Changes between Initial Version and Version 1 of SOPs/SAMBAMqc

Timestamp:

04/27/16 11:13:37 (9 years ago)

Author:

ibarrasa

Comment:

--

SOPs/SAMBAMqc

@@ +1 @@
+= SAM/BAM quality control =
+
+\\
+
+= Analyzing short read quality (after mapping) =
+
+== Remove Duplicates ==
+  * Remove duplicates, for eg. from PCR
+
+ {{{
+   #samtools command
+    samtools rmdup [-sS] <input.srt.bam> <output.bam>
+    -s or -S depending on PE data or not
+}}}
+
+== Determining the paired-end insert size for DNA samples ==
+
+If paired-end insert size or distance is unknown or need to be verified, it can be extracted from a BAM/SAM file after running Bowtie.  
+
+When mapping with bowtie (or another mapper), the insert size can often be included as an input parameter (example for bowtie: -X 500), which can help with mapping.  See the [[http://barcwiki.wi.mit.edu/wiki/SOPs/mapping|mapping SOP]] for mapping details.
+
+
+Method 1: Get insert sizes from BAM file
+{{{
+   # Using a SAM file (at Unix command prompt)
+   awk -F "\t" '$9 > 0 {print $9}' s_1_bowtie.sam > s_1_insert_sizes.txt
+   # Using a BAM file (at Unix command prompt)
+   samtools view s_1_bowtie.bam | awk -F"\t" '$9 > 0 {print $9}' > s_1_insert_sizes.txt
+
+   # and then process column of numbers with R (or Excel)
+   # In R Session
+   sizeFile = "s_1_insert_sizes.txt"
+   sample.name = "My paired reads"
+   distance = read.delim(sizeFile, h=F)[,1]
+   pdf(paste(sample.name, "insert.size.histogram.pdf", sep="."), w=11, h=8.5)
+   hist(distance, breaks=200, col="wheat", main=paste("Insert sizes for", sample.name), xlab="length (nt)")
+   dev.off()
+}}}
+
+Method 2: Calculate insert sizes with CollectInsertSizeMetrics function from picard (http://picard.sourceforge.net).  This is also a good approximation for RNA samples.
+{{{
+   # 
+   # I=File    Input SAM or BAM file.  (Required)
+   # O=File    File to write the output to.  (Required)
+   # H=File    File to write insert size histogram chart to.  (Required)
+   # output: CollectInsertSizeMetrics.txt: values for -r and --mate-std-dev can be found in this text file
+   #         CollectInsertSizeMetrics_hist.pdf: insert size histogram (graphic representation)
+bsub java -jar  /usr/local/share/picard-tools/CollectInsertSizeMetrics.jar I=foo.bam O=CollectInsertSizeMetrics.txt H=CollectInsertSizeMetrics_hist.pdf
+}}}
+
+
+== Quality control after mapping== 
+== QC to get a (visual) summary of mapping statistics.  For eg. coverage/distribution of mapped reads across the genome or transcriptome ==
+
+See [[https://sequencing.qcfail.com/|QC Fail Sequencing]] from the Babraham Institute
+
+
+
+
+==== [http://broadinstitute.github.io/picard/ | Picard]: CollectRnaSeqMetrics.jar to find coverage across gene body for 5' or 3' bias ====
+==== [RNA-seq only] Get global coverage profile across transcripts ====
+
+Do reads come from across the length of a typical transcript, or is there 3' or 5' bias (where most reads come from one end of a typical transcript)?
+
+One way to look at this is with Picard's CollectRnaSeqMetrics tool
+{{{
+   # Usage:
+   java -jar /usr/local/share/picard-tools/CollectRnaSeqMetrics.jar INPUT=bamFile REF_FLAT=refFlatFile STRAND_SPECIFICITY=NONE OUTPUT=outputFile REFERENCE_SEQUENCE=/path/to/genome.fa CHART_OUTPUT=output.pdf VALIDATION_STRINGENCY=SILENT
+   # Example command
+   java -jar /usr/local/share/picard-tools/CollectRnaSeqMetrics.jar INPUT=WT.bam REF_FLAT=/nfs/genomes/mouse_mm10_dec_11_no_random/anno/refFlat.txt STRAND_SPECIFICITY=NONE OUTPUT=QC_metrics/WT.RnaSeqMetrics.txt REFERENCE_SEQUENCE=/nfs/genomes/mouse_mm10_dec_11_no_random/fasta_whole_genome/mm10.fa CHART_OUTPUT=QC_metrics/WT.RnaSeqMetrics.pdf VALIDATION_STRINGENCY=SILENT
