Title: NSD_CR_20230612
Project: (none)
Started on: 6/20/2023 10:21:49
Hostname: login1.ufhpc
Run directory: /blue/licht/runs/NSD2-E1099K-Project/NSD_CR_2023-06-12/NSD_CR_20230612
Configuration NSD_CR_20230612.conf
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Table of contents:
- Input data
- Trimming and quality control
- Mapping to genome
- Genome coverage
- Peak detection
- Fraction of Reads in Peaks
- Differential peak detection
- MultiQC report
- UCSC hub
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1. Input data
The following table summarizes the samples, conditions, and contrasts in this analysis. A readset is either a single fastq file or a pair of fastq files (for paired-end sequencing).
| Category | Data |
| Summary of input data |
| Experimental conditions: | WT-H3K4me3, MUT-H3K4me3, WT-HA, MUT-HA |
| Contrasts: | MUT-H3K4me3 vs. WT-H3K4me3, MUT-HA vs. WT-HA |
| Number of samples | 8 |
| Sequencing data data |
| Total number of reads: | 227,852,021 |
| Average reads per sample: | 28,481,502 |
Table 1. Summary of input data
| Condition | Sample | Number of reads | % Reads |
| WT-H3K4me3 | RCH-ACV-2C-H3K4me3 | 31,651,117 | 13.89% |
| MUT-H3K4me3 | RCH-ACV-9B-H3K4me3 | 29,444,850 | 12.92% |
| WT-HA | RCH-ACV-2C-HA-Tag-Rep1 | 22,735,425 | 9.98% |
| RCH-ACV-2C-HA-Tag-Rep2 | 24,130,676 | 10.59% |
| MUT-HA | RCH-ACV-9B-HA-Tag-Rep1 | 28,349,272 | 12.44% |
| RCH-ACV-9B-HA-Tag-Rep2 | 25,110,372 | 11.02% |
Table 2. Number of reads in each sample.
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2. Trimming and quality control
The input sequences were trimmed using trimmomatic. Quality control was performed before and after trimming using FastQC. The following table provides links to the
quality control reports before and after trimming, as well as the number of reads in the trimmed files.
| Sample | Readset | Reads before trim | QC before trim | Reads after trim | QC after trim | % Retained |
| RCH-ACV-2C-H3K4me3 | RCH-ACV-2C-H3K4me3_r1 | 31,651,117 | RCH-ACV-2C-H3K4me3_S22_L004_R1_001
RCH-ACV-2C-H3K4me3_S22_L004_R2_001 | 30,395,476 | RCH-ACV-2C-H3K4me3_S22_L004_R1_001.trim.paired
RCH-ACV-2C-H3K4me3_S22_L004_R2_001.trim.paired | 96.03% |
| RCH-ACV-2C-IgG | RCH-ACV-2C-IgG_r1 | 34,433,550 | RCH-ACV-2C-IgG_S21_L004_R1_001
RCH-ACV-2C-IgG_S21_L004_R2_001 | 33,065,209 | RCH-ACV-2C-IgG_S21_L004_R1_001.trim.paired
RCH-ACV-2C-IgG_S21_L004_R2_001.trim.paired | 96.03% |
| RCH-ACV-9B-H3K4me3 | RCH-ACV-9B-H3K4me3_r1 | 29,444,850 | RCH-ACV-9B-H3K4me3_S18_L004_R1_001
RCH-ACV-9B-H3K4me3_S18_L004_R2_001 | 28,145,143 | RCH-ACV-9B-H3K4me3_S18_L004_R1_001.trim.paired
RCH-ACV-9B-H3K4me3_S18_L004_R2_001.trim.paired | 95.59% |
| RCH-ACV-9B-IgG | RCH-ACV-9B-IgG_r1 | 31,996,759 | RCH-ACV-9B-IgG_S17_L004_R1_001
RCH-ACV-9B-IgG_S17_L004_R2_001 | 30,592,417 | RCH-ACV-9B-IgG_S17_L004_R1_001.trim.paired
RCH-ACV-9B-IgG_S17_L004_R2_001.trim.paired | 95.61% |
| RCH-ACV-2C-HA-Tag-Rep1 | RCH-ACV-2C-HA-Tag-Rep1_r1 | 22,735,425 | RCH-ACV-2C-HA-Tag-Rep1_S23_L004_R1_001
RCH-ACV-2C-HA-Tag-Rep1_S23_L004_R2_001 | 21,866,097 | RCH-ACV-2C-HA-Tag-Rep1_S23_L004_R1_001.trim.paired
RCH-ACV-2C-HA-Tag-Rep1_S23_L004_R2_001.trim.paired | 96.18% |
