08 Sequencing File Types - NU-CPGME/quest_genomics_2025 GitHub Wiki
February 2025
Egon A. Ozer, MD PhD ([email protected])
Ramon Lorenzo Redondo, PhD ([email protected])
There are a certain file types you can expect to encounter consistently when working with sequencing and genomics data. This is not intended to be an exhaustive list, but more if a quick introduction and a reference.
Section 1 - FASTA
FASTA format is the most widely used file format for storing sequence data.
The basic format of a fasta file is a header line that starts with the greater-than sign ">" followed by identifier information, there can be as much or as little information on this line as you want. Spaces and most special characters are allowed, though be aware some programs will trim after spaces.
The next line and all subsequent lines after the header line contain the sequence associated with the header line. The sequence can all be on one line or split across several lines. Spaces and skipped lines are also allowed.
FASTA Example 1:
>AB040536.1:142-1209 Streptococcus pyogenes fbaA gene for fibronectin-binding protein, complete cds
ATGCGTAGAGCAGAAAATAACAAACACAGCCGCTATTCCATTCGCAAACTGAGCGTTGGGGTAACGAGTA
TAGCAATTGCGAGTCTCTTTTTAGGAAAGGTTGCCTATGCCGTAGATGGCATCCCTCCAATCTCTCTTAC
TCAAAAGACTACAGCCACTACATCAGAAAATTGGCATCATATTGATAAGGATGGCCTTATTCCTTTAGGT
ATAAGCTTAGAAGCTGCCAAAGAGGAATTTAAAAAAGAAGTAGAAGAATCACGTTTATCTGAAGCACAAA
AAGAAACGTATAAACAAAAAATTAAAACTGCACCAGACAAAGATAAGCTATTATTCACGTATCATAGTGA
GTATATGACAGCCGTTAAGGATCTTCCAGCGTCTACTGAGTCTACTACTCAGCCAGTTGAGGCACCCGTG
CAGGAGACACAGGCATCAGCTTCAGATTCGATGGTGACAGGTGATTCAACATCAGTTACGACTGATTCTC
CTGAGGAAACCCCATCTTCGGAAAGTCCAGTGGCCCCAGCTTTATCTGAGGCTCCAGCTCAACCAGCTGA
GAGTGAGGAACCTTCAGTAGCAGCATCTTCTGAGGAAACCCCATCTCCATCAACTCCAGCAGCCCCATCA
ACTCCAGCGGCTCCAGAAACTCCTGAAGAACCAGCAGCTCCATCTCAACCAGCTGAGAGTGAAGAATCTT
CAGTAGCAGCTACGACAAGCCCGTCTCCATCAACTCCAGCTGAATCAGAGACTCAGACGCCACCAGCTGT
TACTAAAGACTCTGATAAGCCATCTTCAGCAGCTGAAAAACCAGCAGCCTCTTCACTTGTTTCAGAACAA
ACCGTTCAACAACCAACTTCAAAGAGATCTTCTGATAAAAAAGAAGAGCAAGAACAGTCTTACTCTCCAA
ATCGCTCATTGTCAAGACAGGTTAGGGCCCATGAGTCAGGTAAGTACTTGCCTTCAACAGGTGAAAAAGC
ACAGCCACTCTTTATAGCTACTATGACTTTGATGTCTCTATTTGGCAGTCTTTTAGTCACAAAACGCCAA
AAAGAAACTAAAAAATAG
A single fasta file can contain multiple separate sequences as long as they are separated by distinct header lines.
FASTA Example 2:
>NODE_29_length_255_cov_42.625000
TTTAATTTGCGTTTGAACTTACTCGTTCCTTCTGTCGCTGACAGATTTATTTCTCGTTTC
TTGACGGGTAATATGTCTCCATATCACCCTCACGTTTGGTTCGTCTTATTCAGTTCTCAA
AGGTCTTCTAATCGGGAAGACAGGATTCGAACCTGCGACACCTTGGTCCCAAACCAAGTA
CTCTACCAAGCTGAGCTACTTCCCGAACTGATGCACCCTAGAGGAGTCGAACCTCTAACC
GCCTGATTCGTAGTC
>NODE_30_length_205_cov_19.102564
TCGAACCCGTGTTACCGCCGTGAAAAGGCGGTGTCTTAACCCCTTGACCAACGGACCATA
ATAATATAATTATAGATAATGGGCACGAGTGGACTCGAACCACCGACCTCACGCTTATCA
GGCGTGCGCTCTAACCACCTGAGCTACGCGCCCAAGCTTTTATTGATATAGCTTGGGAAA
ACTATAAAGCGGGTGACGAGAATCG
FASTA sequences can contain either nucleotide or amino acid sequences.
