Option renders program to skip multiple hits reads. If you are not sureĪbout the strand rule, run ‘infer_experiment.py’ĭefault=none (Not a strand specific RNA-seq data) -u, -skip-multi-hits Mapped to ‘+’ => parental gene on ‘-‘ read2 mapped to Read1 mapped to ‘-‘ => parental gene on ‘-‘ read2 Rule is: read1 mapped to ‘+’ => parental gene on ‘+’ d STRAND_RULE, -strand= STRAND_RULEĪ pair-end, strand-specific RNA-seq, and the strand o OUTPUT_PREFIX, -out-prefix= OUTPUT_PREFIX Options: -versionĪlignment file in BAM format (SAM is not supported). Minimum mapping quality for an alignment to be calledĬalculate raw read count, FPM (fragment per million) and FPKM (fragment per million mapped reads per kilobase exon) for each gene in BED file. Sure about the strand rule, run ‘infer_experiment.py’ĭefault=none (Not a strand specific RNA-seq data). Read2 mapped to ‘+’ => parental gene on ‘-‘ read2 On ‘+’ read1 mapped to ‘-‘ => parental gene on ‘-‘ Strand rule is: read1 mapped to ‘+’ => parental gene ForĮxample: –strand=’1++,1–,2+-,2-+’ means that this isĪ pair-end, strand-specific RNA-seq data, and the How read(s) were stranded during sequencing. Ignore this option toĭisable normalization -u, -skip-multi-hits Will be generated for strand-specific RNA-seq data. One wiggle file willīe generated for non strand-specific data, two wiggleįiles (“Prefix_Forward.wig” and “Prefix_Reverse.wig”) (such as “chr1”) should be consistent between thisįile and the BAM file. With 2 columns: first column is chromosome name/ID, s CHROMSIZE, -chromSize= CHROMSIZEĬhromosome size file. bai files shouldīe placed in the same directory. BAM file must be sortedĪnd indexed using samTools.bam and. Show this help message and exit -i INPUT_FILE, -input-file= INPUT_FILEĪlignment file in BAM format. Show program’s version number and exit -h, -help # sort and index BAM files samtools sort - m 1000000000 input. This script uses BigWig? instead of BAM as input, and requires much less memory (~ 200M) With this option, user can normalize different sequencing depth into the same scale when converting BAM into wiggle format.Īdd another script. Some parts were optimized and runs little faster.Īdd normalization option to bam2wig.py. User can use this module to estimate ribosome RNA amount if the input gene list is ribosomal RNA.Īdd read_hexamer.py: Calculate hexamer frequency for multiple input files (fasta or fastq). Inner_distance.py: add ‘PE_within_diff_chrom’Īdd split_bam.py: Split orignal BAM file into small BAM files based on provided gene list. Transform BAM files into fastq format.īam_stat.py: Now counts ‘Proper-paired reads map to different chrom’īam2wig.py: automatically call ‘wigToBigwig’ if it can be found in system $PATH Generate heatmap to visualize gene body coverage over many samples.Īdd bam2fq.py. Input a directory containing BAM file ( s ). Input plain text file containing the path of BAM file ( s ). Input several BAM files ( separated by "," ). It does not report exon and intron level count.ġ. FPKM.py will report “raw fragment count”, “FPM” and “FPKM” for each gene. This happened when reads were clipped and spliced mapped simultaneously.Īdd FPKM.py. “bam_stat.py” prints summary statistics to STDOUT.įix bugs in “insertion_profile.py”, “clipping_profile.py”, and “inner_distance.py “įix bug in “junction_annotation.py” in that it would report some “novel splice junctions” that don’t exist in the BAM files. Remove “RPKM_count.py” as it generates erroneous results especially for longer reads. bx-python and pysam will be installed automatically if they haven’t been installed before.įix a bug in “read_quality.py” that does not return results if input file containing less than 1000 reads.
Users could install RSeQC using pip: pip install RSeQC. Two dependency packages bx-python and pysam are not shipped with RSeQC starting from v2.6.4. Please use previous versions (v2.6.5 or older) if you are using Python2. Junctions detected from the junction_annotation.py will be converted into Interact format file, which can be uploaded into UCSC genome browser for visualization. Add FPKM-UQ.py to calcualte HTSeq count, FPKM and FPKM-UQ values defined by TCGAįPKM-UQ.py could exactly reproduce TCGA FPKM-UQ values, if you use TCGA BAM file (or follow TCGA RNA-seq alignment workflow to generate your own BAM file), the GDC.h38 GENCODE v22 GTF file and the GDC.h38 GENCODE TSV file.