+
+}}}
+The VALIDATION_STRINGENCY=SILENT option will keep the program from crashing if it finds something unexpected.  The default: VALIDATION_STRINGENCY=STRICT
+
+
+
+
+
+==== [http://qualimap.bioinfo.cipf.es/ | QualiMap]: can be used on DNA or RNA-Seq to get summary of mapping and coverage/distribution ====
+{{{
+# Graphical interface: enter 'qualimap' on the command line
+# Command line:
+unset DISPLAY  #needed for submitting to cluster
+bsub "qualimap bamqc -bam myFile.bam -outdir output_qualimap"
+# For huge data, you can increase memory with --java-mem-size="4800M" to avoid OutOfMemoryError: Java heap space
+
+
+#rnaseq qc
+bsub "qualimap rnaseq -bam myFile.bam -gtf Homo_sapiens.GRCh37.72.canonical.gtf -outdir output_qualimap_rnaseq -p non-strand-specific"
+
+#counts qc (after using htseq-count or similar program to generate a matrix of counts)
+qualimap counts -d countsqc_input.txt -c -s HUMAN -outdir counts_qc
+#Format of countsqc_input.txt (below), totalCounts.txt is a matrix of counts; header lines must be commented "#" and species is human or mouse only.
+#Sample Condition       Path    Column
+HMLE1   HMLE    totalCounts.txt 2
+HMLE2   HMLE    totalCounts.txt 3
+HMLE3   HMLE    totalCounts.txt 4
+N81     N8      totalCounts.txt 5
+N82     N8      totalCounts.txt 6
+N83     N8      totalCounts.txt 7
+
+}}}
+
+
+
+==== [http://rseqc.sourceforge.net/ | RSeQC]: RNA-Seq quality control package for getting mapping statistics (eg. unique/multi-mapped reads) ====
+{{{
+bam_stat.py -i myFile.bam
+}}}
+==== infer_experiment.py from RseQC package: can be used to check if the RNA-seq reads are stranded. ====
+{{{
+
+# Command line:
+
+bsub infer_experiment.py -i accepted_hits.bam -r hs.bed
+
+-i INPUT_FILE in SAM or BAM format
+-r Reference gene model in bed fomat.
+
+# sample output on strand-specific PE reads:
+This is PairEnd Data
+Fraction of reads explained by "1++,1--,2+-,2-+": 0.0193
+Fraction of reads explained by "1+-,1-+,2++,2--": 0.9807
+Fraction of reads explained by other combinations: 0.0000
+
+# sample output on non-stranded PE reads:
+This is PairEnd Data
+Fraction of reads explained by "1++,1--,2+-,2-+": 0.5103
+Fraction of reads explained by "1+-,1-+,2++,2--": 0.4897
+Fraction of reads explained by other combinations: 0.0000
+
+For pair-end RNA-seq, there are two different ways to strand reads:
+  i) 1++,1--,2+-,2-+
+     read1 mapped to '+' strand indicates parental gene on '+' strand
+     read1 mapped to '-' strand indicates parental gene on '-' strand
+     read2 mapped to '+' strand indicates parental gene on '-' strand
+     read2 mapped to '-' strand indicates parental gene on '+' strand
+  ii) 1+-,1-+,2++,2--
+     read1 mapped to '+' strand indicates parental gene on '-' strand
+     read1 mapped to '-' strand indicates parental gene on '+' strand
+     read2 mapped to '+' strand indicates parental gene on '+' strand
+     read2 mapped to '-' strand indicates parental gene on '-' strand
+
+For single-end RNA-seq, there are two different ways to strand reads:
+  i) ++,--
+     read mapped to '+' strand indicates parental gene on '+' strand
+     read mapped to '-' strand indicates parental gene on '-' strand
+  ii) +-,-+
+     read mapped to '+' strand indicates parental gene on '-' strand
+     read mapped to '-' strand indicates parental gene on '+' strand
+
+
+}}}
+
+
+\\
+