FASTA Example 3:
>BAB62098.1 fibronectin-binding protein [Streptococcus pyogenes]
MRRAENNKHSRYSIRKLSVGVTSIAIASLFLGKVAYAVDGIPPISLTQKTTATTSENWHHIDKDGLIPLG
ISLEAAKEEFKKEVEESRLSEAQKETYKQKIKTAPDKDKLLFTYHSEYMTAVKDLPASTESTTQPVEAPV
QETQASASDSMVTGDSTSVTTDSPEETPSSESPVAPALSEAPAQPAESEEPSVAASSEETPSPSTPAAPS
TPAAPETPEEPAAPSQPAESEESSVAATTSPSPSTPAESETQTPPAVTKDSDKPSSAAEKPAASSLVSEQ
TVQQPTSKRSSDKKEEQEQSYSPNRSLSRQVRAHESGKYLPSTGEKAQPLFIATMTLMSLFGSLLVTKRQ
KETKK
Section 2 - FASTQ
FASTQ files usually contain sequence read data.
Each individual sequence record in a FASTQ file consists of four lines:
- Sequence identifier, starts with
@character - Nucleotide sequence
- Separator line, starts with
+character - Quality values for the sequence in line 2
FASTQ Example (Two sequence reads):
@M01915:185:000000000-JLJ5N:1:1101:12139:1000 1:N:0:TAAGGCGA+GTAAGGAG
NGTTAGTCTAGCTGGAGAAAAGTCCAGACCGGTTAAACTAAAAGATGTGGATAATATTAGTTATCACAGAACACAGACTG
+
#8ACCGGGGGGGGGGFGGGGGGGGGGGFGC@EGGGGFGGGGGFGFGGGFCGGGFGGGGGGGGFGGGGFGGGGGGGGFFGG
@M01915:185:000000000-JLJ5N:1:1101:17584:1000 1:N:0:TAAGGCGA+GTAAGGAG
NTAACGTCAATTTCCTGCTGATTTCCAAAACGGATAACCATCTGATTTTCTGGAAGATATGGGTCAATAATCGGATCTCC
+
#8ACCGGGGGGGGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFGGGGG<FGGGGGGGGGDG?FFGFGCFFEGGGFGG
Each letter in line 4 represents the "Phred" quality score for its corresponding base in line 2. The letters can be translated to values indicating the probability that the corresponding base is incorrectly called. These values are assigned by the sequencing instrument during the sequencing and base-calling process. For more info on Phred scores, see here.
Section 3 - GenBank
GenBank-formatted files(.gbk), sometimes referred to as GenBank Flat Files (.gbff), are used for storing detailed annotation data and other metadata about a sequence as well as often the nucleotide sequence itself. These files can contain information about a single gene or an entire genome.
GenBank Example 1 (Two sequence reads):
LOCUS NZ_CP010450 1791401 bp DNA circular CON 15-JAN-2022
DEFINITION Streptococcus pyogenes strain NGAS638 chromosome, complete genome.
ACCESSION NZ_CP010450
VERSION NZ_CP010450.1
DBLINK BioProject: PRJNA224116
BioSample: SAMN03274510
Assembly: GCF_001267845.1
KEYWORDS RefSeq.
SOURCE Streptococcus pyogenes
ORGANISM Streptococcus pyogenes
Bacteria; Firmicutes; Bacilli; Lactobacillales; Streptococcaceae;
Streptococcus.
REFERENCE 1 (bases 1 to 1791401)
AUTHORS Fittipaldi,N.
TITLE Direct Submission
JOURNAL Submitted (05-JAN-2015) Public Health Ontario, 661 University Ave,
Toronto, Ontario M5G 1M1, Canada
FEATURES Location/Qualifiers
source 1..1791401
/organism="Streptococcus pyogenes"
/mol_type="genomic DNA"
/strain="NGAS638"
/db_xref="taxon:1314"
gene join(1790598..1791401,1..3)
/locus_tag="SD90_RS00005"
/old_locus_tag="SD90_00005"
CDS join(1790598..1791401,1..3)
/locus_tag="SD90_RS00005"
/old_locus_tag="SD90_00005"
/inference="COORDINATES: similar to AA
sequence:RefSeq:WP_010922805.1"
/note="Derived by automated computational analysis using
gene prediction method: Protein Homology."
