fastp
MultiQC
fastp | MultiQC | |
---|---|---|
9 | 5 | |
1,775 | 1,173 | |
2.3% | 1.5% | |
4.7 | 9.7 | |
27 days ago | 2 days ago | |
C++ | JavaScript | |
MIT License | GNU General Public License v3.0 only |
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fastp
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R pipelines for bulk RNA-seq analyses
fastp + multiQC + Salmon + DESeq2 all some nextflow workflow. It is a good exercise (not complicated) to create the pipeline from scratch the first time to properly understand each tool.
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NHI Genome Studies: Mexico Govt Sept 12 Congressional hearing
1) QC the data with fastp. This'll trim out adapters and toss reads that are poor quality.
- Illumina adapters and quality trimming
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Low-complexity sequence filtering tool
fastp has an adjustable low complexity filter option.
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Can you evaluate my pipeline?
- in terms of preprocessing and QC, I prefer fastp (https://github.com/OpenGene/fastp)
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Current QC tools for short read and long read sequencing
I generally use fastp as an all-in-one tool for short reads: https://github.com/OpenGene/fastp
- Qurstion about automating trimming process
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What methods (conda installable only please) can you use to determine the complexity of a fastq file? (e.g., kmer analysis)
I don't know if this fits exactly what you need, but I'm using fastp to check my fastq.gz files lately: https://github.com/OpenGene/fastp. You can install it via conda.
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A tool to count basepair in fastq file
If you also need some other basic statistics or want to filter the reads you can try fastp (https://github.com/OpenGene/fastp). If only the basepair count is needed, awk might be the fastest solution as suggested before.
MultiQC
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R pipelines for bulk RNA-seq analyses
fastp + multiQC + Salmon + DESeq2 all some nextflow workflow. It is a good exercise (not complicated) to create the pipeline from scratch the first time to properly understand each tool.
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RNA-seq analysis
I would recommend looking at the pages for FastQC and MultiQC. I run FastQC on my fastq files, then MultiQC on them to collect all that individual data into one report. You can also use MultiQC to analyze the quality of your alignments, at least after using STAR aligner (probably others too, I just have only used STAR aligned).
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How to use MultiQC? I am trying to run it to compile the summary from my FASTQC but I keep getting the "Sample has no read" error.
If that all checks out then I would have to see more of your files in order to help, sorry. Submitting the issue at https://github.com/ewels/MultiQC/issues would help you more
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How can I keep Docker MultiQC from ignoring my large files?
I have seen this Github thread, but it is not applicable for me because I am not running MultiQC natively, I am running a docker version of it in HPC.
What are some alternatives?
galaxy - Data intensive science for everyone.
finviz - Unofficial API for finviz.com
readfq - A simple tool to calculate reads number and total base count in FASTQ file
Sooty - The SOC Analysts all-in-one CLI tool to automate and speed up workflow.
glslSmartDeNoise - Fast glsl deNoise spatial filter, with circular gaussian kernel, full configurable
awesome-single-cell - Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.
nextclade - Viral genome alignment, mutation calling, clade assignment, quality checks and phylogenetic placement
tm_calculator_gui - Calculates the melting temperature(in Celsius) of a user imported forward and reverse primer based on primer blast default parameters & pcr additives
readfq - Fast multi-line FASTA/Q reader in several programming languages
pyrodigal - Cython bindings and Python interface to Prodigal, an ORF finder for genomes and metagenomes. Now with SIMD!
seqtk - Toolkit for processing sequences in FASTA/Q formats
Osintgram - Osintgram is a OSINT tool on Instagram. It offers an interactive shell to perform analysis on Instagram account of any users by its nickname