pcr without starting server:gfServer pcrDirect fPrimer rPrimer file(s).nib |
| maq map |
maq map [-n nmis] [-a maxins] [-c] [-1 len1] [-2 len2] [-d adap3] [-m mutrate] [-u unmapped] [-e maxerr] [-M c|g] [-N] [-H allhits] [-C maxhits] out.aln.map in.ref.bfa in.read1.bfq [in.read2.bfq] 2> out.map.log |
Map reads to the reference sequences. |
| crac |
crac -i <index\_file> -k <int> -r <reads\_file1> -o <output\_file> --nb-threads <int> |
For alignment of single-end reads |
| bwa |
bwa mem [-aCHMpP] [-t nThreads] [-k minSeedLen] [-w bandWidth] [-d zDropoff] [-r seedSplitRatio] [-c maxOcc] [-A matchScore] [-B mmPenalty] [-O gapOpenPen] [-E gapExtPen] [-L clipPen] [-U unpairPen] [-R RGline] [-v verboseLevel] db.prefix reads.fq [mates.fq] |
Align 70bp-1Mbp query sequences with the BWA-MEM algorithm. Briefly, the algorithm works by seeding alignments with maximal exact matches (MEMs) and then extending seeds with the affine-gap Smith-Waterman algorithm (SW). |
| makeblastdb |
makeblastdb -in input_reads.fasta -dbtype [nucl|prot] -out input_reads_db |
Create Local BLAST Database |
| bwa |
bwa sampe [-a maxInsSize] [-o maxOcc] [-n maxHitPaired] [-N maxHitDis] [-P] <in.db.fasta> <in1.sai> <in2.sai> <in1.fq> <in2.fq> > <out.sam> |
Generate alignments in the SAM format given paired-end reads. Repetitive read pairs will be placed randomly. |
| blat |
blat database query [-ooc=11.ooc] output.psl |
Fast sequence search command line tool |
| bwa |
bwa aln [-n maxDiff] [-o maxGapO] [-e maxGapE] [-d nDelTail] [-i nIndelEnd] [-k maxSeedDiff] [-l seedLen] [-t nThrds] [-cRN] [-M misMsc] [-O gapOsc] [-E gapEsc] [-q trimQual] <in.db.fasta> <in.query.fq> > <out.sai> |
Find the SA coordinates of the input reads. Maximum maxSeedDiff differences are allowed in the first seedLen subsequence and maximum maxDiff differences are allowed in the whole sequence. |
| htseq-count |
htseq-count [options] sam_file gff_file |
This tool takes an alignment file in SAM or BAM format and feature file in GFF format and calculates the number of reads mapping to each feature. It uses the htseq-count script that is part of the HTSeq python module |
| bwa |
bwa bwasw [-a matchScore] [-b mmPen] [-q gapOpenPen] [-r gapExtPen] [-t nThreads] [-w bandWidth] [-T thres] [-s hspIntv] [-z zBest] [-N nHspRev] [-c thresCoef] <in.db.fasta> <in.fq> [mate.fq] |
Align query sequences in the in.fq file. When mate.fq is present, perform paired-end alignment. The paired-end mode only works for reads Illumina short-insert libraries. In the paired-end mode, BWA-SW may still output split alignments but they are all marked as not properly paired; the mate positions will not be written if the mate has multiple local hits. |
| hisat2-inspect |
hisat2-inspect [options]* <ht2_base> |
hisat2-inspect extracts information from a HISAT2 index about what kind of index it is and what reference sequences were used to build it. When run without any options, the tool will output a FASTA file containing the sequences of the original references (with all non-A/C/G/T characters converted to Ns). It can also be used to extract just the reference sequence names using the -n/--names option or a more verbose summary using the -s/--summary option. |
| bwa |
bwa index [-p prefix] [-a algoType] <in.db.fasta> |
Index database sequences in the FASTA format. |
| crac |
crac -i <index\_file> -k <int> -r <reads\_file1> <reads\_file2> -o <output\_file> --nb-threads <int> |
For alignment of paired-end reads |