/codon_start=1
/transl_table=11
/product="ParB/RepB/Spo0J family partition protein"
/protein_id="WP_011106931.1"
/translation="MFLILSRNSLMTKELLIDLPIEDIITNPYQPRIQFNQRELQDLA
TSIKSNGLIQPIIVRKSDIFGYELVAGERRLKASKMAGLKKVPAIIKKISTLESMQQA
IVENLQRSNLNAIEEAKAYQLLVEKKHMTHDEIAKYMGKSRPYISNTLRLLQLPAPII
KAIEEGKISAGHARALLTLSDDKQQLYLTHKIQNEGLSVRQIEQLVTSTPSSKLSKKT
KNIFATSLEKQLAKSLGLSVNMKLTANHSGYLQISFSNDDELNRIINKLK"
gene 236..1591
/gene="dnaA"
/locus_tag="SD90_RS00010"
/old_locus_tag="SD90_00010"
CDS 236..1591
/gene="dnaA"
/locus_tag="SD90_RS00010"
/old_locus_tag="SD90_00010"
/inference="COORDINATES: similar to AA
sequence:RefSeq:WP_012657571.1"
/note="Derived by automated computational analysis using
gene prediction method: Protein Homology."
/codon_start=1
/transl_table=11
/product="chromosomal replication initiator protein DnaA"
/protein_id="WP_002987659.1"
/translation="MTENEQIFWNRVLELAQSQLKQATYEFFVHDARLLKVDKHIATI
YLDQMKELFWEKNLKDVILTAGFEVYNAQISVDYVFEEDLMIEQNQTKINQKPKQQAL
NSLPTVTSDLNSKYSFENFIQGDENRWAVAASIAVANTPGTTYNPLFIWGGPGLGKTH
LLNAIGNSVLLENPNARIKYITAENFINEFVIHIRLDTMDELKEKFRNLDLLLIDDIQ
SLAKKTLSGTQEEFFNTFNALHNNNKQIVLTSDRTPDHLNDLEDRLVTRFKWGLTVNI
TPPDFETRVAILTNKIQEYNFIFPQDTIEYLAGQFDSNVRDLEGALKDISLVANFKQI
DTITVDIAAEAIRARKQDGPKMTVIPIEEIQAQVGKFYGVTVKEIKATKRTQNIVLAR
QVAMFLAREMTDNSLPKIGKEFGGRDHSTVLHAYNKIKNMISQDESLRIEIETIKNKI
K"
ORIGIN
1 tagcttgttg atattctgtt ttttcttttt tagttttcca cataaaaaat agttgaaaac
61 aatagcggtg tcaccttaaa atgacttttc cacaggttgt ggagaaccca aattaacagt
121 gttaatttat tttccacaga ttgtggaaaa actaactatt atccattgtt ctgtggaaaa
181 ctagaatagt ttgtggtaga atagttctag aattatccac aagaaggaac ctagtatgac
241 tgaaaatgaa caaatttttt ggaacagggt cttggaatta gctcagagtc aattaaaaca
301 ggcaacttat gaattttttg ttcatgatgc ccgtctatta aaggtcgata agcatattgc
361 aactatttac ttagatcaaa tgaaagaact cttttgggaa aaaaatctta aagatgttat
421 tcttactgct ggttttgaag tttataacgc tcaaatttct gttgactatg ttttcgaaga
481 agacctaatg attgagcaaa atcagaccaa aatcaatcaa aaacctaagc agcaagcctt
541 aaattctttg cctactgtta cttcagattt aaactcgaaa tatagttttg aaaactttat
601 tcaaggagat gaaaatcgtt gggctgttgc tgcttcaata gcagtagcta atactcctgg
661 aactacctat aatcctttgt ttatttgggg tggccctggg cttggaaaaa cccatttatt
721 aaatgctatt ggtaattctg tactattaga aaatccaaat gctcgaatta aatatatcac
781 agctgaaaac tttattaatg agtttgttat ccatattcgc cttgatacca tggatgaatt
841 gaaagaaaaa tttcgtaatt tagatttact ccttattgat gatatccaat ctttagctaa
901 aaaaacgctc tctggaacac aagaagagtt ctttaatact tttaatgcac ttcataataa
961 taacaaacaa attgtcctaa caagcgaccg tacaccagat catctcaatg atttagaaga
1021 tcgattagtt actcgtttta aatggggatt aacagtcaat atcacacctc ctgattttga
1081 aacacgagtg gctattttga caaataaaat tcaagaatat aactttattt ttcctcaaga
1141 taccattgag tatttggctg gtcaatttga ttctaatgtc agagatttag aaggtgcctt
1201 aaaagatatt agtctggttg ctaatttcaa acaaattgac acgattactg ttgacattgc
1261 tgccgaagct attcgcgcca gaaagcaaga tggacctaaa atgacagtta ttcccatcga
1321 agaaattcaa gcgcaagttg gaaaatttta cggtgttacc gtcaaagaaa ttaaagctac
1381 taaacgaaca caaaatattg ttttagcaag acaagtagct atgtttttag cacgtgaaat
1441 gacagataac agtcttccta aaattggaaa agaatttggt ggcagagacc attcaacagt
1501 actccatgcc tataataaaa tcaaaaacat gatcagccag gacgaaagcc ttaggatcga
1561 aattgaaacc ataaaaaaca aaattaaata acatgtggaa aagaatatct tttatgaaat
//
Like FASTA files, GenBank files can also contain information about multiple separate sequences. Information belonging to separate sequences are separated by lines containing two forward slashes //
There is nice example GenBank file and detailed explainer at NCBI here.
