NAME

       htseq-count - Count the number of reads in a SAM alignment file that map to GFF features

       Given  a  file with aligned sequencing reads and a list of genomic features, a common task
       is to count how many reads map to each feature.

       A feature is here an interval (i.e., a range of positions) on a chromosome or a  union  of
       such intervals.

       In  the  case  of RNA-Seq, the features are typically genes, where each gene is considered
       here as the union of all its exons. One may also consider each exon as a feature, e.g., in
       order  to check for alternative splicing.  For comparative ChIP-Seq, the features might be
       binding region from a pre-determined list.

       Special care must be taken to decide how to deal with reads that  overlap  more  than  one
       feature.  The  htseq-count script allows to choose between three modes. Of course, if none
       of these fits your needs, you can write your own script with HTSeq. See the  chapter  tour
       for a step-by-step guide on how to do so.

       The  three overlap resolution modes of htseq-count work as follows. For each position i in
       the read, a set S(i) is defined as the set of all features overlapping position  i.  Then,
       consider the set S, which is (with i running through all position within the read)

       · the union of all the sets S(i) for mode union.

       · the intersection of all the sets S(i) for mode intersection-strict.

       · the intersection of all non-empty sets S(i) for mode intersection-nonempty.

       If  S contains precisely one feature, the read is counted for this feature. If it contains
       more than one feature, the  read  is  counted  as  ambiguous  (and  not  counted  for  any
       features), and if S is empty, the read is counted as no_feature.

       The following figure illustrates the effect of these three modes: [image]

USAGE

       After  you  have  installed  HTSeq (see install), you can run htseq-count from the command
       line:

          htseq-count [options] <sam_file> <gff_file>

       If the file htseq-qa is not in your path, you can, alternatively, call the script with

          python -m HTSeq.scripts.count [options] <sam_file> <gff_file>

       The <sam_file> contains the aligned reads in the  SAM  format.  (Note  that  the  SAMtools
       contain  Perl  scripts  to  convert  most  alignment  formats to SAM.)  Make sure to use a
       splicing-aware aligner such as TopHat. HTSeq-count makes full use of  the  information  in
       the CIGAR field.

       To read from standard input, use - as <sam_file>.

       If  you  have paired-end data, you have to sort the SAM file by read name first.  (If your
       sorting tool cannot handle big files, try e.g. Ruan Jue's msort, available from  the  SOAP
       web site.)

       The <gff_file> contains the features in the GFF format.

       The script outputs a table with counts for each feature, followed by the special counters,
       which count reads that were not counted for any feature for various reasons, namely:

       · no_feature: reads which could not be assigned to any feature (set S as  described  above
         was empty).

       · ambiguous:  reads which could have been assigned to more than one feature and hence were
         not counted for any of these (set S had mroe than one element).

       · too_low_aQual: reads which were not counted due to the -a option, see below

       · not_aligned: reads in the SAM file without alignment

       · alignment_not_unique: reads with more than one  reported  alignment.   These  reads  are
         recognized from the NH optional SAM field tag.  (If the aligner does not set this field,
         multiply aligned reads will be counted multiple times.)

       Important: The default for strandedness is yes. If your RNA-Seq data  has  not  been  made
       with  a  strand-specific  protocol, this causes half of the reads to be lost.  Hence, make
       sure to set the option --stranded=no unless you have strand-specific data!

   Options
       -m <mode>, --mode=<mode>
              Mode to handle reads overlapping more than one feature. Possible values for  <mode>
              are union, intersection-strict and intersection-nonempty (default: union)

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

              For  stranded=no,  a  read  is  considered overlapping with a feature regardless of
              whether it is mapped to the same or  the  opposite  strand  as  the  feature.   For
              stranded=yes  and single-end reads, the read has to be mapped to the same strand as
              the feature. For paired-end reads, the first read has to be on the same strand  and
              the  second  read  on  the  opposite strand.  For stranded=reverse, these rules are
              reversed.

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

       -t <feature type>, --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 and Ensembl GTF files: exon)

       -i <id attribute>, --idattr=<id attribute>
              GFF attribute to be used as feature ID. Several GFF lines with the same feature  ID
              will be considered as parts of the same feature. The feature ID is used to identity
              the counts in the output table. The default, suitable for RNA-SEq and  Ensembl  GTF
              files, is gene_id.

       -o <samout>, --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')

       -q, --quiet
              suppress progress report and warnings

       -h, --help
              Show a usage summary and exit

AUTHOR

       Simon Anders

COPYRIGHT

       2010, Simon Anders