| RCH-ACV-2C-HA-Tag-Rep2 | RCH-ACV-2C-HA-Tag-Rep2_r1 | 24,130,676 | RCH-ACV-2C-HA-Tag-Rep2_S24_L004_R1_001
RCH-ACV-2C-HA-Tag-Rep2_S24_L004_R2_001 | 23,333,771 | RCH-ACV-2C-HA-Tag-Rep2_S24_L004_R1_001.trim.paired
RCH-ACV-2C-HA-Tag-Rep2_S24_L004_R2_001.trim.paired | 96.70% |
| RCH-ACV-9B-HA-Tag-Rep1 | RCH-ACV-9B-HA-Tag-Rep1_r1 | 28,349,272 | RCH-ACV-9B-HA-Tag-Rep1_S19_L004_R1_001
RCH-ACV-9B-HA-Tag-Rep1_S19_L004_R2_001 | 27,342,579 | RCH-ACV-9B-HA-Tag-Rep1_S19_L004_R1_001.trim.paired
RCH-ACV-9B-HA-Tag-Rep1_S19_L004_R2_001.trim.paired | 96.45% |
| RCH-ACV-9B-HA-Tag-Rep2 | RCH-ACV-9B-HA-Tag-Rep2_r1 | 25,110,372 | RCH-ACV-9B-HA-Tag-Rep2_S20_L004_R1_001
RCH-ACV-9B-HA-Tag-Rep2_S20_L004_R2_001 | 24,137,270 | RCH-ACV-9B-HA-Tag-Rep2_S20_L004_R1_001.trim.paired
RCH-ACV-9B-HA-Tag-Rep2_S20_L004_R2_001.trim.paired | 96.12% |
Table 3. Number of reads in input files and links to QC reports.
The following two tables report the number of reads before and after QC in each sample and in each condition.
| Sample | Reads before QC | Reads after QC | % Retained |
| RCH-ACV-2C-H3K4me3 | 31,651,117 | 30,395,476 | 96.03% |
| RCH-ACV-2C-IgG | 34,433,550 | 33,065,209 | 96.03% |
| RCH-ACV-9B-H3K4me3 | 29,444,850 | 28,145,143 | 95.59% |
| RCH-ACV-9B-IgG | 31,996,759 | 30,592,417 | 95.61% |
| RCH-ACV-2C-HA-Tag-Rep1 | 22,735,425 | 21,866,097 | 96.18% |
| RCH-ACV-2C-HA-Tag-Rep2 | 24,130,676 | 23,333,771 | 96.70% |
| RCH-ACV-9B-HA-Tag-Rep1 | 28,349,272 | 27,342,579 | 96.45% |
| RCH-ACV-9B-HA-Tag-Rep2 | 25,110,372 | 24,137,270 | 96.12% |
Table 4. Number of reads in each sample before and after QC.
| Condition | Reads before QC | Reads after QC | % Retained |
| WT-H3K4me3 | 31,651,117 | 30,395,476 | 96.03% |
| MUT-H3K4me3 | 29,444,850 | 28,145,143 | 95.59% |
| WT-HA | 46,866,101 | 45,199,868 | 96.44% |
| MUT-HA | 53,459,644 | 51,479,849 | 96.30% |
Table 5. Number of reads in each condition before and after QC.
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3. Mapping to genome
The input sequences were aligned to the genome using Bowtie 2.4.5. The following table reports the number of aligned reads for each
sample. The WIG files can be uploaded to the UCSC
Genome Browser as custom tracks.
| Sample | Total reads | Aligned reads | Concordant alignment rate | Bowtie2 report |
| RCH-ACV-2C-H3K4me3 | 30,395,476 | 18,165,348 | 59.76% | bam.bowtie/RCH-ACV-2C-H3K4me3.bt2stats.html |
| RCH-ACV-2C-IgG | 33,065,209 | 19,548,674 | 59.12% | bam.bowtie/RCH-ACV-2C-IgG.bt2stats.html |
| RCH-ACV-9B-H3K4me3 | 28,145,143 | 16,402,753 | 58.28% | bam.bowtie/RCH-ACV-9B-H3K4me3.bt2stats.html |
| RCH-ACV-9B-IgG | 30,592,417 | 16,566,653 | 54.15% | bam.bowtie/RCH-ACV-9B-IgG.bt2stats.html |
| RCH-ACV-2C-HA-Tag-Rep1 | 21,866,097 | 8,737,989 | 39.96% | bam.bowtie/RCH-ACV-2C-HA-Tag-Rep1.bt2stats.html |
| RCH-ACV-2C-HA-Tag-Rep2 | 23,333,771 | 11,219,364 | 48.08% | bam.bowtie/RCH-ACV-2C-HA-Tag-Rep2.bt2stats.html |
| RCH-ACV-9B-HA-Tag-Rep1 | 27,342,579 | 15,750,369 | 57.60% | bam.bowtie/RCH-ACV-9B-HA-Tag-Rep1.bt2stats.html |
| RCH-ACV-9B-HA-Tag-Rep2 | 24,137,270 | 12,511,024 | 51.83% | bam.bowtie/RCH-ACV-9B-HA-Tag-Rep2.bt2stats.html |
Table 6. Number of alignments to genome.