Section 4 - SAM / BAM
SAM-formatted files are used to store read alignment information.
In SAM files, each line corresopnds to a single sequence read. Information about the read is organized into columns:
| Col | Field | Description |
|---|---|---|
| 1 | QNAME | Query template name, i.e. read ID |
| 2 | FLAG | Bitwise flag with read mapping information. See below for more information. |
| 3 | RNAME | Reference sequence name |
| 4 | POS | Leftmost mapping position of the read on the reference sequence |
| 5 | MAPQ | Mapping quality score |
| 6 | CIGAR | Information about which portions of the read mapped. More detail on CIGAR strings can be found in the SAM manual or this brief explainer |
| 7 | RNEXT | Read ID of the paired read (if using paired reads) |
| 8 | PNEXT | Leftmost mapping position of the paired read |
| 9 | TLEN | Template length, i.e. distance between the aligned read pairs |
| 10 | SEQ | Sequence of the read |
| 11 | QUAL | Quality score of the read |
Many alignment programs will include extra data about the alignment in columns 12 and up. You should refer to the alignment software's manual for help interpreting these data, if interested.
SAM Flags:
The second column in a SAM aligment file is an integer that represents the flag value. This value can be decoded to identify several properties of the alignment for an individual read such as whether it's mapped on the forward or reverse strand of reference sequence or whether it is part of a pair of mapped reads. There is a useful website that allows you to quickly decode individual flag values: Decoding SAM Flags
SAM Example:
M01915:185:000000000-JLJ5N:1:2117:4014:11709 147 NZ_CP010450 2743 60 85M = 2743 -85 ACCTTATTGAGTCTTTAAAAGCTATTAAAAGTGAAACAGTAAAAATTCATTTCTTATCACCAGTTCGACCATTCACCCTAACACC AGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGCCCCC NM:i:0 MD:Z:85 AS:i:85 XS:i:0 RG:Z:GAS_alignment MQ:i:60 MC:Z:85M ms:i:3207
M01915:185:000000000-JLJ5N:1:1115:16084:21280 163 NZ_CP010450 2747 60 100M = 2747 100 TATTGAGTCTTTAAAAGCTATTAAAAGTGAAACAGTAAAAATTCATTTCTTATCACCAGTTCGACCATTCACCCTAACACCAGGCGATGAGGAAGAAAGT CCCCCGGGGGGGGFFGGGGGGGFGFGGGGGGGGGGGGGFGFFGGGFGGFGGGGGGFGGGFFFGGGDFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFC NM:i:0 MD:Z:100 AS:i:100 XS:i:0 RG:Z:GAS_alignment MQ:i:60 MC:Z:100M ms:i:3766
M01915:185:000000000-JLJ5N:1:1115:16084:21280 83 NZ_CP010450 2747 60 100M = 2747 -100 TATTGAGTCTTTAAAAGCTATTAAAAGTGAAACAGTAAAAATTCATTTCTTATCACCAGTTCGACCATTCACCCTAACACCAGGCGATGAGGAAGAAAGT GGGGFGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGGFFFFGGGGGGGGGGFEGGGGGGGGGGGGDGGFGGGGGGFFGGGGGGGGGGGGGGGGCCCCC NM:i:0 MD:Z:100 AS:i:100 XS:i:0 RG:Z:GAS_alignment MQ:i:60 MC:Z:100M ms:i:3758
BAM files contain the same data as SAM files, but are converted to a binary format to reduce storage requirements as well as for more rapid access by programs that read alignment data. Unlike a SAM file, you won't be able to open and read a BAM file in a text editing program.
SAM files represent alignments one read at a time. To summarize the base calls of the alignment per position along the reference sequence, the SAM alignment can be converted to the Pileup format by programs such as samtools.
Pileup columns:
| Col | Description |
|---|---|
| 1 | Sequence identifier |
| 2 | Position in sequence (1-based) |
| 3 | Reference base |
| 4 | Number of aligned reads |
| 5 | Bases at that position from aligned reads |
| 6 | Base quality scores, in Phred format |
Pileup example:
NC_009089.1 2210 A 32 ..,..,,,.,.,,,,...,,,..,,.,.C,,. A>GDFGGGDGFDFD,GGGGEFGGGEF,F,GCF
NC_009089.1 2211 A 32 ..,..,,,.,.,,,,...,,,.,,,.,..,,. ECGDFGGGCGFDDEGGGGFFEGGE=F=FCGFG
NC_009089.1 2212 T 32 CCcCCcccCcCccccCCCcccCcccCcC.ccC E7GFCGGG,GG>66EGGGGECGDCGE+E,GEG
NC_009089.1 2212 G 32 ..,..,,,.,.,,,,...,,,.,,,.,..,,. E:GADGGGCG:GFGEGGGGFFGGFFG<F,GFG
NC_009089.1 2214 A 32 ..,..,,,.,.,,,,...,,,.,,,.,..,,. F5GFGGGFEGFGDEGGGGG@GGGGEG:E;G=C
Bases column interpretation:
- . (dot): Base matches the reference on the forward strand
- , (comma): Base matches the reference on the reverse strand
- AGTCN (upper case): Base that did not match the reference on the forward strand
- agtcn (lower case): Base that did not match the reference on the reverse strand
- ^ (caret): Start of a read segment followed by mapping quality
- $ (dollar): End of a read segment
File containing sequence variation data, i.e. base calls at each position based on sequence alignments. Also contains supporting information.
VCF columns:
| Col | Field | Description |
|---|---|---|
| 1 | CHROM | The name of the sequence |
| 2 | POS | Position of the variation on the sequence (1-based) |
| 3 | ID | Identifier of the variation; "." if unknown |
| 4 | REF | Reference base |
| 5 | ALT | Alternative base(s) based on alignment |
| 6 | QUAL | Quality score of the base call(s) |
| 7 | FILTER | Variation filter results; "." if unknown |
| 8 | INFO | Descriptons of the variation. See here for more information. |
| 9 | FORMAT | Descriptions of the samples. See link above. |
- | SAMPLEs | Per-sample balues for each of the fields listed in FORMAT
VCF example:
NC_009089.1 2210 . A . 117 . DP=32;AF1=0;AC1=0;DP=13,16,0,0;MQ=60;FQ=-114 PL:DP:SP 0:29:0
NC_009089.1 2211 . A . 126 . DP=32;AF1=0;AC1=0;DP=14,18,0,0;MQ=60;FQ=-123 PL:DP:SP 0:32:0
NC_009089.1 2212 . T C 222 . DP=32;VDB=9.43e-02;AF1=1;AC1=2;DP=4,0,11,15;MQ=60;FQ=-105 PL:DP:SP 0:29:0
NC_009089.1 2213 . G . 123 . DP=32;AF1=0;AC1=0;DP=13,18,0,0;MQ=60;FQ=-120 PL:DP:SP 0:31:0
NC_009089.1 2214 . A . 120 . DP=32;AF1=0;AC1=0;DP=13,17,0,0;MQ=60;FQ=-117 PL:DP:SP 0:30:0
There are a number of differnt formats for storing phylogenetic trees or other relational data. One of the most common and simplest formats is Newick format. A relative of the Newick tree files is the Nexus format which contains a newick-formatted tree but can also encode other data associated with the tree.
Common suffixes for tree files are .tre and .nwk, but there are others out there.
Newick Tree File Example:
(COV0536:0.000228603,(COV0118:0.000114239,(COV0074:0.000038079,COV0420:0.000076177)0.997:0.000342946)1.000:0.000342930,(COV1650:0.000114265,COV0415:0.000000005)0.438:0.000000005);
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