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4. Genome coverage
The following table reports the overall and effective genome coverage in each sample. The Total nt column reports
the total number of nucleotides sequenced, i.e. the number of aligned reads times the length of each read. Coverage is this number
divided by the size of the genome. Effective bp reports the number of bases in the genome having coverage greater than 5, and the
Effective Perc column shows what percentage this is of the genome size. Note that, especially in the case of RNA-seq, the effective
genome size may be much smaller than the full size. Eff Coverage is the average coverage over the effectively covered fraction of
the genome.
| Name | Total nt | Coverage | Effective bp | Effective Perc | Eff Coverage |
| RCH-ACV-2C-H3K4me3 | 2,419,725,027 | 0.78 | 43,801,966 | 1.40% | 55.24 |
| RCH-ACV-2C-IgG | 547,658,302 | 0.18 | 62,503,598 | 2.00% | 8.76 |
| RCH-ACV-9B-H3K4me3 | 2,053,976,029 | 0.67 | 46,687,135 | 1.50% | 43.99 |
| RCH-ACV-9B-IgG | 638,839,892 | 0.21 | 70,755,942 | 2.30% | 9.03 |
| RCH-ACV-2C-HA-Tag-Rep1 | 112,845,443 | 0.04 | 9,719,989 | 0.30% | 11.61 |
| RCH-ACV-2C-HA-Tag-Rep2 | 284,388,652 | 0.09 | 30,781,858 | 1.00% | 9.24 |
| RCH-ACV-9B-HA-Tag-Rep1 | 896,286,236 | 0.29 | 100,356,568 | 3.30% | 8.93 |
| RCH-ACV-9B-HA-Tag-Rep2 | 354,323,109 | 0.11 | 38,220,986 | 1.20% | 9.27 |
Table 7. Genome coverage by sample.
The following table reports the overall and effective genome coverage in each condition.
| Name | Total nt | Coverage | Effective bp | Effective Perc | Eff Coverage |
| WT-H3K4me3 | 2,419,725,027 | 0.78 | 43,801,966 | 1.40% | 55.24 |
| MUT-H3K4me3 | 2,053,976,029 | 0.67 | 46,687,135 | 1.50% | 43.99 |
| WT-HA | 878,974,228 | 0.28 | 103,640,157 | 3.40% | 8.48 |
| MUT-HA | 0 | 0.00 | 0 | 0.00% | 0.00 |
Table 8. Genome coverage by condition
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5. Peak detection
Peak detection was performed using SEACR with the following options: mode=stringent, normalization=True.
The following table shows the number of peaks found for each condition.
Table 9. Peaks detected by SEACR and their classification in genomic regions.
The following histogram shows the distribution of peak locations in the different conditions.
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6. Fraction of Reads in Peaks
The Fraction of Reads in Peaks (FRIP) is the fraction of reads that fall in regions called as peaks, out of all aligned peaks.
| Condition | Reads | Reads in peaks | FRIP |
| WT-H3K4me3 | 44,700,733 | 23,234,585 | 51.98% |
| MUT-H3K4me3 | 41,551,817 | 18,844,062 | 45.35% |
| WT-HA | 57,684,898 | 0 | 0.00% |
| MUT-HA | 78,736,504 | 0 | 0.00% |
Table 10. Fraction of Reads in Peaks
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7. Differential peak detection
The following table reports peaks that are increased, decreased, or unchanged in each contrast. Note that these results are simply based on the fold change of the peak sizes in the two conditions,
with no statistical significance information, using a Log2(FC) threshold of 1.0. More accurate differential analysis can be performed with DASA.
Show values | percentages
Table 11. Differential peak analysis results.
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8. MultiQC report
MultiQC is a general Quality Control tool for a large number of bioinformatics pipelines. The report
on this analysis (generated using MultiQC version 1.12) is available here:
MultiQC report
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9. UCSC hub
UCSC Genome Browser: use the previous link to display the data tracks automatically, or copy the the URL https://lichtlab.cancer.ufl.edu/reports/NSD2//NSD_CR_20230612/NSD_CR_20230612/hub.txt and paste it into the "My Hubs" form in this page.
WashU EpiGenome Browser: use the previous link to display the data tracks automatically, or copy the following URL into the "Datahub by URL Link" field: https://lichtlab.cancer.ufl.edu/reports/NSD2//NSD_CR_20230612/NSD_CR_20230612/hub.json.
Completed: 6-20-2023@10:22 |
| © 2023, A. Riva, University of Florida. |
